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Sample records for learning feedforward component

  1. Structural learning in feedforward and feedback control.

    Science.gov (United States)

    Yousif, Nada; Diedrichsen, Jörn

    2012-11-01

    For smooth and efficient motor control, the brain needs to make fast corrections during the movement to resist possible perturbations. It also needs to adapt subsequent movements to improve future performance. It is important that both feedback corrections and feedforward adaptation need to be made based on noisy and often ambiguous sensory data. Therefore, the initial response of the motor system, both for online corrections and adaptive responses, is guided by prior assumptions about the likely structure of perturbations. In the context of correcting and adapting movements perturbed by a force field, we asked whether these priors are hard wired or whether they can be modified through repeated exposure to differently shaped force fields. We found that both feedback corrections to unexpected perturbations and feedforward adaptation to a new force field changed, such that they were appropriate to counteract the type of force field that participants had experienced previously. We then investigated whether these changes were driven by a common mechanism or by two separate mechanisms. Participants experienced force fields that were either temporally consistent, causing sustained adaptation, or temporally inconsistent, causing little overall adaptation. We found that the consistent force fields modified both feedback and feedforward responses. In contrast, the inconsistent force field modified the temporal shape of feedback corrections but not of the feedforward adaptive response. These results indicate that responses to force perturbations can be modified in a structural manner and that these modifications are at least partly dissociable for feedback and feedforward control.

  2. Application of parsimonious learning feedforward control to mechatronic systems

    NARCIS (Netherlands)

    de Vries, Theodorus J.A.; Velthuis, W.J.R.; Idema, L.J.

    2001-01-01

    For motion control, learning feedforward controllers (LFFCs) should be applied when accurate process modelling is difficult. When controlling such processes with LFFCs in the form of multidimensional B-spline networks, large network sizes and a poor generalising ability may result, known as the

  3. The Roles of Feedback and Feedforward as Humans Learn to Control Unknown Dynamic Systems.

    Science.gov (United States)

    Zhang, Xingye; Wang, Shaoqian; Hoagg, Jesse B; Seigler, T Michael

    2018-02-01

    We present results from an experiment in which human subjects interact with an unknown dynamic system 40 times during a two-week period. During each interaction, subjects are asked to perform a command-following (i.e., pursuit tracking) task. Each subject's performance at that task improves from the first trial to the last trial. For each trial, we use subsystem identification to estimate each subject's feedforward (or anticipatory) control, feedback (or reactive) control, and feedback time delay. Over the 40 trials, the magnitudes of the identified feedback controllers and the identified feedback time delays do not change significantly. In contrast, the identified feedforward controllers do change significantly. By the last trial, the average identified feedforward controller approximates the inverse of the dynamic system. This observation provides evidence that a fundamental component of human learning is updating the anticipatory control until it models the inverse dynamics.

  4. Biomimetic Hybrid Feedback Feedforward Neural-Network Learning Control.

    Science.gov (United States)

    Pan, Yongping; Yu, Haoyong

    2017-06-01

    This brief presents a biomimetic hybrid feedback feedforward neural-network learning control (NNLC) strategy inspired by the human motor learning control mechanism for a class of uncertain nonlinear systems. The control structure includes a proportional-derivative controller acting as a feedback servo machine and a radial-basis-function (RBF) NN acting as a feedforward predictive machine. Under the sufficient constraints on control parameters, the closed-loop system achieves semiglobal practical exponential stability, such that an accurate NN approximation is guaranteed in a local region along recurrent reference trajectories. Compared with the existing NNLC methods, the novelties of the proposed method include: 1) the implementation of an adaptive NN control to guarantee plant states being recurrent is not needed, since recurrent reference signals rather than plant states are utilized as NN inputs, which greatly simplifies the analysis and synthesis of the NNLC and 2) the domain of NN approximation can be determined a priori by the given reference signals, which leads to an easy construction of the RBF-NNs. Simulation results have verified the effectiveness of this approach.

  5. Enhanced HMAX model with feedforward feature learning for multiclass categorization

    Directory of Open Access Journals (Sweden)

    Yinlin eLi

    2015-10-01

    Full Text Available In recent years, the interdisciplinary research between neuroscience and computer vision has promoted the development in both fields. Many biologically inspired visual models are proposed, and among them, the Hierarchical Max-pooling model (HMAX is a feedforward model mimicking the structures and functions of V1 to posterior inferotemporal (PIT layer of the primate visual cortex, which could generate a series of position- and scale- invariant features. However, it could be improved with attention modulation and memory processing, which are two important properties of the primate visual cortex. Thus, in this paper, based on recent biological research on the primate visual cortex, we still mimic the first 100-150 milliseconds of visual cognition to enhance the HMAX model, which mainly focuses on the unsupervised feedforward feature learning process. The main modifications are as follows: 1 To mimic the attention modulation mechanism of V1 layer, a bottom-up saliency map is computed in the S1 layer of the HMAX model, which can support the initial feature extraction for memory processing; 2 To mimic the learning, clustering and short-term memory to long-term memory conversion abilities of V2 and IT, an unsupervised iterative clustering method is used to learn clusters with multiscale middle level patches, which are taken as long-term memory; 3 Inspired by the multiple feature encoding mode of the primate visual cortex, information including color, orientation, and spatial position are encoded in different layers of the HMAX model progressively. By adding a softmax layer at the top of the model, multiclass categorization experiments can be conducted, and the results on Caltech101 show that the enhanced model with a smaller memory size exhibits higher accuracy than the original HMAX model, and could also achieve better accuracy than other unsupervised feature learning methods in multiclass categorization task.

  6. Enhanced HMAX model with feedforward feature learning for multiclass categorization.

    Science.gov (United States)

    Li, Yinlin; Wu, Wei; Zhang, Bo; Li, Fengfu

    2015-01-01

    In recent years, the interdisciplinary research between neuroscience and computer vision has promoted the development in both fields. Many biologically inspired visual models are proposed, and among them, the Hierarchical Max-pooling model (HMAX) is a feedforward model mimicking the structures and functions of V1 to posterior inferotemporal (PIT) layer of the primate visual cortex, which could generate a series of position- and scale- invariant features. However, it could be improved with attention modulation and memory processing, which are two important properties of the primate visual cortex. Thus, in this paper, based on recent biological research on the primate visual cortex, we still mimic the first 100-150 ms of visual cognition to enhance the HMAX model, which mainly focuses on the unsupervised feedforward feature learning process. The main modifications are as follows: (1) To mimic the attention modulation mechanism of V1 layer, a bottom-up saliency map is computed in the S1 layer of the HMAX model, which can support the initial feature extraction for memory processing; (2) To mimic the learning, clustering and short-term memory to long-term memory conversion abilities of V2 and IT, an unsupervised iterative clustering method is used to learn clusters with multiscale middle level patches, which are taken as long-term memory; (3) Inspired by the multiple feature encoding mode of the primate visual cortex, information including color, orientation, and spatial position are encoded in different layers of the HMAX model progressively. By adding a softmax layer at the top of the model, multiclass categorization experiments can be conducted, and the results on Caltech101 show that the enhanced model with a smaller memory size exhibits higher accuracy than the original HMAX model, and could also achieve better accuracy than other unsupervised feature learning methods in multiclass categorization task.

  7. Learning feedforward controller for a mobile robot vehicle

    NARCIS (Netherlands)

    Starrenburg, J.G.; Starrenburg, J.G.; van Luenen, W.T.C.; van Luenen, W.T.C.; Oelen, W.; Oelen, W.; van Amerongen, J.

    1996-01-01

    This paper describes the design and realisation of an on-line learning posetracking controller for a three-wheeled mobile robot vehicle. The controller consists of two components. The first is a constant-gain feedback component, designed on the basis of a second-order model. The second is a learning

  8. Learning feedback and feedforward control in a mirror-reversed visual environment.

    Science.gov (United States)

    Kasuga, Shoko; Telgen, Sebastian; Ushiba, Junichi; Nozaki, Daichi; Diedrichsen, Jörn

    2015-10-01

    When we learn a novel task, the motor system needs to acquire both feedforward and feedback control. Currently, little is known about how the learning of these two mechanisms relate to each other. In the present study, we tested whether feedforward and feedback control need to be learned separately, or whether they are learned as common mechanism when a new control policy is acquired. Participants were trained to reach to two lateral and one central target in an environment with mirror (left-right)-reversed visual feedback. One group was allowed to make online movement corrections, whereas the other group only received visual information after the end of the movement. Learning of feedforward control was assessed by measuring the accuracy of the initial movement direction to lateral targets. Feedback control was measured in the responses to sudden visual perturbations of the cursor when reaching to the central target. Although feedforward control improved in both groups, it was significantly better when online corrections were not allowed. In contrast, feedback control only adaptively changed in participants who received online feedback and remained unchanged in the group without online corrections. Our findings suggest that when a new control policy is acquired, feedforward and feedback control are learned separately, and that there may be a trade-off in learning between feedback and feedforward controllers. Copyright © 2015 the American Physiological Society.

  9. Feed-Forward Neural Networks and Minimal Search Space Learning

    Czech Academy of Sciences Publication Activity Database

    Neruda, Roman

    2005-01-01

    Roč. 4, č. 12 (2005), s. 1867-1872 ISSN 1109-2750 R&D Projects: GA ČR GA201/05/0557 Institutional research plan: CEZ:AV0Z10300504 Keywords : search space * feed-forward networks * genetic algorithm s Subject RIV: BA - General Mathematics

  10. Postural threat differentially affects the feedforward and feedback components of the vestibular-evoked balance response.

    Science.gov (United States)

    Osler, Callum J; Tersteeg, M C A; Reynolds, Raymond F; Loram, Ian D

    2013-10-01

    Circumstances may render the consequence of falling quite severe, thus maximising the motivation to control postural sway. This commonly occurs when exposed to height and may result from the interaction of many factors, including fear, arousal, sensory information and perception. Here, we examined human vestibular-evoked balance responses during exposure to a highly threatening postural context. Nine subjects stood with eyes closed on a narrow walkway elevated 3.85 m above ground level. This evoked an altered psycho-physiological state, demonstrated by a twofold increase in skin conductance. Balance responses were then evoked by galvanic vestibular stimulation. The sway response, which comprised a whole-body lean in the direction of the edge of the walkway, was significantly and substantially attenuated after ~800 ms. This demonstrates that a strong reason to modify the balance control strategy was created and subjects were highly motivated to minimise sway. Despite this, the initial response remained unchanged. This suggests little effect on the feedforward settings of the nervous system responsible for coupling pure vestibular input to functional motor output. The much stronger, later effect can be attributed to an integration of balance-relevant sensory feedback once the body was in motion. These results demonstrate that the feedforward and feedback components of a vestibular-evoked balance response are differently affected by postural threat. Although a fear of falling has previously been linked with instability and even falling itself, our findings suggest that this relationship is not attributable to changes in the feedforward vestibular control of balance. © 2013 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

  11. Repurposing learning object components

    NARCIS (Netherlands)

    Verbert, K.; Jovanovic, J.; Gasevic, D.; Duval, E.; Meersman, R.

    2005-01-01

    This paper presents an ontology-based framework for repurposing learning object components. Unlike the usual practice where learning object components are assembled manually, the proposed framework enables on-the-fly access and repurposing of learning object components. The framework supports two

  12. Learning to breathe? Feedforward regulation of the inspiratory motor drive.

    Science.gov (United States)

    Zaman, Jonas; Van den Bergh, Omer; Fannes, Stien; Van Diest, Ilse

    2014-09-15

    Claims have been made that breathing is in part controlled by feedforward regulation. In a classical conditioning paradigm, we investigated anticipatory increases in the inspiratory motor drive as measured by inspiratory occlusion pressure (P100). In an acquisition phase, an experimental group (N=13) received a low-intensity resistive load (5 cmH2O/l/s) for three consecutive inspirations as Conditioned Stimulus (CS), preceding a load of a stronger intensity (20 cmH2O/l/s) for three subsequent inspirations as unconditioned stimulus (US). The control group (N=11) received the low-intensity load for six consecutive inspirations. In a post-acquisition phase both groups received the low-intensity load for six consecutive inspirations. Responses to the CS-load only differed between groups during the first acquisition trials and a strong increase in P100 during the US-loads was observed, which habituated across the experiment. Our results suggest that the disruption caused by adding low to moderate resistive loads to three consecutive inspirations results in a short-lasting anticipatory increase in inspiratory motor drive. Copyright © 2014 Elsevier B.V. All rights reserved.

  13. Single-hidden-layer feed-forward quantum neural network based on Grover learning.

    Science.gov (United States)

    Liu, Cheng-Yi; Chen, Chein; Chang, Ching-Ter; Shih, Lun-Min

    2013-09-01

    In this paper, a novel single-hidden-layer feed-forward quantum neural network model is proposed based on some concepts and principles in the quantum theory. By combining the quantum mechanism with the feed-forward neural network, we defined quantum hidden neurons and connected quantum weights, and used them as the fundamental information processing unit in a single-hidden-layer feed-forward neural network. The quantum neurons make a wide range of nonlinear functions serve as the activation functions in the hidden layer of the network, and the Grover searching algorithm outstands the optimal parameter setting iteratively and thus makes very efficient neural network learning possible. The quantum neuron and weights, along with a Grover searching algorithm based learning, result in a novel and efficient neural network characteristic of reduced network, high efficient training and prospect application in future. Some simulations are taken to investigate the performance of the proposed quantum network and the result show that it can achieve accurate learning. Copyright © 2013 Elsevier Ltd. All rights reserved.

  14. Aversive Learning and Appetitive Motivation Toggle Feed-Forward Inhibition in the Drosophila Mushroom Body.

    Science.gov (United States)

    Perisse, Emmanuel; Owald, David; Barnstedt, Oliver; Talbot, Clifford B; Huetteroth, Wolf; Waddell, Scott

    2016-06-01

    In Drosophila, negatively reinforcing dopaminergic neurons also provide the inhibitory control of satiety over appetitive memory expression. Here we show that aversive learning causes a persistent depression of the conditioned odor drive to two downstream feed-forward inhibitory GABAergic interneurons of the mushroom body, called MVP2, or mushroom body output neuron (MBON)-γ1pedc>α/β. However, MVP2 neuron output is only essential for expression of short-term aversive memory. Stimulating MVP2 neurons preferentially inhibits the odor-evoked activity of avoidance-directing MBONs and odor-driven avoidance behavior, whereas their inhibition enhances odor avoidance. In contrast, odor-evoked activity of MVP2 neurons is elevated in hungry flies, and their feed-forward inhibition is required for expression of appetitive memory at all times. Moreover, imposing MVP2 activity promotes inappropriate appetitive memory expression in food-satiated flies. Aversive learning and appetitive motivation therefore toggle alternate modes of a common feed-forward inhibitory MVP2 pathway to promote conditioned odor avoidance or approach. Copyright © 2016 The Author(s). Published by Elsevier Inc. All rights reserved.

  15. Identification of the feedforward component in manual control with predictable target signals.

    Science.gov (United States)

    Drop, Frank M; Pool, Daan M; Damveld, Herman J; van Paassen, Marinus M; Mulder, Max

    2013-12-01

    In the manual control of a dynamic system, the human controller (HC) often follows a visible and predictable reference path. Compared with a purely feedback control strategy, performance can be improved by making use of this knowledge of the reference. The operator could effectively introduce feedforward control in conjunction with a feedback path to compensate for errors, as hypothesized in literature. However, feedforward behavior has never been identified from experimental data, nor have the hypothesized models been validated. This paper investigates human control behavior in pursuit tracking of a predictable reference signal while being perturbed by a quasi-random multisine disturbance signal. An experiment was done in which the relative strength of the target and disturbance signals were systematically varied. The anticipated changes in control behavior were studied by means of an ARX model analysis and by fitting three parametric HC models: two different feedback models and a combined feedforward and feedback model. The ARX analysis shows that the experiment participants employed control action on both the error and the target signal. The control action on the target was similar to the inverse of the system dynamics. Model fits show that this behavior can be modeled best by the combined feedforward and feedback model.

  16. Feedforward self-modeling enhances skill acquisition in children learning trampoline skills.

    Science.gov (United States)

    Ste-Marie, Diane M; Vertes, Kelly; Rymal, Amanda M; Martini, Rose

    2011-01-01

    The purpose of this research was to examine whether children would benefit from a feedforward self-modeling (FSM) video and to explore possible explanatory mechanisms for the potential benefits, using a self-regulation framework. To this end, children were involved in learning two five-skill trampoline routines. For one of the routines, a FSM video was provided during acquisition, whereas only verbal instructions were provided for the alternate routine. The FSM involved editing video footage such that it showed the learner performing the trampoline routine at a higher skill level than their current capability. Analyses of the data showed that while physical performance benefits were observed for the routine that was learned with the FSM video, no differences were obtained in relation to the self-regulatory measures. Thus, the FSM video enhanced motor skill acquisition, but this could not be explained by changes to the varied self-regulatory processes examined.

  17. Feedforward self-modeling enhances skill acquisition in children learning trampoline skills

    Directory of Open Access Journals (Sweden)

    Diane M. Ste-Marie

    2011-07-01

    Full Text Available The purpose of this research was to examine whether children would benefit from a feedforward self-modeling (FSM video and to explore possible explanatory mechanisms for the potential benefits, using a self-regulation framework. To this end, children were involved in learning two five-skill trampoline routines. For one of the routines, a FSM video was provided during acquisition, whereas only verbal instructions were provided for the alternate routine. The FSM involved editing video footage such that it showed the learner performing the trampoline routine at a higher skill level than their current capability. Analyses of the data showed that while physical performance benefits were observed for the routine that was learned with the FSM video, no differences were obtained in relation to the self-regulatory measures. Thus, the FSM video enhanced motor skill acquisition, but this could not be explained by changes to the varied self-regulatory processes examined.

  18. Batch-To-Batch Rational Feedforward Control : From Iterative Learning to Identification Approaches, with Application to a Wafer Stage

    NARCIS (Netherlands)

    Blanken, L.; Boeren, F.A.J.; Bruijnen, D.J.H.; Oomen, T.A.E.

    2017-01-01

    Feedforward control enables high performance for industrial motion systems that perform nonrepeating motion tasks. Recently, learning techniques have been proposed that improve both performance and flexibility to nonrepeating tasks in a batch-To-batch fashion by using a rational parameterization in

  19. A fast and accurate online sequential learning algorithm for feedforward networks.

    Science.gov (United States)

    Liang, Nan-Ying; Huang, Guang-Bin; Saratchandran, P; Sundararajan, N

    2006-11-01

    In this paper, we develop an online sequential learning algorithm for single hidden layer feedforward networks (SLFNs) with additive or radial basis function (RBF) hidden nodes in a unified framework. The algorithm is referred to as online sequential extreme learning machine (OS-ELM) and can learn data one-by-one or chunk-by-chunk (a block of data) with fixed or varying chunk size. The activation functions for additive nodes in OS-ELM can be any bounded nonconstant piecewise continuous functions and the activation functions for RBF nodes can be any integrable piecewise continuous functions. In OS-ELM, the parameters of hidden nodes (the input weights and biases of additive nodes or the centers and impact factors of RBF nodes) are randomly selected and the output weights are analytically determined based on the sequentially arriving data. The algorithm uses the ideas of ELM of Huang et al. developed for batch learning which has been shown to be extremely fast with generalization performance better than other batch training methods. Apart from selecting the number of hidden nodes, no other control parameters have to be manually chosen. Detailed performance comparison of OS-ELM is done with other popular sequential learning algorithms on benchmark problems drawn from the regression, classification and time series prediction areas. The results show that the OS-ELM is faster than the other sequential algorithms and produces better generalization performance.

  20. A Constrained Multi-Objective Learning Algorithm for Feed-Forward Neural Network Classifiers

    Directory of Open Access Journals (Sweden)

    M. Njah

    2017-06-01

    Full Text Available This paper proposes a new approach to address the optimal design of a Feed-forward Neural Network (FNN based classifier. The originality of the proposed methodology, called CMOA, lie in the use of a new constraint handling technique based on a self-adaptive penalty procedure in order to direct the entire search effort towards finding only Pareto optimal solutions that are acceptable. Neurons and connections of the FNN Classifier are dynamically built during the learning process. The approach includes differential evolution to create new individuals and then keeps only the non-dominated ones as the basis for the next generation. The designed FNN Classifier is applied to six binary classification benchmark problems, obtained from the UCI repository, and results indicated the advantages of the proposed approach over other existing multi-objective evolutionary neural networks classifiers reported recently in the literature.

  1. Single-Iteration Learning Algorithm for Feed-Forward Neural Networks

    Energy Technology Data Exchange (ETDEWEB)

    Barhen, J.; Cogswell, R.; Protopopescu, V.

    1999-07-31

    A new methodology for neural learning is presented, whereby only a single iteration is required to train a feed-forward network with near-optimal results. To this aim, a virtual input layer is added to the multi-layer architecture. The virtual input layer is connected to the nominal input layer by a specird nonlinear transfer function, and to the fwst hidden layer by regular (linear) synapses. A sequence of alternating direction singular vrdue decompositions is then used to determine precisely the inter-layer synaptic weights. This algorithm exploits the known separability of the linear (inter-layer propagation) and nonlinear (neuron activation) aspects of information &ansfer within a neural network.

  2. Degraded expression of learned feedforward control in movements released by startle.

    Science.gov (United States)

    Wright, Zachary A; Carlsen, Anthony N; MacKinnon, Colum D; Patton, James L

    2015-08-01

    Recent work has shown that preplanned motor programs can be rapidly released via fast conducting pathways using a startling acoustic stimulus. Our question was whether the startle-elicited response might also release a recently learned internal model, which draws on experience to predict and compensate for expected perturbations in a feedforward manner. Our initial investigation using adaptation to robotically produced forces showed some evidence of this, but the results were potentially confounded by co-contraction caused by startle. In this study, we eliminated this confound by asking subjects to make reaching movements in the presence of a visual distortion. Results show that a startle stimulus (1) decreased performance of the recently learned task and (2) reduced after-effect magnitude. Since the recall of learned control was reduced, but not eliminated during startle trials, we suggest that multiple neural centers (cortical and subcortical) are involved in such learning and adaptation. These findings have implications for motor training in areas such as piloting, teleoperation, sports, and rehabilitation.

  3. An H(∞) control approach to robust learning of feedforward neural networks.

    Science.gov (United States)

    Jing, Xingjian

    2011-09-01

    A novel H(∞) robust control approach is proposed in this study to deal with the learning problems of feedforward neural networks (FNNs). The analysis and design of a desired weight update law for the FNN is transformed into a robust controller design problem for a discrete dynamic system in terms of the estimation error. The drawbacks of some existing learning algorithms can therefore be revealed, especially for the case that the output data is fast changing with respect to the input or the output data is corrupted by noise. Based on this approach, the optimal learning parameters can be found by utilizing the linear matrix inequality (LMI) optimization techniques to achieve a predefined H(∞) "noise" attenuation level. Several existing BP-type algorithms are shown to be special cases of the new H(∞)-learning algorithm. Theoretical analysis and several examples are provided to show the advantages of the new method. Copyright © 2011 Elsevier Ltd. All rights reserved.

  4. Fusion of deep learning architectures, multilayer feedforward networks and learning vector quantizers for deep classification learning

    NARCIS (Netherlands)

    Villmann, T.; Biehl, M.; Villmann, A.; Saralajew, S.

    2017-01-01

    The advantage of prototype based learning vector quantizers are the intuitive and simple model adaptation as well as the easy interpretability of the prototypes as class representatives for the class distribution to be learned. Although they frequently yield competitive performance and show robust

  5. Fast-Spiking Interneurons Supply Feedforward Control of Bursting, Calcium, and Plasticity for Efficient Learning.

    Science.gov (United States)

    Owen, Scott F; Berke, Joshua D; Kreitzer, Anatol C

    2018-02-08

    Fast-spiking interneurons (FSIs) are a prominent class of forebrain GABAergic cells implicated in two seemingly independent network functions: gain control and network plasticity. Little is known, however, about how these roles interact. Here, we use a combination of cell-type-specific ablation, optogenetics, electrophysiology, imaging, and behavior to describe a unified mechanism by which striatal FSIs control burst firing, calcium influx, and synaptic plasticity in neighboring medium spiny projection neurons (MSNs). In vivo silencing of FSIs increased bursting, calcium transients, and AMPA/NMDA ratios in MSNs. In a motor sequence task, FSI silencing increased the frequency of calcium transients but reduced the specificity with which transients aligned to individual task events. Consistent with this, ablation of FSIs disrupted the acquisition of striatum-dependent egocentric learning strategies. Together, our data support a model in which feedforward inhibition from FSIs temporally restricts MSN bursting and calcium-dependent synaptic plasticity to facilitate striatum-dependent sequence learning. Copyright © 2018 Elsevier Inc. All rights reserved.

  6. Robust sequential learning of feedforward neural networks in the presence of heavy-tailed noise.

    Science.gov (United States)

    Vuković, Najdan; Miljković, Zoran

    2015-03-01

    Feedforward neural networks (FFNN) are among the most used neural networks for modeling of various nonlinear problems in engineering. In sequential and especially real time processing all neural networks models fail when faced with outliers. Outliers are found across a wide range of engineering problems. Recent research results in the field have shown that to avoid overfitting or divergence of the model, new approach is needed especially if FFNN is to run sequentially or in real time. To accommodate limitations of FFNN when training data contains a certain number of outliers, this paper presents new learning algorithm based on improvement of conventional extended Kalman filter (EKF). Extended Kalman filter robust to outliers (EKF-OR) is probabilistic generative model in which measurement noise covariance is not constant; the sequence of noise measurement covariance is modeled as stochastic process over the set of symmetric positive-definite matrices in which prior is modeled as inverse Wishart distribution. In each iteration EKF-OR simultaneously estimates noise estimates and current best estimate of FFNN parameters. Bayesian framework enables one to mathematically derive expressions, while analytical intractability of the Bayes' update step is solved by using structured variational approximation. All mathematical expressions in the paper are derived using the first principles. Extensive experimental study shows that FFNN trained with developed learning algorithm, achieves low prediction error and good generalization quality regardless of outliers' presence in training data. Copyright © 2014 Elsevier Ltd. All rights reserved.

  7. Controlling the chaotic discrete-Hénon system using a feedforward neural network with an adaptive learning rate

    OpenAIRE

    GÖKCE, Kürşad; UYAROĞLU, Yılmaz

    2013-01-01

    This paper proposes a feedforward neural network-based control scheme to control the chaotic trajectories of a discrete-Hénon map in order to stay within an acceptable distance from the stable fixed point. An adaptive learning back propagation algorithm with online training is employed to improve the effectiveness of the proposed method. The simulation study carried in the discrete-Hénon system verifies the validity of the proposed control system.

  8. Short- and Long-Term Learning of Feedforward Control of a Myoelectric Prosthesis with Sensory Feedback by Amputees.

    Science.gov (United States)

    Strbac, Matija; Isakovic, Milica; Belic, Minja; Popovic, Igor; Simanic, Igor; Farina, Dario; Keller, Thierry; Dosen, Strahinja

    2017-11-01

    Human motor control relies on a combination of feedback and feedforward strategies. The aim of this study was to longitudinally investigate artificial somatosensory feedback and feedforward control in the context of grasping with myoelectric prosthesis. Nine amputee subjects performed routine grasping trials, with the aim to produce four levels of force during four blocks of 60 trials across five days. The electrotactile force feedback was provided in the second and third block using multipad electrode and spatial coding. The first baseline and last validation block (open-loop control) evaluated the effects of long- (across sessions) and short-term (within session) learning, respectively. The outcome measures were the absolute error between the generated and target force, and the number of force saturations. The results demonstrated that the electrotactile feedback improved the performance both within and across sessions. In the validation block, the performance did not significantly decrease and the quality of open-loop control (baseline) improved across days, converging to the performance characterizing closed-loop control. This paper provides important insights into the feedback and feedforward processes in prosthesis control, contributing to the better understanding of the role and design of feedback in prosthetic systems.

  9. Video Feedforward for Rapid Learning of a Picture-Based Communication System

    Science.gov (United States)

    Smith, Jemma; Hand, Linda; Dowrick, Peter W.

    2014-01-01

    This study examined the efficacy of video self modeling (VSM) using feedforward, to teach various goals of a picture exchange communication system (PECS). The participants were two boys with autism and one man with Down syndrome. All three participants were non-verbal with no current functional system of communication; the two children had long…

  10. Metacognitive components in smart learning environment

    Science.gov (United States)

    Sumadyo, M.; Santoso, H. B.; Sensuse, D. I.

    2018-03-01

    Metacognitive ability in digital-based learning process helps students in achieving learning goals. So that digital-based learning environment should make the metacognitive component as a facility that must be equipped. Smart Learning Environment is the concept of a learning environment that certainly has more advanced components than just a digital learning environment. This study examines the metacognitive component of the smart learning environment to support the learning process. A review of the metacognitive literature was conducted to examine the components involved in metacognitive learning strategies. Review is also conducted on the results of study smart learning environment, ranging from design to context in building smart learning. Metacognitive learning strategies certainly require the support of adaptable, responsive and personalize learning environments in accordance with the principles of smart learning. The current study proposed the role of metacognitive component in smart learning environment, which is useful as the basis of research in building environment in smart learning.

  11. An iterative learning strategy for the auto-tuning of the feedforward and feedback controller in type-1 diabetes.

    Science.gov (United States)

    Fravolini, M L; Fabietti, P G

    2014-01-01

    This paper proposes a scheme for the control of the blood glucose in subjects with type-1 diabetes mellitus based on the subcutaneous (s.c.) glucose measurement and s.c. insulin administration. The tuning of the controller is based on an iterative learning strategy that exploits the repetitiveness of the daily feeding habit of a patient. The control consists of a mixed feedback and feedforward contribution whose parameters are tuned through an iterative learning process that is based on the day-by-day automated analysis of the glucose response to the infusion of exogenous insulin. The scheme does not require any a priori information on the patient insulin/glucose response, on the meal times and on the amount of ingested carbohydrates (CHOs). Thanks to the learning mechanism the scheme is able to improve its performance over time. A specific logic is also introduced for the detection and prevention of possible hypoglycaemia events. The effectiveness of the methodology has been validated using long-term simulation studies applied to a set of nine in silico patients considering realistic uncertainties on the meal times and on the quantities of ingested CHOs.

  12. Reprint of "Learning to breathe? Feedforward regulation of the inspiratory motor drive".

    Science.gov (United States)

    Zaman, Jonas; Van den Bergh, Omer; Fannes, Stien; Van Diest, Ilse

    2014-12-01

    Claims have been made that breathing is in part controlled by feedforward regulation. In a classical conditioning paradigm, we investigated anticipatory increases in the inspiratory motor drive as measured by inspiratory occlusion pressure (P100). In an acquisition phase, an experimental group (N = 13) received a low-intensity resistive load (5 cmH2O/l/s) for three consecutive inspirations as Conditioned Stimulus (CS), preceding a load of a stronger intensity (20 cmH2O/l/s) for three subsequent inspirations as unconditioned stimulus (US). The control group (N = 11) received the low-intensity load for six consecutive inspirations. In a post-acquisition phase both groups received the low-intensity load for six consecutive inspirations. Responses to the CS-load only differed between groups during the first acquisition trials and a strong increase in P100 during the US-loads was observed, which habituated across the experiment. Our results suggest that the disruption caused by adding low to moderate resistive loads to three consecutive inspirations results in a short-lasting anticipatory increase in inspiratory motor drive. Copyright © 2014 Elsevier B.V. All rights reserved.

  13. Generating Multimedia Components for M-Learning

    Directory of Open Access Journals (Sweden)

    Adriana REVEIU

    2009-01-01

    Full Text Available The paper proposes a solution to generate template based multimedia components for instruction and learning available both for computer based applications and for mobile devices. The field of research is situated at the intersection of computer science, mobile tools and e-learning and is generically named mobile learning or M-learning. The research goal is to provide access to computer based training resources from any location and to adapt the training content to the specific features of mobile devices, communication environment, users' preferences and users' knowledge. To become important tools in education field, the technical solutions proposed will follow to use the potential of mobile devices.

  14. Emotional Component in Teaching and Learning

    Science.gov (United States)

    Ponnambalam, Michael

    2018-02-01

    The laws of physics are often seen as objective truth, pure and simple. Hence, they tend to appear cerebral and cold. However, their presentation is necessarily subjective and may vary from being boring to being exciting. A detailed analysis of physics education reform efforts over the last three decades finds that interactive instruction results in greater learning gains than the traditional lecture format. In interactive engagement, the emotional component plays a far greater role than acknowledged by many. As an experienced physics teacher [(i) Four decades of teaching and research in four continents (teaching all courses to undergraduate physics majors and algebra-based physics to high school seniors as well as college freshmen), (ii) 11 years of volunteer work in Physics Popularization in six countries to many thousands of students in elementary, middle, and high schools as well as colleges and universities, and (iii) eight years as a Master Teacher and mentor], I feel that the emotional component in teaching and learning physics has been neglected. This paper presents the role of the emotional component in transforming ordinary teaching and learning of physics into an enjoyable and exciting experience for students as well as teachers.

  15. Component-Based Approach in Learning Management System Development

    Science.gov (United States)

    Zaitseva, Larisa; Bule, Jekaterina; Makarov, Sergey

    2013-01-01

    The paper describes component-based approach (CBA) for learning management system development. Learning object as components of e-learning courses and their metadata is considered. The architecture of learning management system based on CBA being developed in Riga Technical University, namely its architecture, elements and possibilities are…

  16. Feedforward motor control in developmental dyslexia and developmental coordination disorder: Does comorbidity matter?

    Science.gov (United States)

    Cignetti, Fabien; Vaugoyeau, Marianne; Fontan, Aurelie; Jover, Marianne; Livet, Marie-Odile; Hugonenq, Catherine; Audic, Frédérique; Chabrol, Brigitte; Assaiante, Christine

    2018-05-01

    Feedforward and online controls are two facets of predictive motor control from internal models, which is suspected to be impaired in learning disorders. We examined whether the feedforward component is affected in children (8-12 years) with developmental dyslexia (DD) and/or with developmental coordination disorder (DCD) compared to typically developing (TD) children. Children underwent a bimanual unloading paradigm during which a load supported to one arm, the postural arm, was either unexpectedly unloaded by a computer or voluntary unloaded by the subject with the other arm. All children showed a better stabilization (lower flexion) of the postural arm and an earlier inhibition of the arm flexors during voluntary unloading, indicating anticipation of unloading. Between-group comparisons of kinematics and electromyographic activity of the postural arm revealed that the difference during voluntary unloading was between DD-DCD children and the other groups, with the former showing a delayed inhibition of the flexor muscles. Deficit of the feedforward component of motor control may particularly apply to comorbid subtypes, here the DD-DCD subtype. The development of a comprehensive framework for motor performance deficits in children with learning disorders will be achieved only by dissociating key components of motor prediction and focusing on subtypes and comorbidities. Copyright © 2018 Elsevier Ltd. All rights reserved.

  17. Time series prediction by feedforward neural networks - is it difficult?

    International Nuclear Information System (INIS)

    Rosen-Zvi, Michal; Kanter, Ido; Kinzel, Wolfgang

    2003-01-01

    The difficulties that a neural network faces when trying to learn from a quasi-periodic time series are studied analytically using a teacher-student scenario where the random input is divided into two macroscopic regions with different variances, 1 and 1/γ 2 (γ >> 1). The generalization error is found to decrease as ε g ∝ exp(-α/γ 2 ), where α is the number of examples per input dimension. In contradiction to this very slow vanishing generalization error, the next output prediction is found to be almost free of mistakes. This picture is consistent with learning quasi-periodic time series produced by feedforward neural networks, which is dominated by enhanced components of the Fourier spectrum of the input. Simulation results are in good agreement with the analytical results

  18. Stochastic Feedforward Control Technique

    Science.gov (United States)

    Halyo, Nesim

    1990-01-01

    Class of commanded trajectories modeled as stochastic process. Advanced Transport Operating Systems (ATOPS) research and development program conducted by NASA Langley Research Center aimed at developing capabilities for increases in capacities of airports, safe and accurate flight in adverse weather conditions including shear, winds, avoidance of wake vortexes, and reduced consumption of fuel. Advances in techniques for design of modern controls and increased capabilities of digital flight computers coupled with accurate guidance information from Microwave Landing System (MLS). Stochastic feedforward control technique developed within context of ATOPS program.

  19. Document-Oriented E-Learning Components

    Science.gov (United States)

    Piotrowski, Michael

    2009-01-01

    This dissertation questions the common assumption that e-learning requires a "learning management system" (LMS) such as Moodle or Blackboard. Based on an analysis of the current state of the art in LMSs, we come to the conclusion that the functionality of conventional e-learning platforms consists of basic content management and…

  20. Assessment of learning components of management training course ...

    African Journals Online (AJOL)

    Assessment of learning components of any training course provides a benchmark through which training institutions or organizers could assess the effectiveness of the training. The study assessed learning components of agricultural research management training course organized for senior research managers in Nigeria.

  1. Unsupervised learning of facial expression components

    OpenAIRE

    Egede, Joy Onyekachukwu

    2013-01-01

    The face is one of the most important means of non-verbal communication. A lot of information can be gotten about the emotional state of a person just by merely observing their facial expression. This is relatively easy in face to face communication but not so in human computer interaction. Supervised learning has been widely used by researchers to train machines to recognise facial expressions just like humans. However, supervised learning has significant limitations one of which is the fact...

  2. Components in models of learning: Different operationalisations and relations between components

    Directory of Open Access Journals (Sweden)

    Mirkov Snežana

    2013-01-01

    Full Text Available This paper provides the presentation of different operationalisations of components in different models of learning. Special emphasis is on the empirical verifications of relations between components. Starting from the research of congruence between learning motives and strategies, underlying the general model of school learning that comprises different approaches to learning, we have analyzed the empirical verifications of factor structure of instruments containing the scales of motives and learning strategies corresponding to these motives. Considering the problems in the conceptualization of the achievement approach to learning, we have discussed the ways of operational sing the goal orientations and exploring their role in using learning strategies, especially within the model of the regulation of constructive learning processes. This model has served as the basis for researching learning styles that are the combination of a large number of components. Complex relations between the components point to the need for further investigation of the constructs involved in various models. We have discussed the findings and implications of the studies of relations between the components involved in different models, especially between learning motives/goals and learning strategies. We have analyzed the role of regulation in the learning process, whose elaboration, as indicated by empirical findings, can contribute to a more precise operationalisation of certain learning components. [Projekat Ministarstva nauke Republike Srbije, br. 47008: Unapređivanje kvaliteta i dostupnosti obrazovanja u procesima modernizacije Srbije i br. 179034: Od podsticanja inicijative, saradnje i stvaralaštva u obrazovanju do novih uloga i identiteta u društvu

  3. Feedforward mapping for engine control

    OpenAIRE

    Aran, Volkan; Ünel, Mustafa; Unel, Mustafa

    2016-01-01

    Feedforward control is widely used in electronic control units of internal combustion engines besides feedback controls. However, almost all feedforward control values are used in table form, also called maps, having engine speed and engine torque in their axes. Table approach limits all inte ractions in two input dimensions. This paper focuses on application of Gaussian process modelling of errors of inverse parametric model of the valve position. Validation results based on ...

  4. On optimal feedforward and ILC : the role of feedback for optimal performance and inferential control

    NARCIS (Netherlands)

    van Zundert, J.C.D.; Oomen, T.A.E

    2017-01-01

    The combination of feedback control with inverse model feedforward control or iterative learning control is known to yield high performance. The aim of this paper is to clarify the role of feedback in the design of feedforward controllers, with specific attention to the inferential situation. Recent

  5. Genetic component in learning ability in bees.

    Science.gov (United States)

    Kerr, W E; Moura Duarte, F A; Oliveira, R S

    1975-10-01

    Twenty-five bees, five from each of five hives, were trained to collect food at a table. When the bee reached the table, time was recorded for 12 visits. Then a blue and yellow pan was substituted for the original metal pan, and time and correct responses were recorded for 30 trips (discrimination phase). Finally, food was taken from the pan and extinction was recorded as incorrect responses for 20 visits. Variance analysis was carried out, and genetic variance was undetected for discrimination, but was detected for extinction. It is concluded that learning is very important for bees, so that any impairment in such ability affects colony survival.

  6. Jerk derivative feedforward control for motion systems

    NARCIS (Netherlands)

    Boerlage, M.L.G.; Tousain, R.L.; Steinbuch, M.

    2004-01-01

    This work discusses reference trajectory relevant model based feedforward design. For motion systems which contain at least one rigid body mode and which are subject to reference trajectories with mostly low frequency energy, the proposed feedforward controller improves tracking performance

  7. The E-Learning Component of a Blended Learning Course

    Science.gov (United States)

    Olejarczuk, Edyta

    2014-01-01

    Using new technologies in the academic field has become more and more visible in Poland in the recent years. In the past, digital learning resources were used as supplementary materials helping to support face-to-face instruction. Nowadays, we have the opportunity not only to apply "traditional" methods but also to use more sophisticated…

  8. Cognitive components underpinning the development of model-based learning.

    Science.gov (United States)

    Potter, Tracey C S; Bryce, Nessa V; Hartley, Catherine A

    2017-06-01

    Reinforcement learning theory distinguishes "model-free" learning, which fosters reflexive repetition of previously rewarded actions, from "model-based" learning, which recruits a mental model of the environment to flexibly select goal-directed actions. Whereas model-free learning is evident across development, recruitment of model-based learning appears to increase with age. However, the cognitive processes underlying the development of model-based learning remain poorly characterized. Here, we examined whether age-related differences in cognitive processes underlying the construction and flexible recruitment of mental models predict developmental increases in model-based choice. In a cohort of participants aged 9-25, we examined whether the abilities to infer sequential regularities in the environment ("statistical learning"), maintain information in an active state ("working memory") and integrate distant concepts to solve problems ("fluid reasoning") predicted age-related improvements in model-based choice. We found that age-related improvements in statistical learning performance did not mediate the relationship between age and model-based choice. Ceiling performance on our working memory assay prevented examination of its contribution to model-based learning. However, age-related improvements in fluid reasoning statistically mediated the developmental increase in the recruitment of a model-based strategy. These findings suggest that gradual development of fluid reasoning may be a critical component process underlying the emergence of model-based learning. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

  9. Learning Local Components to Understand Large Bayesian Networks

    DEFF Research Database (Denmark)

    Zeng, Yifeng; Xiang, Yanping; Cordero, Jorge

    2009-01-01

    (domain experts) to extract accurate information from a large Bayesian network due to dimensional difficulty. We define a formulation of local components and propose a clustering algorithm to learn such local components given complete data. The algorithm groups together most inter-relevant attributes......Bayesian networks are known for providing an intuitive and compact representation of probabilistic information and allowing the creation of models over a large and complex domain. Bayesian learning and reasoning are nontrivial for a large Bayesian network. In parallel, it is a tough job for users...... in a domain. We evaluate its performance on three benchmark Bayesian networks and provide results in support. We further show that the learned components may represent local knowledge more precisely in comparison to the full Bayesian networks when working with a small amount of data....

  10. Experimental evaluation of feedforward control for the trajectory tracking of power in nuclear reactors

    International Nuclear Information System (INIS)

    Lau, S.H.; Bernard, J.A.; Lanning, D.D.

    1991-01-01

    This paper reports on an experimental comparison of feedforward control techniques for the trajectory-tracking of neutronic power was performed on the 5-MWt MIT Research Reactor. Included in the comparison were pure feedforward control in which the actuator signal is found solely by processing a demanded output through a system model, hybrid feedforward/feedback control in which the actuator signal is obtained by summing feedforward and feedback components, and period-generated control in which feedback is used to update the demand trajectory prior to its being processed through the system model for calculation of the actuator signal. This latter approach was found to be the most effective. In addition to the experimental results, discussions are given of both the rationale for model-based, feedforward control and the designs of the various controllers

  11. Use and limitations of learning curves for energy technology policy: A component-learning hypothesis

    International Nuclear Information System (INIS)

    Ferioli, F.; Schoots, K.; Zwaan, B.C.C. van der

    2009-01-01

    In this paper, we investigate the use of learning curves for the description of observed cost reductions for a variety of energy technologies. Starting point of our analysis is the representation of energy processes and technologies as the sum of different components. While we recognize that in many cases 'learning-by-doing' may improve the overall costs or efficiency of a technology, we argue that so far insufficient attention has been devoted to study the effects of single component improvements that together may explain an aggregated form of learning. Indeed, for an entire technology the phenomenon of learning-by-doing may well result from learning of one or a few individual components only. We analyze under what conditions it is possible to combine learning curves for single components to derive one comprehensive learning curve for the total product. The possibility that for certain technologies some components (e.g., the primary natural resources that serve as essential input) do not exhibit cost improvements might account for the apparent time dependence of learning rates reported in several studies (the learning rate might also change considerably over time depending on the data set considered, a crucial issue to be aware of when one uses the learning curve methodology). Such an explanation may have important consequences for the extent to which learning curves can be extrapolated into the future. This argumentation suggests that cost reductions may not continue indefinitely and that well-behaved learning curves do not necessarily exist for every product or technology. In addition, even for diffusing and maturing technologies that display clear learning effects, market and resource constraints can eventually significantly reduce the scope for further improvements in their fabrication or use. It appears likely that some technologies, such as wind turbines and photovoltaic cells, are significantly more amenable than others to industry-wide learning. For such

  12. Component Pin Recognition Using Algorithms Based on Machine Learning

    Science.gov (United States)

    Xiao, Yang; Hu, Hong; Liu, Ze; Xu, Jiangchang

    2018-04-01

    The purpose of machine vision for a plug-in machine is to improve the machine’s stability and accuracy, and recognition of the component pin is an important part of the vision. This paper focuses on component pin recognition using three different techniques. The first technique involves traditional image processing using the core algorithm for binary large object (BLOB) analysis. The second technique uses the histogram of oriented gradients (HOG), to experimentally compare the effect of the support vector machine (SVM) and the adaptive boosting machine (AdaBoost) learning meta-algorithm classifiers. The third technique is the use of an in-depth learning method known as convolution neural network (CNN), which involves identifying the pin by comparing a sample to its training. The main purpose of the research presented in this paper is to increase the knowledge of learning methods used in the plug-in machine industry in order to achieve better results.

  13. Advances in independent component analysis and learning machines

    CERN Document Server

    Bingham, Ella; Laaksonen, Jorma; Lampinen, Jouko

    2015-01-01

    In honour of Professor Erkki Oja, one of the pioneers of Independent Component Analysis (ICA), this book reviews key advances in the theory and application of ICA, as well as its influence on signal processing, pattern recognition, machine learning, and data mining. Examples of topics which have developed from the advances of ICA, which are covered in the book are: A unifying probabilistic model for PCA and ICA Optimization methods for matrix decompositions Insights into the FastICA algorithmUnsupervised deep learning Machine vision and image retrieval A review of developments in the t

  14. Academic workload management towards learning, components of academic work

    OpenAIRE

    Ocvirk, Aleksandra; Trunk Širca, Nada

    2013-01-01

    This paper deals with attributing time value to academic workload from the point of view of an HEI, management of teaching and an individual. We have conducted a qualitative study aimed at analysing documents on academic workload in terms of its definition, and at analysing the attribution of time value to components of academic work in relation to the proportion of workload devoted to teaching in the sense of ensuring quality and effectiveness of learning, and in relation to financial implic...

  15. Feedforward Control of Magnetically Levitated Planar Actuators

    OpenAIRE

    Bloemers, T.; Proimadis, I.; Kasemsinsup, Y.; Tóth, R.

    2018-01-01

    The present report summarizes the work conducted during the internship on Feedforward Control of the Magnetic Levitation Setup. Different feedforward strategies, specifically tailored for this setup, are developed and reviewed. These feedforward methods explicitly take the intrinsic position-dependent behavior of the magnetic levitation setup into account. Additionally, closed-loop stability of the given setup is assessed. All investigations are carried out under the rigid-body assumption of ...

  16. Results of adaptive feedforward on GTA

    International Nuclear Information System (INIS)

    Ziomek, C.D.; Denney, P.M.; Regan, A.H.; Lynch, M.T.; Jachim, S.P.; Eaton, L.E.; Natter, E.F.

    1993-01-01

    This paper presents the results of the adaptive feedforward system in use on the Ground Test Accelerator (GTA). The adaptive feedforward system was shown to correct repetitive, high-frequency errors in the amplitude and phase of the RF field of the pulsed accelerator. The adaptive feedforward system was designed as an augmentation to the RF field feedback control system and was able to extend the closed-loop bandwidth and disturbance rejection by a factor of ten. Within a second implementation, the adaptive feedforward hardware was implemented in place of the feedback control system and was shown to negate both beam transients and phase droop in the klystron amplifier

  17. Drosophila Learn Opposing Components of a Compound Food Stimulus

    Science.gov (United States)

    Das, Gaurav; Klappenbach, Martín; Vrontou, Eleftheria; Perisse, Emmanuel; Clark, Christopher M.; Burke, Christopher J.; Waddell, Scott

    2014-01-01

    Summary Dopaminergic neurons provide value signals in mammals and insects [1–3]. During Drosophila olfactory learning, distinct subsets of dopaminergic neurons appear to assign either positive or negative value to odor representations in mushroom body neurons [4–9]. However, it is not known how flies evaluate substances that have mixed valence. Here we show that flies form short-lived aversive olfactory memories when trained with odors and sugars that are contaminated with the common insect repellent DEET. This DEET-aversive learning required the MB-MP1 dopaminergic neurons that are also required for shock learning [7]. Moreover, differential conditioning with DEET versus shock suggests that formation of these distinct aversive olfactory memories relies on a common negatively reinforcing dopaminergic mechanism. Surprisingly, as time passed after training, the behavior of DEET-sugar-trained flies reversed from conditioned odor avoidance into odor approach. In addition, flies that were compromised for reward learning exhibited a more robust and longer-lived aversive-DEET memory. These data demonstrate that flies independently process the DEET and sugar components to form parallel aversive and appetitive olfactory memories, with distinct kinetics, that compete to guide learned behavior. PMID:25042590

  18. Autonomous learning in gesture recognition by using lobe component analysis

    Science.gov (United States)

    Lu, Jian; Weng, Juyang

    2007-02-01

    Gesture recognition is a new human-machine interface method implemented by pattern recognition(PR).In order to assure robot safety when gesture is used in robot control, it is required to implement the interface reliably and accurately. Similar with other PR applications, 1) feature selection (or model establishment) and 2) training from samples, affect the performance of gesture recognition largely. For 1), a simple model with 6 feature points at shoulders, elbows, and hands, is established. The gestures to be recognized are restricted to still arm gestures, and the movement of arms is not considered. These restrictions are to reduce the misrecognition, but are not so unreasonable. For 2), a new biological network method, called lobe component analysis(LCA), is used in unsupervised learning. Lobe components, corresponding to high-concentrations in probability of the neuronal input, are orientation selective cells follow Hebbian rule and lateral inhibition. Due to the advantage of LCA method for balanced learning between global and local features, large amount of samples can be used in learning efficiently.

  19. [Membrane-bound cytokine and feedforward regulation].

    Science.gov (United States)

    Wu, Ke-Fu; Zheng, Guo-Guang; Ma, Xiao-Tong; Song, Yu-Hua

    2013-10-01

    Feedback and feedforward widely exist in life system, both of them are the basic processes of control system. While the concept of feedback has been widely used in life science, feedforward regulation was systematically studied in neurophysiology, awaiting further evidence and mechanism in molecular biology and cell biology. The authors put forward a hypothesis about the feedforward regulation of membrane bound macrophage colony stimulation factor (mM-CSF) on the basis of their previous work. This hypothesis might provide a new direction for the study on the biological effects of mM-CSF on leukemia and solid tumors, and contribute to the study on other membrane bound cytokines.

  20. Variational Bayesian Learning for Wavelet Independent Component Analysis

    Science.gov (United States)

    Roussos, E.; Roberts, S.; Daubechies, I.

    2005-11-01

    In an exploratory approach to data analysis, it is often useful to consider the observations as generated from a set of latent generators or "sources" via a generally unknown mapping. For the noisy overcomplete case, where we have more sources than observations, the problem becomes extremely ill-posed. Solutions to such inverse problems can, in many cases, be achieved by incorporating prior knowledge about the problem, captured in the form of constraints. This setting is a natural candidate for the application of the Bayesian methodology, allowing us to incorporate "soft" constraints in a natural manner. The work described in this paper is mainly driven by problems in functional magnetic resonance imaging of the brain, for the neuro-scientific goal of extracting relevant "maps" from the data. This can be stated as a `blind' source separation problem. Recent experiments in the field of neuroscience show that these maps are sparse, in some appropriate sense. The separation problem can be solved by independent component analysis (ICA), viewed as a technique for seeking sparse components, assuming appropriate distributions for the sources. We derive a hybrid wavelet-ICA model, transforming the signals into a domain where the modeling assumption of sparsity of the coefficients with respect to a dictionary is natural. We follow a graphical modeling formalism, viewing ICA as a probabilistic generative model. We use hierarchical source and mixing models and apply Bayesian inference to the problem. This allows us to perform model selection in order to infer the complexity of the representation, as well as automatic denoising. Since exact inference and learning in such a model is intractable, we follow a variational Bayesian mean-field approach in the conjugate-exponential family of distributions, for efficient unsupervised learning in multi-dimensional settings. The performance of the proposed algorithm is demonstrated on some representative experiments.

  1. Feedforward-feedback control of dissolved oxygen concentration in a predenitrification system.

    Science.gov (United States)

    Yong, Ma; Yongzhen, Peng; Shuying, Wang

    2005-07-01

    As the largest single energy-consuming component in most biological wastewater treatment systems, aeration control is of great interest from the point of view of saving energy and improving wastewater treatment plant efficiency. In this paper, three different strategies, including conventional constant dissolved oxygen (DO) set-point control, cascade DO set-point control, and feedforward-feedback DO set-point control were evaluated using the denitrification layout of the IWA simulation benchmark. Simulation studies showed that the feedforward-feedback DO set-point control strategy was better than the other control strategies at meeting the effluent standards and reducing operational costs. The control strategy works primarily by feedforward control based on an ammonium sensor located at the head of the aerobic process. It has an important advantage over effluent measurements in that there is no (or only a very short) time delay for information; feedforward control was combined with slow feedback control to compensate for model approximations. The feedforward-feedback DO control was implemented in a lab-scale wastewater treatment plant for a period of 60 days. Compared to operation with constant DO concentration, the required airflow could be reduced by up to 8-15% by employing the feedforward-feedback DO-control strategy, and the effluent ammonia concentration could be reduced by up to 15-25%. This control strategy can be expected to be accepted by the operating personnel in wastewater treatment plants.

  2. Processing oscillatory signals by incoherent feedforward loops

    Science.gov (United States)

    Zhang, Carolyn; Wu, Feilun; Tsoi, Ryan; Shats, Igor; You, Lingchong

    From the timing of amoeba development to the maintenance of stem cell pluripotency,many biological signaling pathways exhibit the ability to differentiate between pulsatile and sustained signals in the regulation of downstream gene expression.While networks underlying this signal decoding are diverse,many are built around a common motif, the incoherent feedforward loop (IFFL),where an input simultaneously activates an output and an inhibitor of the output.With appropriate parameters,this motif can generate temporal adaptation,where the system is desensitized to a sustained input.This property serves as the foundation for distinguishing signals with varying temporal profiles.Here,we use quantitative modeling to examine another property of IFFLs,the ability to process oscillatory signals.Our results indicate that the system's ability to translate pulsatile dynamics is limited by two constraints.The kinetics of IFFL components dictate the input range for which the network can decode pulsatile dynamics.In addition,a match between the network parameters and signal characteristics is required for optimal ``counting''.We elucidate one potential mechanism by which information processing occurs in natural networks with implications in the design of synthetic gene circuits for this purpose. This work was partially supported by the National Science Foundation Graduate Research Fellowship (CZ).

  3. Recognition of Prior Learning as an integral component of ...

    African Journals Online (AJOL)

    This is irrespective of whether that learning has been acquired through unstructured learning, performance development, off-the-job assessment, or skills and knowledge that meet workplace needs but have been gained through various previous learning experiences. The concept Recognition of Prior Learning (RPL) is ...

  4. Development of E-learning Software Based Multiplatform Components

    OpenAIRE

    Salamah, Irma; Ganiardi, M. Aris

    2017-01-01

    E-learning software is a product of information and communication technology used to help dynamic and flexible learning process between teacher and student. The software technology was first used in the development of e-learning software in the form of web applications. The advantages of this technology because of the ease in the development, installation, and distribution of data. Along with advances in mobile/wireless electronics technology, e-learning software is adapted to this technology...

  5. Components of Self-Regulated Learning; Implications for School Performance

    Science.gov (United States)

    Mih, Codruta; Mih, Viorel

    2010-01-01

    Self-regulated school learning behavior includes the activation of a relatively large number of psychological dimensions. Among the most important self-regulation constructs that influence school learning are: learning goals, personal self-efficacy, metacognition and test-anxiety. The adaptive functioning of these is associated with high…

  6. Learning Algorithms for Audio and Video Processing: Independent Component Analysis and Support Vector Machine Based Approaches

    National Research Council Canada - National Science Library

    Qi, Yuan

    2000-01-01

    In this thesis, we propose two new machine learning schemes, a subband-based Independent Component Analysis scheme and a hybrid Independent Component Analysis/Support Vector Machine scheme, and apply...

  7. Support surface related changes in feedforward and feedback control of standing posture.

    Science.gov (United States)

    Mohapatra, Sambit; Kukkar, Komal K; Aruin, Alexander S

    2014-02-01

    The aim of the study was to investigate the effect of different support surfaces on feedforward and feedback components of postural control. Nine healthy subjects were exposed to external perturbations applied to their shoulders while standing on a rigid platform, foam, and wobble board with eyes open or closed. Electrical activity of nine trunk and leg muscles and displacements of the center of pressure were recorded and analyzed during the time frames typical of feedforward and feedback postural adjustments. Feedforward control of posture was characterized by earlier activation of anterior muscles when the subjects stood on foam compared to a wobble board or a firm surface. In addition, the magnitude of feedforward muscle activity was the largest when the foam was used. During the feedback control, anterior muscles were activated prior to posterior muscles irrespective of the nature of surface. Moreover, the largest muscle activity was seen when the supporting surface was foam. Maximum CoP displacement occurred when subjects were standing on a rigid surface. Altering support surface affects both feedforward and feedback components of postural control. This information should be taken into consideration in planning rehabilitation interventions geared towards improvement of balance. Copyright © 2013 Elsevier Ltd. All rights reserved.

  8. Precision requirements for single-layer feed-forward neural networks

    NARCIS (Netherlands)

    Annema, Anne J.; Hoen, K.; Hoen, Klaas; Wallinga, Hans

    1994-01-01

    This paper presents a mathematical analysis of the effect of limited precision analog hardware for weight adaptation to be used in on-chip learning feedforward neural networks. Easy-to-read equations and simple worst-case estimations for the maximum tolerable imprecision are presented. As an

  9. On-line Learning of Prototypes and Principal Components

    NARCIS (Netherlands)

    Biehl, M.; Freking, A.; Hölzer, M.; Reents, G.; Schlösser, E.; Saad, David

    1998-01-01

    We review our recent investigation of on-line unsupervised learning from high-dimensional structured data. First, on-line competitive learning is studied as a method for the identification of prototype vectors from overlapping clusters of examples. Specifically, we analyse the dynamics of the

  10. Recognition of Prior Learning as an integral component of ...

    African Journals Online (AJOL)

    Erna Kinsey

    In these theories, learning is seen as a lifelong developmental process which is ... According to Gawe (1999:23) many institutions of higher learning all over the ... the vocational sector as well as the education and training sector with different ...

  11. Stochastic resonance in feedforward acupuncture networks

    Science.gov (United States)

    Qin, Ying-Mei; Wang, Jiang; Men, Cong; Deng, Bin; Wei, Xi-Le; Yu, Hai-Tao; Chan, Wai-Lok

    2014-10-01

    Effects of noises and some other network properties on the weak signal propagation are studied systematically in feedforward acupuncture networks (FFN) based on FitzHugh-Nagumo neuron model. It is found that noises with medium intensity can enhance signal propagation and this effect can be further increased by the feedforward network structure. Resonant properties in the noisy network can also be altered by several network parameters, such as heterogeneity, synapse features, and feedback connections. These results may also provide a novel potential explanation for the propagation of acupuncture signal.

  12. Vocabulary Learning in Primary School Children: Working Memory and Long-Term Memory Components

    Science.gov (United States)

    Morra, Sergio; Camba, Roberta

    2009-01-01

    The goal of this study was to investigate which working memory and long-term memory components predict vocabulary learning. We used a nonword learning paradigm in which 8- to 10-year-olds learned picture-nonword pairs. The nonwords varied in length (two vs. four syllables) and phonology (native sounding vs. including one Russian phoneme). Short,…

  13. Pupil size directly modulates the feedforward response in human primary visual cortex independently of attention.

    Science.gov (United States)

    Bombeke, Klaas; Duthoo, Wout; Mueller, Sven C; Hopf, Jens-Max; Boehler, C Nico

    2016-02-15

    Controversy revolves around the question of whether psychological factors like attention and emotion can influence the initial feedforward response in primary visual cortex (V1). Although traditionally, the electrophysiological correlate of this response in humans (the C1 component) has been found to be unaltered by psychological influences, a number of recent studies have described attentional and emotional modulations. Yet, research into psychological effects on the feedforward V1 response has neglected possible direct contributions of concomitant pupil-size modulations, which are known to also occur under various conditions of attentional load and emotional state. Here we tested the hypothesis that such pupil-size differences themselves directly affect the feedforward V1 response. We report data from two complementary experiments, in which we used procedures that modulate pupil size without differences in attentional load or emotion while simultaneously recording pupil-size and EEG data. Our results confirm that pupil size indeed directly influences the feedforward V1 response, showing an inverse relationship between pupil size and early V1 activity. While it is unclear in how far this effect represents a functionally-relevant adaptation, it identifies pupil-size differences as an important modulating factor of the feedforward response of V1 and could hence represent a confounding variable in research investigating the neural influence of psychological factors on early visual processing. Copyright © 2015 Elsevier Inc. All rights reserved.

  14. Feedforward temperature control using a heat flux microsensor

    OpenAIRE

    Lartz, Douglas John

    1993-01-01

    The concept of using heat flux measurements to provide the input for a feedforward temperature control loop is investigated. The feedforward loop is added to proportional and integral feedback control to increase the speed of the response to a disturbance. Comparison is made between the feedback and the feedback plus feedforward control laws. The control law with the feedforward control loop is also compared to the conventional approach of adding derivative control to speed up ...

  15. Feedforward inhibition and synaptic scaling--two sides of the same coin?

    Directory of Open Access Journals (Sweden)

    Christian Keck

    Full Text Available Feedforward inhibition and synaptic scaling are important adaptive processes that control the total input a neuron can receive from its afferents. While often studied in isolation, the two have been reported to co-occur in various brain regions. The functional implications of their interactions remain unclear, however. Based on a probabilistic modeling approach, we show here that fast feedforward inhibition and synaptic scaling interact synergistically during unsupervised learning. In technical terms, we model the input to a neural circuit using a normalized mixture model with Poisson noise. We demonstrate analytically and numerically that, in the presence of lateral inhibition introducing competition between different neurons, Hebbian plasticity and synaptic scaling approximate the optimal maximum likelihood solutions for this model. Our results suggest that, beyond its conventional use as a mechanism to remove undesired pattern variations, input normalization can make typical neural interaction and learning rules optimal on the stimulus subspace defined through feedforward inhibition. Furthermore, learning within this subspace is more efficient in practice, as it helps avoid locally optimal solutions. Our results suggest a close connection between feedforward inhibition and synaptic scaling which may have important functional implications for general cortical processing.

  16. Feedforward inhibition and synaptic scaling--two sides of the same coin?

    Science.gov (United States)

    Keck, Christian; Savin, Cristina; Lücke, Jörg

    2012-01-01

    Feedforward inhibition and synaptic scaling are important adaptive processes that control the total input a neuron can receive from its afferents. While often studied in isolation, the two have been reported to co-occur in various brain regions. The functional implications of their interactions remain unclear, however. Based on a probabilistic modeling approach, we show here that fast feedforward inhibition and synaptic scaling interact synergistically during unsupervised learning. In technical terms, we model the input to a neural circuit using a normalized mixture model with Poisson noise. We demonstrate analytically and numerically that, in the presence of lateral inhibition introducing competition between different neurons, Hebbian plasticity and synaptic scaling approximate the optimal maximum likelihood solutions for this model. Our results suggest that, beyond its conventional use as a mechanism to remove undesired pattern variations, input normalization can make typical neural interaction and learning rules optimal on the stimulus subspace defined through feedforward inhibition. Furthermore, learning within this subspace is more efficient in practice, as it helps avoid locally optimal solutions. Our results suggest a close connection between feedforward inhibition and synaptic scaling which may have important functional implications for general cortical processing.

  17. Feedforward Inhibition and Synaptic Scaling – Two Sides of the Same Coin?

    Science.gov (United States)

    Lücke, Jörg

    2012-01-01

    Feedforward inhibition and synaptic scaling are important adaptive processes that control the total input a neuron can receive from its afferents. While often studied in isolation, the two have been reported to co-occur in various brain regions. The functional implications of their interactions remain unclear, however. Based on a probabilistic modeling approach, we show here that fast feedforward inhibition and synaptic scaling interact synergistically during unsupervised learning. In technical terms, we model the input to a neural circuit using a normalized mixture model with Poisson noise. We demonstrate analytically and numerically that, in the presence of lateral inhibition introducing competition between different neurons, Hebbian plasticity and synaptic scaling approximate the optimal maximum likelihood solutions for this model. Our results suggest that, beyond its conventional use as a mechanism to remove undesired pattern variations, input normalization can make typical neural interaction and learning rules optimal on the stimulus subspace defined through feedforward inhibition. Furthermore, learning within this subspace is more efficient in practice, as it helps avoid locally optimal solutions. Our results suggest a close connection between feedforward inhibition and synaptic scaling which may have important functional implications for general cortical processing. PMID:22457610

  18. Implementation of Learning Organization Components in Ardabil Social Security Hospital

    Directory of Open Access Journals (Sweden)

    Azadeh Zirak

    2015-06-01

    Full Text Available This study aimed to investigate the implementation of learning organization characteristics based on Marquardt systematic model in Ardabil Social Security Hospital. The statistical population of this research was 234 male and female employees of Ardabil Social Security Hospital. For data collection, Marquardt questionnaire was used in the present study which its validity and reliability had been confirmed. Statistical analysis of hypotheses based on independent samples t-test showed that learning organization characteristics were used more than average level in some subsystems of Marquardt model and there was a significant difference between current position and excellent position based on learning organization characteristic application. According to the research findings, more attention should be paid to the subsystems of learning organization establishment and balanced development of these subsystems.

  19. Training Feedforward Neural Networks Using Symbiotic Organisms Search Algorithm

    Directory of Open Access Journals (Sweden)

    Haizhou Wu

    2016-01-01

    Full Text Available Symbiotic organisms search (SOS is a new robust and powerful metaheuristic algorithm, which stimulates the symbiotic interaction strategies adopted by organisms to survive and propagate in the ecosystem. In the supervised learning area, it is a challenging task to present a satisfactory and efficient training algorithm for feedforward neural networks (FNNs. In this paper, SOS is employed as a new method for training FNNs. To investigate the performance of the aforementioned method, eight different datasets selected from the UCI machine learning repository are employed for experiment and the results are compared among seven metaheuristic algorithms. The results show that SOS performs better than other algorithms for training FNNs in terms of converging speed. It is also proven that an FNN trained by the method of SOS has better accuracy than most algorithms compared.

  20. Dialogic feedforward in group coaching

    DEFF Research Database (Denmark)

    Alrø, Helle; Dahl, Poul Nørgård

    2015-01-01

    The overall purpose of the article is to describe a joint learning process where both practicable and theoretically anchored knowledge are in the foreground. The empirical data derives from an EU project. In focus is a group of course leaders and their experiences of carrying out a training...... programme targeted for a group of individuals with a weak position on the labour market. The author brings out what happens when individuals try to understand perspectives from one another. The results demonstrate the knowledge that is developed when members of a project team are included in the entire...... research process, from the definition of problems to the analysis, presentation of results and suggestions of change. Further the outcome illustrates how an interactive research approach can be conducted in close co-operation with those concerned. Active participation, a structured learning process...

  1. Implementation and Qualifications Lessons Learned for Space Flight Photonic Components

    Science.gov (United States)

    Ott, Melanie N.

    2010-01-01

    This slide presentation reviews the process for implementation and qualification of space flight photonic components. It discusses the causes for most common anomalies for the space flight components, design compatibility, a specific failure analysis of optical fiber that occurred in a cable in 1999-2000, and another ExPCA connector anomaly involving pins that broke off. It reviews issues around material selection, quality processes and documentation, and current projects that the Photonics group is involved in. The importance of good documentation is stressed.

  2. Neural networks for feedback feedforward nonlinear control systems.

    Science.gov (United States)

    Parisini, T; Zoppoli, R

    1994-01-01

    This paper deals with the problem of designing feedback feedforward control strategies to drive the state of a dynamic system (in general, nonlinear) so as to track any desired trajectory joining the points of given compact sets, while minimizing a certain cost function (in general, nonquadratic). Due to the generality of the problem, conventional methods are difficult to apply. Thus, an approximate solution is sought by constraining control strategies to take on the structure of multilayer feedforward neural networks. After discussing the approximation properties of neural control strategies, a particular neural architecture is presented, which is based on what has been called the "linear-structure preserving principle". The original functional problem is then reduced to a nonlinear programming one, and backpropagation is applied to derive the optimal values of the synaptic weights. Recursive equations to compute the gradient components are presented, which generalize the classical adjoint system equations of N-stage optimal control theory. Simulation results related to nonlinear nonquadratic problems show the effectiveness of the proposed method.

  3. Implementation of Learning Organization Components in Ardabil Social Security Hospital

    OpenAIRE

    Azadeh Zirak

    2015-01-01

    This study aimed to investigate the implementation of learning organization characteristics based on Marquardt systematic model in Ardabil Social Security Hospital. The statistical population of this research was 234 male and female employees of Ardabil Social Security Hospital. For data collection, Marquardt questionnaire was used in the present study which its validity and reliability had been confirmed. Statistical analysis of hypotheses based on independent samples t-test showed that lear...

  4. Differences in feedforward trunk muscle activity in subgroups of patients with mechanical low back pain.

    Science.gov (United States)

    Silfies, Sheri P; Mehta, Rupal; Smith, Sue S; Karduna, Andrew R

    2009-07-01

    To investigate alterations in trunk muscle timing patterns in subgroups of patients with mechanical low back pain (MLBP). Our hypothesis was that subjects with MLBP would demonstrate delayed muscle onset and have fewer muscles functioning in a feedforward manner than the control group. We further hypothesized that we would find differences between subgroups of our patients with MLBP, grouped according to diagnosis (segmental instability and noninstability). Case-control. Laboratory. Forty-three patients with chronic MLBP (25 instability, 18 noninstability) and 39 asymptomatic controls. Not applicable. Surface electromyography was used to measure onset time of 10 trunk muscles during a self-perturbation task. Trunk muscle onset latency relative to the anterior deltoid was calculated and the number of muscles functioning in feedforward determined. Activation timing patterns (Pfeedforward (P=.02; eta=.30; 1-beta=.83) were statistically different between patients with MLBP and controls. The control group activated the external oblique, lumbar multifidus, and erector spinae muscles in a feedforward manner. The heterogeneous MLBP group did not activate the trunk musculature in feedforward, but responded with significantly delayed activations. MLBP subgroups demonstrated significantly different timing patterns. The noninstability MLBP subgroup activated trunk extensors in a feedforward manner, similar to the control group, but significantly earlier than the instability subgroup. Lack of feedforward activation of selected trunk musculature in patients with MLBP may result in a period of inefficient muscular stabilization. Activation timing was more impaired in the instability than the noninstability MLBP subgroup. Training specifically for recruitment timing may be an important component of the rehabilitation program.

  5. Component Architectures and Web-Based Learning Environments

    Science.gov (United States)

    Ferdig, Richard E.; Mishra, Punya; Zhao, Yong

    2004-01-01

    The Web has caught the attention of many educators as an efficient communication medium and content delivery system. But we feel there is another aspect of the Web that has not been given the attention it deserves. We call this aspect of the Web its "component architecture." Briefly it means that on the Web one can develop very complex…

  6. Do quality improvement collaboratives' educational components match the dominant learning style preferences of the participants?

    Science.gov (United States)

    Weggelaar-Jansen, Anne Marie; van Wijngaarden, Jeroen; Slaghuis, Sarah-Sue

    2015-06-20

    Quality improvement collaboratives are used to improve healthcare by various organizations. Despite their popularity literature shows mixed results on their effectiveness. A quality improvement collaborative can be seen as a temporary learning organization in which knowledge about improvement themes and methods is exchanged. In this research we studied: Does the learning approach of a quality improvement collaborative match the learning styles preferences of the individual participants and how does that affect the learning process of participants? This research used a mixed methods design combining a validated learning style questionnaire with data collected in the tradition of action research methodology to study two Dutch quality improvement collaboratives. The questionnaire is based on the learning style model of Ruijters and Simons, distinguishing five learning style preferences: Acquisition of knowledge, Apperception from others, Discovery of new insights, Exercising in fictitious situations and Participation with others. The most preferred learning styles of the participants were Discovery and Participation. The learning style Acquisition was moderately preferred and Apperception and Exercising were least preferred. The educational components of the quality improvement collaboratives studied (national conferences, half-day learning sessions, faculty site visits and use of an online tool) were predominantly associated with the learning styles Acquisition and Apperception. We observed a decrease in attendance to the learning activities and non-conformance with the standardized set goals and approaches. We conclude that the participants' satisfaction with the offered learning approach changed over time. The lacking match between these learning style preferences and the learning approach in the educational components of the quality improvement collaboratives studied might be the reason why the participants felt they did not gain new insights and therefore ceased

  7. Design Of Feedforward Controllers For Multivariable Plants

    Science.gov (United States)

    Seraji, Homayoun

    1989-01-01

    Controllers based on simple low-order transfer functions. Mathematical criteria derived for design of feedforward controllers for class of multiple-input/multiple-output linear plants. Represented by simple low-order transfer functions, obtained without reconstruction of states of commands and disturbances. Enables plant to track command while remaining unresponsive to disturbance in steady state. Feedback controller added independently to stabilize plant or to make control system less susceptible to variations in parameters of plant.

  8. Output Control Using Feedforward And Cascade Controllers

    Science.gov (United States)

    Seraji, Homayoun

    1990-01-01

    Report presents theoretical study of open-loop control elements in single-input, single-output linear system. Focus on output-control (servomechanism) problem, in which objective is to find control scheme that causes output to track certain command inputs and to reject certain disturbance inputs in steady state. Report closes with brief discussion of characteristics and relative merits of feedforward, cascade, and feedback controllers and combinations thereof.

  9. Nonlinear programming with feedforward neural networks.

    Energy Technology Data Exchange (ETDEWEB)

    Reifman, J.

    1999-06-02

    We provide a practical and effective method for solving constrained optimization problems by successively training a multilayer feedforward neural network in a coupled neural-network/objective-function representation. Nonlinear programming problems are easily mapped into this representation which has a simpler and more transparent method of solution than optimization performed with Hopfield-like networks and poses very mild requirements on the functions appearing in the problem. Simulation results are illustrated and compared with an off-the-shelf optimization tool.

  10. Vocabulary learning in primary school children: working memory and long-term memory components.

    Science.gov (United States)

    Morra, Sergio; Camba, Roberta

    2009-10-01

    The goal of this study was to investigate which working memory and long-term memory components predict vocabulary learning. We used a nonword learning paradigm in which 8- to 10-year-olds learned picture-nonword pairs. The nonwords varied in length (two vs. four syllables) and phonology (native sounding vs. including one Russian phoneme). Short, phonologically native nonwords were learned best, whereas learning long nonwords leveled off after a few presentation cycles. Linear structural equation analyses showed an influence of three constructs-phonological sensitivity, vocabulary knowledge, and central attentional resources (M capacity)-on nonword learning, but the extent of their contributions depended on specific characteristics of the nonwords to be learned. Phonological sensitivity predicted learning of all nonword types except short native nonwords, vocabulary predicted learning of only short native nonwords, and M capacity predicted learning of short nonwords but not long nonwords. The discussion considers three learning processes-effortful activation of phonological representations, lexical mediation, and passive associative learning-that use different cognitive resources and could be involved in learning different nonword types.

  11. Children's acceptance learning of New Nordic components and potential challenges

    DEFF Research Database (Denmark)

    Hartvig, Ditte Luise

    that repeated exposure as well as food engagement constitute efficient methods to enhance the acceptance of Nordic foods. Furthermore the importance of follow-up tests and initial liking was highlighted. Many different factors affect acceptance and acceptance learning of food products, some of those may even......It has been suggested that dietary recommendations should be tailored to regional conditions to bridge gastronomi, health and sustainability. The New Nordic diet (NND) has been defined as part of the OPUS project:”Optimal well-being, development and health of school children through a New Nordic......’s food preferences. In the first part of the project it was investigated how a five week intervention with Nordic foods and food engagement affected the acceptance of sea-buckthorn berry products, not included in the intervention. The effect of the intervention was compared to the effect of eight product...

  12. Beliefs on Learning and Teaching Language Components: The Case of Iranian EAP and EFL Learners

    Science.gov (United States)

    Parsi, Gholamreza

    2017-01-01

    The present study intended to investigate the possible difference between EAP and EFL learners' beliefs concerning learning and teaching of language components, namely, vocabulary, pronunciation and grammar. Furthermore, this study examined the association between EAP and EFL learners' beliefs and their language components' development. To this…

  13. Conjugate descent formulation of backpropagation error in feedforward neural networks

    Directory of Open Access Journals (Sweden)

    NK Sharma

    2009-06-01

    Full Text Available The feedforward neural network architecture uses backpropagation learning to determine optimal weights between different interconnected layers. This learning procedure uses a gradient descent technique applied to a sum-of-squares error function for the given input-output pattern. It employs an iterative procedure to minimise the error function for a given set of patterns, by adjusting the weights of the network. The first derivates of the error with respect to the weights identify the local error surface in the descent direction. Hence the network exhibits a different local error surface for every different pattern presented to it, and weights are iteratively modified in order to minimise the current local error. The determination of an optimal weight vector is possible only when the total minimum error (mean of the minimum local errors for all patterns from the training set may be minimised. In this paper, we present a general mathematical formulation for the second derivative of the error function with respect to the weights (which represents a conjugate descent for arbitrary feedforward neural network topologies, and we use this derivative information to obtain the optimal weight vector. The local error is backpropagated among the units of hidden layers via the second order derivative of the error with respect to the weights of the hidden and output layers independently and also in combination. The new total minimum error point may be evaluated with the help of the current total minimum error and the current minimised local error. The weight modification processes is performed twice: once with respect to the present local error and once more with respect to the current total or mean error. We present some numerical evidence that our proposed method yields better network weights than those determined via a conventional gradient descent approach.

  14. Feed-Forward versus Feedback Inhibition in a Basic Olfactory Circuit.

    Directory of Open Access Journals (Sweden)

    Tiffany Kee

    2015-10-01

    Full Text Available Inhibitory interneurons play critical roles in shaping the firing patterns of principal neurons in many brain systems. Despite difference in the anatomy or functions of neuronal circuits containing inhibition, two basic motifs repeatedly emerge: feed-forward and feedback. In the locust, it was proposed that a subset of lateral horn interneurons (LHNs, provide feed-forward inhibition onto Kenyon cells (KCs to maintain their sparse firing--a property critical for olfactory learning and memory. But recently it was established that a single inhibitory cell, the giant GABAergic neuron (GGN, is the main and perhaps sole source of inhibition in the mushroom body, and that inhibition from this cell is mediated by a feedback (FB loop including KCs and the GGN. To clarify basic differences in the effects of feedback vs. feed-forward inhibition in circuit dynamics we here use a model of the locust olfactory system. We found both inhibitory motifs were able to maintain sparse KCs responses and provide optimal odor discrimination. However, we further found that only FB inhibition could create a phase response consistent with data recorded in vivo. These findings describe general rules for feed-forward versus feedback inhibition and suggest GGN is potentially capable of providing the primary source of inhibition to the KCs. A better understanding of how inhibitory motifs impact post-synaptic neuronal activity could be used to reveal unknown inhibitory structures within biological networks.

  15. Feed-Forward Corrections for Tune and Chromaticity Injection Decay During 2015 LHC Operation

    CERN Document Server

    Solfaroli Camillocci, Matteo; Lamont, Mike; Schaumann, Michaela; Todesco, Ezio; Wenninger, Jorg

    2016-01-01

    After two years of shutdown, the Large Hadron Collider (LHC) has been operated in 2015 at 6.5 TeV, close to its designed energy. When the current is stable at low field, the harmonic components of the main circuits are subject to a dynamic variation induced by current redistribution on the superconducting cables. The Field Description of the LHC (FiDel) foresaw an increase of the decay at injection of tune (quadrupolar components) and chromaticity (sextupolar components) of about 50% with respect to LHC Run1 due to the higher operational current. This paper discusses the beam-based measurements of the decay during the injection plateau and the implementation and accuracy of the feed-forward corrections as present in 2015. Moreover, the observed tune shift proportional to the circulating beam intensity and it's foreseen feed-forward correction are covered.

  16. Lessons learned from fatique failures in major FWR components

    International Nuclear Information System (INIS)

    Ware, A.G.; Shah, V.N.

    1992-01-01

    This paper evaluates the field fatigue failure experience and describes the lessons learned that can be employed in managing fatigue damage at the sites of these failures and at other susceptible sites. Fatigue damage has resulted in cracks on the inside surfaces of vessels and piping, and in some cases, through-wall cracks resulting in coolant leakage. All of the fatigue failures resulted from conditions or stressors that were not accounted for in the original design analyses. In some cases, it has proven difficult to discover fatigue cracks using conventional inservice inspection methods; several cracks were detected because of leakage. Supplementary monitoring and inspection techniques such as fatigue monitoring, acoustic emission monitoring, and time-of-flight-diffraction ultrasonic testing can be used to assist in identifying susceptible sites, estimating crack growth, and sizing existing fatigue cracks. It is important to identify the root cause of failures because once the stressors and degradation mechanisms are known, changes in operating procedures and designs can be implemented to mitigate future fatigue damage

  17. Combined feedforward and feedback control of end milling system

    OpenAIRE

    Čuš, Franc; Župerl, Uroš; Balič, Jože

    2012-01-01

    Purpose: Purpose of this paper. An intelligent control system is presented that uses a combination of feedforward and feedback for cutting force control in end milling.Design/methodology/approach: The network is trained by the feedback output that is minimized during training and most control action for disturbance rejection is finally performed by the rapid feedforward action of the network.Findings: The feedback controller corrects for errors caused by external disturbances. The feedforward...

  18. Low-order feedforward controllers: Optimal performance and practical considerations

    OpenAIRE

    Hast, Martin; Hägglund, Tore

    2014-01-01

    Feedforward control from measurable disturbances can significantly improve the performance in control loops. However, tuning rules for such controllers are scarce. In this paper design rules for how to choose optimal low-order feedforward controller parameter are presented. The parameters are chosen so that the integrated squared error, when the system is subject to a step disturbance, is minimized. The approach utilizes a controller structure that decouples the feedforward and the feedback c...

  19. High-speed linear optics quantum computing using active feed-forward.

    Science.gov (United States)

    Prevedel, Robert; Walther, Philip; Tiefenbacher, Felix; Böhi, Pascal; Kaltenbaek, Rainer; Jennewein, Thomas; Zeilinger, Anton

    2007-01-04

    As information carriers in quantum computing, photonic qubits have the advantage of undergoing negligible decoherence. However, the absence of any significant photon-photon interaction is problematic for the realization of non-trivial two-qubit gates. One solution is to introduce an effective nonlinearity by measurements resulting in probabilistic gate operations. In one-way quantum computation, the random quantum measurement error can be overcome by applying a feed-forward technique, such that the future measurement basis depends on earlier measurement results. This technique is crucial for achieving deterministic quantum computation once a cluster state (the highly entangled multiparticle state on which one-way quantum computation is based) is prepared. Here we realize a concatenated scheme of measurement and active feed-forward in a one-way quantum computing experiment. We demonstrate that, for a perfect cluster state and no photon loss, our quantum computation scheme would operate with good fidelity and that our feed-forward components function with very high speed and low error for detected photons. With present technology, the individual computational step (in our case the individual feed-forward cycle) can be operated in less than 150 ns using electro-optical modulators. This is an important result for the future development of one-way quantum computers, whose large-scale implementation will depend on advances in the production and detection of the required highly entangled cluster states.

  20. Comparison between hybrid feedforward-feedback, feedforward, and feedback structures for active noise control of fMRI noise.

    Science.gov (United States)

    Reddy, Rajiv M; Panahi, Issa M S

    2008-01-01

    The performance of FIR feedforward, IIR feedforward, FIR feedback, hybrid FIR feedforward--FIR feedback, and hybrid IIR feedforward - FIR feedback structures for active noise control (ANC) are compared for an fMRI noise application. The filtered-input normalized least squares (FxNLMS) algorithm is used to update the coefficients of the adaptive filters in all these structures. Realistic primary and secondary paths of an fMRI bore are used by estimating them on a half cylindrical acrylic bore of 0.76 m (D)x1.52 m (L). Detailed results of the performance of the ANC system are presented in the paper for each of these structures. We find that the IIR feedforward structure produces most of the performance improvement in the hybrid IIR feedforward - FIR feedback structure and adding the feedback structure becomes almost redundant in the case of fMRI noise.

  1. Shared internal models for feedforward and feedback control.

    Science.gov (United States)

    Wagner, Mark J; Smith, Maurice A

    2008-10-15

    A child often learns to ride a bicycle in the driveway, free of unforeseen obstacles. Yet when she first rides in the street, we hope that if a car suddenly pulls out in front of her, she will combine her innate goal of avoiding an accident with her learned knowledge of the bicycle, and steer away or brake. In general, when we train to perform a new motor task, our learning is most robust if it updates the rules of online error correction to reflect the rules and goals of the new task. Here we provide direct evidence that, after a new feedforward motor adaptation, motor feedback responses to unanticipated errors become precisely task appropriate, even when such errors were never experienced during training. To study this ability, we asked how, if at all, do online responses to occasional, unanticipated force pulses during reaching arm movements change after adapting to altered arm dynamics? Specifically, do they change in a task-appropriate manner? In our task, subjects learned novel velocity-dependent dynamics. However, occasional force-pulse perturbations produced unanticipated changes in velocity. Therefore, after adaptation, task-appropriate responses to unanticipated pulses should compensate corresponding changes in velocity-dependent dynamics. We found that after adaptation, pulse responses precisely compensated these changes, although they were never trained to do so. These results provide evidence for a smart feedback controller which automatically produces responses specific to the learned dynamics of the current task. To accomplish this, the neural processes underlying feedback control must (1) be capable of accurate real-time state prediction for velocity via a forward model and (2) have access to recently learned changes in internal models of limb dynamics.

  2. The Assurance of Learning Process Components and the Effects of Engaging Students in the Learning

    Science.gov (United States)

    Mosca, Joseph B.; Agacer, Gilder; Flaming, Linda; Buzza, John

    2011-01-01

    Assurance of learning process plays a major role in higher education and has increased the accountability on the part of instructors at all levels. This paper will discuss the role of assurance processes in teaching and the ways to measure these processes of student learning. The research focus will be to determine if student engagement in problem…

  3. Reflections on Designing a MPA Service-Learning Component: Lessons Learned

    Science.gov (United States)

    Roman, Alexandru V.

    2015-01-01

    This article provides the "lessons learned" from the experience of redesigning two sections (face-to-face and online) of a core master of public administration class as a service-learning course. The suggestions made here can be traced to the entire process of the project, from the "seed idea" through its conceptualization and…

  4. Multiple brain networks underpinning word learning from fluent speech revealed by independent component analysis.

    Science.gov (United States)

    López-Barroso, Diana; Ripollés, Pablo; Marco-Pallarés, Josep; Mohammadi, Bahram; Münte, Thomas F; Bachoud-Lévi, Anne-Catherine; Rodriguez-Fornells, Antoni; de Diego-Balaguer, Ruth

    2015-04-15

    Although neuroimaging studies using standard subtraction-based analysis from functional magnetic resonance imaging (fMRI) have suggested that frontal and temporal regions are involved in word learning from fluent speech, the possible contribution of different brain networks during this type of learning is still largely unknown. Indeed, univariate fMRI analyses cannot identify the full extent of distributed networks that are engaged by a complex task such as word learning. Here we used Independent Component Analysis (ICA) to characterize the different brain networks subserving word learning from an artificial language speech stream. Results were replicated in a second cohort of participants with a different linguistic background. Four spatially independent networks were associated with the task in both cohorts: (i) a dorsal Auditory-Premotor network; (ii) a dorsal Sensory-Motor network; (iii) a dorsal Fronto-Parietal network; and (iv) a ventral Fronto-Temporal network. The level of engagement of these networks varied through the learning period with only the dorsal Auditory-Premotor network being engaged across all blocks. In addition, the connectivity strength of this network in the second block of the learning phase correlated with the individual variability in word learning performance. These findings suggest that: (i) word learning relies on segregated connectivity patterns involving dorsal and ventral networks; and (ii) specifically, the dorsal auditory-premotor network connectivity strength is directly correlated with word learning performance. Copyright © 2015 Elsevier Inc. All rights reserved.

  5. Feed-Forward Control in Resonant DC Link Inverter

    OpenAIRE

    Apinan Aurasopon; Worawat Sa-ngiavibool

    2008-01-01

    This paper proposes a feed-forward control in resonant dc link inverter. The feed-forward control configuration is based on synchronous sigma-delta modulation. The simulation results showing the proposed technique can reject non-ideal dc bus improving the total harmonic distortion.

  6. Feedforward signal prediction for accurate motion systems using digital filters

    NARCIS (Netherlands)

    Butler, H.

    2012-01-01

    A positioning system that needs to accurately track a reference can benefit greatly from using feedforward. When using a force actuator, the feedforward needs to generate a force proportional to the reference acceleration, which can be measured by means of an accelerometer or can be created by

  7. A Feedforward Inhibitory Circuit Mediated by CB1-Expressing Fast-Spiking Interneurons in the Nucleus Accumbens.

    Science.gov (United States)

    Wright, William J; Schlüter, Oliver M; Dong, Yan

    2017-04-01

    The nucleus accumbens (NAc) gates motivated behaviors through the functional output of principle medium spiny neurons (MSNs), whereas dysfunctional output of NAc MSNs contributes to a variety of psychiatric disorders. Fast-spiking interneurons (FSIs) are sparsely distributed throughout the NAc, forming local feedforward inhibitory circuits. It remains elusive how FSI-based feedforward circuits regulate the output of NAc MSNs. Here, we investigated a distinct subpopulation of NAc FSIs that express the cannabinoid receptor type-1 (CB1). Using a combination of paired electrophysiological recordings and pharmacological approaches, we characterized and compared feedforward inhibition of NAc MSNs from CB1 + FSIs and lateral inhibition from recurrent MSN collaterals. We observed that CB1 + FSIs exerted robust inhibitory control over a large percentage of nearby MSNs in contrast to local MSN collaterals that provided only sparse and weak inhibitory input to their neighboring MSNs. Furthermore, CB1 + FSI-mediated feedforward inhibition was preferentially suppressed by endocannabinoid (eCB) signaling, whereas MSN-mediated lateral inhibition was unaffected. Finally, we demonstrated that CB1 + FSI synapses onto MSNs are capable of undergoing experience-dependent long-term depression in a voltage- and eCB-dependent manner. These findings demonstrated that CB1 + FSIs are a major source of local inhibitory control of MSNs and a critical component of the feedforward inhibitory circuits regulating the output of the NAc.

  8. Using the Internet to Study the Internet: An Active Learning Component.

    Science.gov (United States)

    Kohut, Dave; Sternberg, Joel

    1995-01-01

    Describes the Internet component of an undergraduate course at St. Xavier University (Illinois) in which a librarian helps mass communications students survey state-of-the-art technologies and predict future possibilities. Active learning techniques are discussed and examples of class exercises and the final assignment are included. (Author/LRW)

  9. On combining principal components with Fisher's linear discriminants for supervised learning

    NARCIS (Netherlands)

    Pechenizkiy, M.; Tsymbal, A.; Puuronen, S.

    2006-01-01

    "The curse of dimensionality" is pertinent to many learning algorithms, and it denotes the drastic increase of computational complexity and classification error in high dimensions. In this paper, principal component analysis (PCA), parametric feature extraction (FE) based on Fisher’s linear

  10. EEG-Based Emotion Recognition Using Deep Learning Network with Principal Component Based Covariate Shift Adaptation

    Directory of Open Access Journals (Sweden)

    Suwicha Jirayucharoensak

    2014-01-01

    Full Text Available Automatic emotion recognition is one of the most challenging tasks. To detect emotion from nonstationary EEG signals, a sophisticated learning algorithm that can represent high-level abstraction is required. This study proposes the utilization of a deep learning network (DLN to discover unknown feature correlation between input signals that is crucial for the learning task. The DLN is implemented with a stacked autoencoder (SAE using hierarchical feature learning approach. Input features of the network are power spectral densities of 32-channel EEG signals from 32 subjects. To alleviate overfitting problem, principal component analysis (PCA is applied to extract the most important components of initial input features. Furthermore, covariate shift adaptation of the principal components is implemented to minimize the nonstationary effect of EEG signals. Experimental results show that the DLN is capable of classifying three different levels of valence and arousal with accuracy of 49.52% and 46.03%, respectively. Principal component based covariate shift adaptation enhances the respective classification accuracy by 5.55% and 6.53%. Moreover, DLN provides better performance compared to SVM and naive Bayes classifiers.

  11. Image Denoising Algorithm Combined with SGK Dictionary Learning and Principal Component Analysis Noise Estimation

    Directory of Open Access Journals (Sweden)

    Wenjing Zhao

    2018-01-01

    Full Text Available SGK (sequential generalization of K-means dictionary learning denoising algorithm has the characteristics of fast denoising speed and excellent denoising performance. However, the noise standard deviation must be known in advance when using SGK algorithm to process the image. This paper presents a denoising algorithm combined with SGK dictionary learning and the principal component analysis (PCA noise estimation. At first, the noise standard deviation of the image is estimated by using the PCA noise estimation algorithm. And then it is used for SGK dictionary learning algorithm. Experimental results show the following: (1 The SGK algorithm has the best denoising performance compared with the other three dictionary learning algorithms. (2 The SGK algorithm combined with PCA is superior to the SGK algorithm combined with other noise estimation algorithms. (3 Compared with the original SGK algorithm, the proposed algorithm has higher PSNR and better denoising performance.

  12. Cerebellar contribution to feedforward control of locomotion.

    Science.gov (United States)

    Pisotta, Iolanda; Molinari, Marco

    2014-01-01

    The cerebellum is an important contributor to feedforward control mechanisms of the central nervous system, and sequencing-the process that allows spatial and temporal relationships between events to be recognized-has been implicated as the fundamental cerebellar mode of operation. By adopting such a mode and because cerebellar activity patterns are sensitive to a variety of sensorimotor-related tasks, the cerebellum is believed to support motor and cognitive functions that are encoded in the frontal and parietal lobes of the cerebral cortex. In this model, the cerebellum is hypothesized to make predictions about the consequences of a motor or cognitive command that originates from the cortex to prepare the entire system to cope with ongoing changes. In this framework, cerebellar predictive mechanisms for locomotion are addressed, focusing on sensorial and motoric sequencing. The hypothesis that sequence recognition is the mechanism by which the cerebellum functions in gait control is presented and discussed.

  13. Quantum generalisation of feedforward neural networks

    Science.gov (United States)

    Wan, Kwok Ho; Dahlsten, Oscar; Kristjánsson, Hlér; Gardner, Robert; Kim, M. S.

    2017-09-01

    We propose a quantum generalisation of a classical neural network. The classical neurons are firstly rendered reversible by adding ancillary bits. Then they are generalised to being quantum reversible, i.e., unitary (the classical networks we generalise are called feedforward, and have step-function activation functions). The quantum network can be trained efficiently using gradient descent on a cost function to perform quantum generalisations of classical tasks. We demonstrate numerically that it can: (i) compress quantum states onto a minimal number of qubits, creating a quantum autoencoder, and (ii) discover quantum communication protocols such as teleportation. Our general recipe is theoretical and implementation-independent. The quantum neuron module can naturally be implemented photonically.

  14. Honey Bees Modulate Their Olfactory Learning in the Presence of Hornet Predators and Alarm Component.

    Directory of Open Access Journals (Sweden)

    Zhengwei Wang

    Full Text Available In Southeast Asia the native honey bee species Apis cerana is often attacked by hornets (Vespa velutina, mainly in the period from April to November. During the co-evolution of these two species honey bees have developed several strategies to defend themselves such as learning the odors of hornets and releasing alarm components to inform other mates. However, so far little is known about whether and how honey bees modulate their olfactory learning in the presence of the hornet predator and alarm components of honey bee itself. In the present study, we test for associative olfactory learning of A. cerana in the presence of predator odors, the alarm pheromone component isopentyl acetate (IPA, or a floral odor (hexanal as a control. The results show that bees can detect live hornet odors, that there is almost no association between the innately aversive hornet odor and the appetitive stimulus sucrose, and that IPA is less well associated with an appetitive stimulus when compared with a floral odor. In order to imitate natural conditions, e.g. when bees are foraging on flowers and a predator shows up, or alarm pheromone is released by a captured mate, we tested combinations of the hornet odor and floral odor, or IPA and floral odor. Both of these combinations led to reduced learning scores. This study aims to contribute to a better understanding of the prey-predator system between A. cerana and V. velutina.

  15. Measuring Feedforward Inhibition and Its Impact on Local Circuit Function.

    Science.gov (United States)

    Hull, Court

    2017-05-01

    This protocol describes a series of approaches to measure feedforward inhibition in acute brain slices from the cerebellar cortex. Using whole-cell voltage and current clamp recordings from Purkinje cells in conjunction with electrical stimulation of the parallel fibers, these methods demonstrate how to measure the relationship between excitation and inhibition in a feedforward circuit. This protocol also describes how to measure the impact of feedforward inhibition on Purkinje cell excitability, with an emphasis on spike timing. © 2017 Cold Spring Harbor Laboratory Press.

  16. Nonlinear Feedforward Control for Wind Disturbance Rejection on Autonomous Helicopter

    DEFF Research Database (Denmark)

    Bisgaard, Morten; la Cour-Harbo, Anders; A. Danapalasingam, Kumeresan

    2010-01-01

    for the purpose. The model is inverted for the calculation of rotor collective and cyclic pitch angles given the wind disturbance. The control strategy is then applied on a small helicopter in a controlled wind environment and flight tests demonstrates the effectiveness and advantage of the feedforward controller.......This paper presents the design and verification of a model based nonlinear feedforward controller for wind disturbance rejection on autonomous helicopters. The feedforward control is based on a helicopter model that is derived using a number of carefully chosen simplifications to make it suitable...

  17. Encoding Time in Feedforward Trajectories of a Recurrent Neural Network Model.

    Science.gov (United States)

    Hardy, N F; Buonomano, Dean V

    2018-02-01

    Brain activity evolves through time, creating trajectories of activity that underlie sensorimotor processing, behavior, and learning and memory. Therefore, understanding the temporal nature of neural dynamics is essential to understanding brain function and behavior. In vivo studies have demonstrated that sequential transient activation of neurons can encode time. However, it remains unclear whether these patterns emerge from feedforward network architectures or from recurrent networks and, furthermore, what role network structure plays in timing. We address these issues using a recurrent neural network (RNN) model with distinct populations of excitatory and inhibitory units. Consistent with experimental data, a single RNN could autonomously produce multiple functionally feedforward trajectories, thus potentially encoding multiple timed motor patterns lasting up to several seconds. Importantly, the model accounted for Weber's law, a hallmark of timing behavior. Analysis of network connectivity revealed that efficiency-a measure of network interconnectedness-decreased as the number of stored trajectories increased. Additionally, the balance of excitation (E) and inhibition (I) shifted toward excitation during each unit's activation time, generating the prediction that observed sequential activity relies on dynamic control of the E/I balance. Our results establish for the first time that the same RNN can generate multiple functionally feedforward patterns of activity as a result of dynamic shifts in the E/I balance imposed by the connectome of the RNN. We conclude that recurrent network architectures account for sequential neural activity, as well as for a fundamental signature of timing behavior: Weber's law.

  18. Isolating Visual and Proprioceptive Components of Motor Sequence Learning in ASD.

    Science.gov (United States)

    Sharer, Elizabeth A; Mostofsky, Stewart H; Pascual-Leone, Alvaro; Oberman, Lindsay M

    2016-05-01

    In addition to defining impairments in social communication skills, individuals with autism spectrum disorder (ASD) also show impairments in more basic sensory and motor skills. Development of new skills involves integrating information from multiple sensory modalities. This input is then used to form internal models of action that can be accessed when both performing skilled movements, as well as understanding those actions performed by others. Learning skilled gestures is particularly reliant on integration of visual and proprioceptive input. We used a modified serial reaction time task (SRTT) to decompose proprioceptive and visual components and examine whether patterns of implicit motor skill learning differ in ASD participants as compared with healthy controls. While both groups learned the implicit motor sequence during training, healthy controls showed robust generalization whereas ASD participants demonstrated little generalization when visual input was constant. In contrast, no group differences in generalization were observed when proprioceptive input was constant, with both groups showing limited degrees of generalization. The findings suggest, when learning a motor sequence, individuals with ASD tend to rely less on visual feedback than do healthy controls. Visuomotor representations are considered to underlie imitative learning and action understanding and are thereby crucial to social skill and cognitive development. Thus, anomalous patterns of implicit motor learning, with a tendency to discount visual feedback, may be an important contributor in core social communication deficits that characterize ASD. Autism Res 2016, 9: 563-569. © 2015 International Society for Autism Research, Wiley Periodicals, Inc. © 2015 International Society for Autism Research, Wiley Periodicals, Inc.

  19. Multi-center MRI carotid plaque component segmentation using feature normalization and transfer learning

    DEFF Research Database (Denmark)

    van Engelen, Arna; van Dijk, Anouk C; Truijman, Martine T.B.

    2015-01-01

    implementation of supervised methods. In this paper we segment carotid plaque components of clinical interest (fibrous tissue, lipid tissue, calcification and intraplaque hemorrhage) in a multicenter MRI study. We perform voxelwise tissue classification by traditional same-center training, and compare results...... not yield significant differences from that reference. We conclude that both extensive feature normalization and transfer learning can be valuable for the development of supervised methods that perform well on different types of datasets.......Automated segmentation of plaque components in carotid artery MRI is important to enable large studies on plaque vulnerability, and for incorporating plaque composition as an imaging biomarker in clinical practice. Especially supervised classification techniques, which learn from labeled examples...

  20. Training feed-forward neural networks with gain constraints

    Science.gov (United States)

    Hartman

    2000-04-01

    Inaccurate input-output gains (partial derivatives of outputs with respect to inputs) are common in neural network models when input variables are correlated or when data are incomplete or inaccurate. Accurate gains are essential for optimization, control, and other purposes. We develop and explore a method for training feedforward neural networks subject to inequality or equality-bound constraints on the gains of the learned mapping. Gain constraints are implemented as penalty terms added to the objective function, and training is done using gradient descent. Adaptive and robust procedures are devised for balancing the relative strengths of the various terms in the objective function, which is essential when the constraints are inconsistent with the data. The approach has the virtue that the model domain of validity can be extended via extrapolation training, which can dramatically improve generalization. The algorithm is demonstrated here on artificial and real-world problems with very good results and has been advantageously applied to dozens of models currently in commercial use.

  1. Experience with feedback and feedforward for plasma control in ASDEX

    International Nuclear Information System (INIS)

    Schneider, F.

    1983-01-01

    Experimental results of vertical and radial position feedback are shown and discussed. In particular, stability problems of vertical position control are studied in detail. A feedforward procedure for the process computer is described and proved by measurements. (author)

  2. Minimal-Inversion Feedforward-And-Feedback Control System

    Science.gov (United States)

    Seraji, Homayoun

    1990-01-01

    Recent developments in theory of control systems support concept of minimal-inversion feedforward-and feedback control system consisting of three independently designable control subsystems. Applicable to the control of linear, time-invariant plant.

  3. NREL Advances Feedforward Control in Turbines (Fact Sheet)

    Energy Technology Data Exchange (ETDEWEB)

    2015-01-01

    This NREL Highlight is being produced for the 2015 February Alliance S&T Board meeting, and describes research that uses lidar and feedforward algorithms to improve rotor speed regulation and reduce costs of maintenance and operation.

  4. On Optimal Input Design for Feed-forward Control

    OpenAIRE

    Hägg, Per; Wahlberg, Bo

    2013-01-01

    This paper considers optimal input design when the intended use of the identified model is to construct a feed-forward controller based on measurable disturbances. The objective is to find a minimum power excitation signal to be used in a system identification experiment, such that the corresponding model-based feed-forward controller guarantees, with a given probability, that the variance of the output signal is within given specifications. To start with, some low order model problems are an...

  5. E-Learning as an Important Component in “Blended Learning” in School Development Projects in Norway

    OpenAIRE

    Aasen, Ann Margareth

    2013-01-01

    E-learning is an important component in ཿblended learning࿝ in all of SePU`s projects and is used for additional education and development of competences. Blended learning is defined as learning facilitated by the effective combination of different modes of delivery, models of teaching, styles of learning, and based on transparent communication among all parties involved in development competences. In general, one of the challenges with improving the workplace is linked to employee training an...

  6. Feedforward Nonlinear Control Using Neural Gas Network

    Directory of Open Access Journals (Sweden)

    Iván Machón-González

    2017-01-01

    Full Text Available Nonlinear systems control is a main issue in control theory. Many developed applications suffer from a mathematical foundation not as general as the theory of linear systems. This paper proposes a control strategy of nonlinear systems with unknown dynamics by means of a set of local linear models obtained by a supervised neural gas network. The proposed approach takes advantage of the neural gas feature by which the algorithm yields a very robust clustering procedure. The direct model of the plant constitutes a piece-wise linear approximation of the nonlinear system and each neuron represents a local linear model for which a linear controller is designed. The neural gas model works as an observer and a controller at the same time. A state feedback control is implemented by estimation of the state variables based on the local transfer function that was provided by the local linear model. The gradient vectors obtained by the supervised neural gas algorithm provide a robust procedure for feedforward nonlinear control, that is, supposing the inexistence of disturbances.

  7. Machine learning of frustrated classical spin models. I. Principal component analysis

    Science.gov (United States)

    Wang, Ce; Zhai, Hui

    2017-10-01

    This work aims at determining whether artificial intelligence can recognize a phase transition without prior human knowledge. If this were successful, it could be applied to, for instance, analyzing data from the quantum simulation of unsolved physical models. Toward this goal, we first need to apply the machine learning algorithm to well-understood models and see whether the outputs are consistent with our prior knowledge, which serves as the benchmark for this approach. In this work, we feed the computer data generated by the classical Monte Carlo simulation for the X Y model in frustrated triangular and union jack lattices, which has two order parameters and exhibits two phase transitions. We show that the outputs of the principal component analysis agree very well with our understanding of different orders in different phases, and the temperature dependences of the major components detect the nature and the locations of the phase transitions. Our work offers promise for using machine learning techniques to study sophisticated statistical models, and our results can be further improved by using principal component analysis with kernel tricks and the neural network method.

  8. Principal component reconstruction (PCR) for cine CBCT with motion learning from 2D fluoroscopy.

    Science.gov (United States)

    Gao, Hao; Zhang, Yawei; Ren, Lei; Yin, Fang-Fang

    2018-01-01

    This work aims to generate cine CT images (i.e., 4D images with high-temporal resolution) based on a novel principal component reconstruction (PCR) technique with motion learning from 2D fluoroscopic training images. In the proposed PCR method, the matrix factorization is utilized as an explicit low-rank regularization of 4D images that are represented as a product of spatial principal components and temporal motion coefficients. The key hypothesis of PCR is that temporal coefficients from 4D images can be reasonably approximated by temporal coefficients learned from 2D fluoroscopic training projections. For this purpose, we can acquire fluoroscopic training projections for a few breathing periods at fixed gantry angles that are free from geometric distortion due to gantry rotation, that is, fluoroscopy-based motion learning. Such training projections can provide an effective characterization of the breathing motion. The temporal coefficients can be extracted from these training projections and used as priors for PCR, even though principal components from training projections are certainly not the same for these 4D images to be reconstructed. For this purpose, training data are synchronized with reconstruction data using identical real-time breathing position intervals for projection binning. In terms of image reconstruction, with a priori temporal coefficients, the data fidelity for PCR changes from nonlinear to linear, and consequently, the PCR method is robust and can be solved efficiently. PCR is formulated as a convex optimization problem with the sum of linear data fidelity with respect to spatial principal components and spatiotemporal total variation regularization imposed on 4D image phases. The solution algorithm of PCR is developed based on alternating direction method of multipliers. The implementation is fully parallelized on GPU with NVIDIA CUDA toolbox and each reconstruction takes about a few minutes. The proposed PCR method is validated and

  9. Hybrid Analytical and Data-Driven Modeling for Feed-Forward Robot Control †

    Directory of Open Access Journals (Sweden)

    René Felix Reinhart

    2017-02-01

    Full Text Available Feed-forward model-based control relies on models of the controlled plant, e.g., in robotics on accurate knowledge of manipulator kinematics or dynamics. However, mechanical and analytical models do not capture all aspects of a plant’s intrinsic properties and there remain unmodeled dynamics due to varying parameters, unmodeled friction or soft materials. In this context, machine learning is an alternative suitable technique to extract non-linear plant models from data. However, fully data-based models suffer from inaccuracies as well and are inefficient if they include learning of well known analytical models. This paper thus argues that feed-forward control based on hybrid models comprising an analytical model and a learned error model can significantly improve modeling accuracy. Hybrid modeling here serves the purpose to combine the best of the two modeling worlds. The hybrid modeling methodology is described and the approach is demonstrated for two typical problems in robotics, i.e., inverse kinematics control and computed torque control. The former is performed for a redundant soft robot and the latter for a rigid industrial robot with redundant degrees of freedom, where a complete analytical model is not available for any of the platforms.

  10. Hybrid Analytical and Data-Driven Modeling for Feed-Forward Robot Control.

    Science.gov (United States)

    Reinhart, René Felix; Shareef, Zeeshan; Steil, Jochen Jakob

    2017-02-08

    Feed-forward model-based control relies on models of the controlled plant, e.g., in robotics on accurate knowledge of manipulator kinematics or dynamics. However, mechanical and analytical models do not capture all aspects of a plant's intrinsic properties and there remain unmodeled dynamics due to varying parameters, unmodeled friction or soft materials. In this context, machine learning is an alternative suitable technique to extract non-linear plant models from data. However, fully data-based models suffer from inaccuracies as well and are inefficient if they include learning of well known analytical models. This paper thus argues that feed-forward control based on hybrid models comprising an analytical model and a learned error model can significantly improve modeling accuracy. Hybrid modeling here serves the purpose to combine the best of the two modeling worlds. The hybrid modeling methodology is described and the approach is demonstrated for two typical problems in robotics, i.e., inverse kinematics control and computed torque control. The former is performed for a redundant soft robot and the latter for a rigid industrial robot with redundant degrees of freedom, where a complete analytical model is not available for any of the platforms.

  11. Hybrid Analytical and Data-Driven Modeling for Feed-Forward Robot Control †

    Science.gov (United States)

    Reinhart, René Felix; Shareef, Zeeshan; Steil, Jochen Jakob

    2017-01-01

    Feed-forward model-based control relies on models of the controlled plant, e.g., in robotics on accurate knowledge of manipulator kinematics or dynamics. However, mechanical and analytical models do not capture all aspects of a plant’s intrinsic properties and there remain unmodeled dynamics due to varying parameters, unmodeled friction or soft materials. In this context, machine learning is an alternative suitable technique to extract non-linear plant models from data. However, fully data-based models suffer from inaccuracies as well and are inefficient if they include learning of well known analytical models. This paper thus argues that feed-forward control based on hybrid models comprising an analytical model and a learned error model can significantly improve modeling accuracy. Hybrid modeling here serves the purpose to combine the best of the two modeling worlds. The hybrid modeling methodology is described and the approach is demonstrated for two typical problems in robotics, i.e., inverse kinematics control and computed torque control. The former is performed for a redundant soft robot and the latter for a rigid industrial robot with redundant degrees of freedom, where a complete analytical model is not available for any of the platforms. PMID:28208697

  12. An empirical investigation of intellectual capital components on each others and organizational learning capabilities

    Directory of Open Access Journals (Sweden)

    Nabi ollah Nejatizadeh

    2013-02-01

    Full Text Available During the past few years, there have been growing interests on intellectual capital due to industrial changes on the market. Thus, identifying different ways to create, manage, and evaluate the impact of intellectual capital has remained an open area of research. One of the most important organizational capabilities, which could help organizations create and share knowledge is to effectively use knowledge to create competitive advantage. The primary objective of this study is to investigate the effects of intellectual capital on other components and their impacts on organizational learning capability using structural equation modeling. The statistical population includes 500 employees of an Iranian organization. The study uses a sample size including 273 people using Morgan statistical table. In our survey, human capital influences positively (0.330 on structural capital, human capital influences positively on relational capital (0.47 and relational capital influences positively on structural capital (0.455. In addition human capital influences positively on learning capabilities (0.06, structural capital impacts learning capabilities (0.355 and relational capital on learning capabilities (0.545.

  13. Optimisation of a machine learning algorithm in human locomotion using principal component and discriminant function analyses.

    Science.gov (United States)

    Bisele, Maria; Bencsik, Martin; Lewis, Martin G C; Barnett, Cleveland T

    2017-01-01

    Assessment methods in human locomotion often involve the description of normalised graphical profiles and/or the extraction of discrete variables. Whilst useful, these approaches may not represent the full complexity of gait data. Multivariate statistical methods, such as Principal Component Analysis (PCA) and Discriminant Function Analysis (DFA), have been adopted since they have the potential to overcome these data handling issues. The aim of the current study was to develop and optimise a specific machine learning algorithm for processing human locomotion data. Twenty participants ran at a self-selected speed across a 15m runway in barefoot and shod conditions. Ground reaction forces (BW) and kinematics were measured at 1000 Hz and 100 Hz, respectively from which joint angles (°), joint moments (N.m.kg-1) and joint powers (W.kg-1) for the hip, knee and ankle joints were calculated in all three anatomical planes. Using PCA and DFA, power spectra of the kinematic and kinetic variables were used as a training database for the development of a machine learning algorithm. All possible combinations of 10 out of 20 participants were explored to find the iteration of individuals that would optimise the machine learning algorithm. The results showed that the algorithm was able to successfully predict whether a participant ran shod or barefoot in 93.5% of cases. To the authors' knowledge, this is the first study to optimise the development of a machine learning algorithm.

  14. Learning representative features for facial images based on a modified principal component analysis

    Science.gov (United States)

    Averkin, Anton; Potapov, Alexey

    2013-05-01

    The paper is devoted to facial image analysis and particularly deals with the problem of automatic evaluation of the attractiveness of human faces. We propose a new approach for automatic construction of feature space based on a modified principal component analysis. Input data sets for the algorithm are the learning data sets of facial images, which are rated by one person. The proposed approach allows one to extract features of the individual subjective face beauty perception and to predict attractiveness values for new facial images, which were not included into a learning data set. The Pearson correlation coefficient between values predicted by our method for new facial images and personal attractiveness estimation values equals to 0.89. This means that the new approach proposed is promising and can be used for predicting subjective face attractiveness values in real systems of the facial images analysis.

  15. Model of components in a process of acoustic diagnosis correlated with learning

    International Nuclear Information System (INIS)

    Seballos, S.; Costabal, H.; Matamala, P.

    1992-06-01

    Using Linden's functional scheme as a theoretical reference framework, we define a matrix of component for clinical and field applications in the acoustic diagnostic process and correlations with audiologic, learning and behavioral problems. It is expected that the model effectively contributes to classify and provide a greater knowledge about this multidisciplinary problem. Although the exact nature of this component is at present a matter to be defined, its correlation can be hypothetically established. Applying this descriptive and integral approach in the diagnostic process it is possible if not to avoid, at least to decrease, the uncertainties and assure the proper solutions becoming a powerful tool applicable to environmental studies and/or social claims. (author). 8 refs, 2 figs

  16. Resource-efficient ILC for LTI/LTV systems through LQ tracking and stable inversion: enabling large feedforward tasks on a position-dependent printer

    NARCIS (Netherlands)

    van Zundert, J.; Bolder, J.J.; Koekebakker, S.H.; Oomen, T.A.E.

    Iterative learning control (ILC) enables high performance for systems that execute repeating tasks. Norm-optimal ILC based on lifted system representations provides an analytic expression for the optimal feedforward signal. However, for large tasks the computational load increases rapidly for

  17. Feed-forward motor control of ultrafast, ballistic movements.

    Science.gov (United States)

    Kagaya, K; Patek, S N

    2016-02-01

    To circumvent the limits of muscle, ultrafast movements achieve high power through the use of springs and latches. The time scale of these movements is too short for control through typical neuromuscular mechanisms, thus ultrafast movements are either invariant or controlled prior to movement. We tested whether mantis shrimp (Stomatopoda: Neogonodactylus bredini) vary their ultrafast smashing strikes and, if so, how this control is achieved prior to movement. We collected high-speed images of strike mechanics and electromyograms of the extensor and flexor muscles that control spring compression and latch release. During spring compression, lateral extensor and flexor units were co-activated. The strike initiated several milliseconds after the flexor units ceased, suggesting that flexor activity prevents spring release and determines the timing of strike initiation. We used linear mixed models and Akaike's information criterion to serially evaluate multiple hypotheses for control mechanisms. We found that variation in spring compression and strike angular velocity were statistically explained by spike activity of the extensor muscle. The results show that mantis shrimp can generate kinematically variable strikes and that their kinematics can be changed through adjustments to motor activity prior to the movement, thus supporting an upstream, central-nervous-system-based control of ultrafast movement. Based on these and other findings, we present a shishiodoshi model that illustrates alternative models of control in biological ballistic systems. The discovery of feed-forward control in mantis shrimp sets the stage for the assessment of targets, strategic variation in kinematics and the role of learning in ultrafast animals. © 2016. Published by The Company of Biologists Ltd.

  18. Beliefs on Learning and Teaching Language Components: The Case of Iranian EAP and EFL Learners

    Directory of Open Access Journals (Sweden)

    Gholamreza Parsi

    2017-06-01

    Full Text Available The present study intended to investigate the possible difference between EAP and EFL learners’ beliefs concerning learning and teaching of language components, namely, vocabulary, pronunciation and grammar. Furthermore, this study examined the association between EAP and EFL learners’ beliefs and their language components’ development. To this end, 231 undergraduate EAP (117 and EFL (114 learners at Ferdowsi University took part in the study by completing a five-point Likert scale questionnaire adapted from Simon and Taverniers (2011. The face and content validity of the questionnaire was confirmed by the experts’ judgment and factor analysis. Moreover using Cronbach alpha coefficient the questionnaire was found acceptably reliable (α=0.88. Furthermore, for language components’ development, the EAP learners’ scores in English course and EFL learners’ average scores in their Basic English courses were taken into account. The results of an Independent Samples t-test revealed that there existed a statistically significant difference between EAP and EFL learners’ beliefs on learning and teaching language components. Furthermore, the results of Pearson correlation coefficients indicated a statistically significant positive association between EFL learners’ beliefs and their language components’ development, however no statistically significant correlation was found between EAP learners’ beliefs and their language components’ development.

  19. Aero Engine Component Fault Diagnosis Using Multi-Hidden-Layer Extreme Learning Machine with Optimized Structure

    Directory of Open Access Journals (Sweden)

    Shan Pang

    2016-01-01

    Full Text Available A new aero gas turbine engine gas path component fault diagnosis method based on multi-hidden-layer extreme learning machine with optimized structure (OM-ELM was proposed. OM-ELM employs quantum-behaved particle swarm optimization to automatically obtain the optimal network structure according to both the root mean square error on training data set and the norm of output weights. The proposed method is applied to handwritten recognition data set and a gas turbine engine diagnostic application and is compared with basic ELM, multi-hidden-layer ELM, and two state-of-the-art deep learning algorithms: deep belief network and the stacked denoising autoencoder. Results show that, with optimized network structure, OM-ELM obtains better test accuracy in both applications and is more robust to sensor noise. Meanwhile it controls the model complexity and needs far less hidden nodes than multi-hidden-layer ELM, thus saving computer memory and making it more efficient to implement. All these advantages make our method an effective and reliable tool for engine component fault diagnosis tool.

  20. Feedforward somatosensory inhibition is normal in cervical dystonia.

    Science.gov (United States)

    Ferrè, Elisa R; Ganos, Christos; Bhatia, Kailash P; Haggard, Patrick

    2015-03-01

    Insufficient cortical inhibition is a key pathophysiological finding in dystonia. Subliminal sensory stimuli were reported to transiently inhibit somatosensory processing. Here we investigated whether such subliminal feedforward inhibition is reduced in patients with cervical dystonia. Sixteen cervical dystonia patients and 16 matched healthy controls performed a somatosensory detection task. We measured the drop in sensitivity to detect a threshold-level digital nerve shock when it was preceded by a subliminal conditioning shock, compared to when it was not. Subliminal conditioning shocks reduced sensitivity to threshold stimuli to a similar extent in both patients and controls, suggesting that somatosensory subliminal feedforward inhibition is normal in cervical dystonia. Somatosensory feedforward inhibition was normal in this group of cervical dystonia patients. Our results qualify previous concepts of a general dystonic deficit in sensorimotor inhibitory processing. Copyright © 2015 Elsevier Ltd. All rights reserved.

  1. Neural network based approach for tuning of SNS feedback and feedforward controllers

    International Nuclear Information System (INIS)

    Kwon, Sung-Il; Prokop, Mark S.; Regan, Amy H.

    2002-01-01

    The primary controllers in the SNS low level RF system are proportional-integral (PI) feedback controllers. To obtain the best performance of the linac control systems, approximately 91 individual PI controller gains should be optimally tuned. Tuning is time consuming and requires automation. In this paper, a neural network is used for the controller gain tuning. A neural network can approximate any continuous mapping through learning. In a sense, the cavity loop PI controller is a continuous mapping of the tracking error and its one-sample-delay inputs to the controller output. Also, monotonic cavity output with respect to its input makes knowing the detailed parameters of the cavity unnecessary. Hence the PI controller is a prime candidate for approximation through a neural network. Using mean square error minimization to train the neural network along with a continuous mapping of appropriate weights, optimally tuned PI controller gains can be determined. The same neural network approximation property is also applied to enhance the adaptive feedforward controller performance. This is done by adjusting the feedforward controller gains, forgetting factor, and learning ratio. Lastly, the automation of the tuning procedure data measurement, neural network training, tuning and loading the controller gain to the DSP is addressed.

  2. Extracting functionally feedforward networks from a population of spiking neurons.

    Science.gov (United States)

    Vincent, Kathleen; Tauskela, Joseph S; Thivierge, Jean-Philippe

    2012-01-01

    Neuronal avalanches are a ubiquitous form of activity characterized by spontaneous bursts whose size distribution follows a power-law. Recent theoretical models have replicated power-law avalanches by assuming the presence of functionally feedforward connections (FFCs) in the underlying dynamics of the system. Accordingly, avalanches are generated by a feedforward chain of activation that persists despite being embedded in a larger, massively recurrent circuit. However, it is unclear to what extent networks of living neurons that exhibit power-law avalanches rely on FFCs. Here, we employed a computational approach to reconstruct the functional connectivity of cultured cortical neurons plated on multielectrode arrays (MEAs) and investigated whether pharmacologically induced alterations in avalanche dynamics are accompanied by changes in FFCs. This approach begins by extracting a functional network of directed links between pairs of neurons, and then evaluates the strength of FFCs using Schur decomposition. In a first step, we examined the ability of this approach to extract FFCs from simulated spiking neurons. The strength of FFCs obtained in strictly feedforward networks diminished monotonically as links were gradually rewired at random. Next, we estimated the FFCs of spontaneously active cortical neuron cultures in the presence of either a control medium, a GABA(A) receptor antagonist (PTX), or an AMPA receptor antagonist combined with an NMDA receptor antagonist (APV/DNQX). The distribution of avalanche sizes in these cultures was modulated by this pharmacology, with a shallower power-law under PTX (due to the prominence of larger avalanches) and a steeper power-law under APV/DNQX (due to avalanches recruiting fewer neurons) relative to control cultures. The strength of FFCs increased in networks after application of PTX, consistent with an amplification of feedforward activity during avalanches. Conversely, FFCs decreased after application of APV

  3. Decoding small surface codes with feedforward neural networks

    Science.gov (United States)

    Varsamopoulos, Savvas; Criger, Ben; Bertels, Koen

    2018-01-01

    Surface codes reach high error thresholds when decoded with known algorithms, but the decoding time will likely exceed the available time budget, especially for near-term implementations. To decrease the decoding time, we reduce the decoding problem to a classification problem that a feedforward neural network can solve. We investigate quantum error correction and fault tolerance at small code distances using neural network-based decoders, demonstrating that the neural network can generalize to inputs that were not provided during training and that they can reach similar or better decoding performance compared to previous algorithms. We conclude by discussing the time required by a feedforward neural network decoder in hardware.

  4. Feedforward Tracking Control of Flat Recurrent Fuzzy Systems

    International Nuclear Information System (INIS)

    Gering, Stefan; Adamy, Jürgen

    2014-01-01

    Flatness based feedforward control has proven to be a feasible solution for the problem of tracking control, which may be applied to a broad class of nonlinear systems. If a flat output of the system is known, the control is often based on a feedforward controller generating a nominal input in combination with a linear controller stabilizing the linearized error dynamics around the trajectory. We show in this paper that the very same idea may be incorporated for tracking control of MIMO recurrent fuzzy systems. Their dynamics is given by means of linguistic differential equations but may be converted into a hybrid system representation, which then serves as the basis for controller synthesis

  5. Feedforward Tracking Control of Flat Recurrent Fuzzy Systems

    Science.gov (United States)

    Gering, Stefan; Adamy, Jürgen

    2014-12-01

    Flatness based feedforward control has proven to be a feasible solution for the problem of tracking control, which may be applied to a broad class of nonlinear systems. If a flat output of the system is known, the control is often based on a feedforward controller generating a nominal input in combination with a linear controller stabilizing the linearized error dynamics around the trajectory. We show in this paper that the very same idea may be incorporated for tracking control of MIMO recurrent fuzzy systems. Their dynamics is given by means of linguistic differential equations but may be converted into a hybrid system representation, which then serves as the basis for controller synthesis.

  6. Robust Position Tracking for Electro-Hydraulic Drives Based on Generalized Feedforward Compensation Approach

    DEFF Research Database (Denmark)

    Schmidt, Lasse; Andersen, Torben Ole; Pedersen, Henrik C.

    2012-01-01

    This paper presents a robust tracking control concept based on accurate feedforward compensation for hydraulic valve-cylinder drives. The proposed feedforward compensator is obtained utilizing a generalized description of the valve flow that takes into account any asymmetry of valves and...... constant gain type feedforward compensator, when subjected to strong perturbations in supply pressure and coulomb friction....

  7. Resting State EEG in Children With Learning Disabilities: An Independent Component Analysis Approach.

    Science.gov (United States)

    Jäncke, Lutz; Alahmadi, Nsreen

    2016-01-01

    In this study, the neurophysiological underpinnings of learning disabilities (LD) in children are examined using resting state EEG. We were particularly interested in the neurophysiological differences between children with learning disabilities not otherwise specified (LD-NOS), learning disabilities with verbal disabilities (LD-Verbal), and healthy control (HC) children. We applied 2 different approaches to examine the differences between the different groups. First, we calculated theta/beta and theta/alpha ratios in order to quantify the relationship between slow and fast EEG oscillations. Second, we used a recently developed method for analyzing spectral EEG, namely the group independent component analysis (gICA) model. Using these measures, we identified substantial differences between LD and HC children and between LD-NOS and LD-Verbal children in terms of their spectral EEG profiles. We obtained the following findings: (a) theta/beta and theta/alpha ratios were substantially larger in LD than in HC children, with no difference between LD-NOS and LD-Verbal children; (b) there was substantial slowing of EEG oscillations, especially for gICs located in frontal scalp positions, with LD-NOS children demonstrating the strongest slowing; (c) the estimated intracortical sources of these gICs were mostly located in brain areas involved in the control of executive functions, attention, planning, and language; and (d) the LD-Verbal children demonstrated substantial differences in EEG oscillations compared with LD-NOS children, and these differences were localized in language-related brain areas. The general pattern of atypical neurophysiological activation found in LD children suggests that they suffer from neurophysiological dysfunction in brain areas involved with the control of attention, executive functions, planning, and language functions. LD-Verbal children also demonstrate atypical activation, especially in language-related brain areas. These atypical

  8. Two aspects of feedforward postural control: anticipatory postural adjustments and anticipatory synergy adjustments.

    Science.gov (United States)

    Klous, Miriam; Mikulic, Pavle; Latash, Mark L

    2011-05-01

    We used the framework of the uncontrolled manifold hypothesis to explore the relations between anticipatory synergy adjustments (ASAs) and anticipatory postural adjustments (APAs) during feedforward control of vertical posture. ASAs represent a drop in the index of a multimuscle-mode synergy stabilizing the coordinate of the center of pressure in preparation to an action. ASAs reflect early changes of an index of covariation among variables reflecting muscle activation, whereas APAs reflect early changes in muscle activation levels averaged across trials. The assumed purpose of ASAs is to modify stability of performance variables, whereas the purpose of APAs is to change magnitudes of those variables. We hypothesized that ASAs would be seen before APAs and that this finding would be consistent with regard to the muscle-mode composition defined on the basis of different tasks and phases of action. Subjects performed a voluntary body sway task and a quick, bilateral shoulder flexion task under self-paced and reaction time conditions. Surface muscle activity of 12 leg and trunk muscles was analyzed to identify sets of 4 muscle modes for each task and for different phases within the shoulder flexion task. Variance components in the muscle-mode space and indexes of multimuscle-mode synergy stabilizing shift of the center of pressure were computed. ASAs were seen ∼ 100-150 ms prior to the task initiation, before APAs. The results were consistent with respect to different sets of muscle modes defined over the two tasks and different shoulder flexion phases. We conclude that the preparation for a self-triggered postural perturbation is associated with two types of anticipatory adjustments, ASAs and APAs. They reflect different feedforward processes within the hypothetical hierarchical control scheme, resulting in changes in patterns of covariation of elemental variables and in their patterns averaged across trials, respectively. The results show that synergies quantified

  9. Development of Feedforward Control in a Dynamic Manual Tracking Task

    Science.gov (United States)

    van Roon, Dominique; Caeyenberghs, Karen; Swinnen, Stephan P.; Smits-Engelsman, Bouwien C. M.

    2008-01-01

    To examine the development of feedforward control during manual tracking, 117 participants in 5 age groups (6 to 7, 8 to 9, 10 to 11, 12 to 14, and 15 to 17 years) tracked an accelerating dot presented on a monitor by moving an electronic pen on a digitizer. To remain successful at higher target velocities, they had to create a predictive model of…

  10. A stochastic optimal feedforward and feedback control methodology for superagility

    Science.gov (United States)

    Halyo, Nesim; Direskeneli, Haldun; Taylor, Deborah B.

    1992-01-01

    A new control design methodology is developed: Stochastic Optimal Feedforward and Feedback Technology (SOFFT). Traditional design techniques optimize a single cost function (which expresses the design objectives) to obtain both the feedforward and feedback control laws. This approach places conflicting demands on the control law such as fast tracking versus noise atttenuation/disturbance rejection. In the SOFFT approach, two cost functions are defined. The feedforward control law is designed to optimize one cost function, the feedback optimizes the other. By separating the design objectives and decoupling the feedforward and feedback design processes, both objectives can be achieved fully. A new measure of command tracking performance, Z-plots, is also developed. By analyzing these plots at off-nominal conditions, the sensitivity or robustness of the system in tracking commands can be predicted. Z-plots provide an important tool for designing robust control systems. The Variable-Gain SOFFT methodology was used to design a flight control system for the F/A-18 aircraft. It is shown that SOFFT can be used to expand the operating regime and provide greater performance (flying/handling qualities) throughout the extended flight regime. This work was performed under the NASA SBIR program. ICS plans to market the software developed as a new module in its commercial CACSD software package: ACET.

  11. Regularization and Complexity Control in Feed-forward Networks

    OpenAIRE

    Bishop, C. M.

    1995-01-01

    In this paper we consider four alternative approaches to complexity control in feed-forward networks based respectively on architecture selection, regularization, early stopping, and training with noise. We show that there are close similarities between these approaches and we argue that, for most practical applications, the technique of regularization should be the method of choice.

  12. MIMO FIR feedforward design for zero error tracking control

    NARCIS (Netherlands)

    Heertjes, M.F.; Bruijnen, D.J.H.

    2014-01-01

    This paper discusses a multi-input multi-output (MIMO) finite impulse response (FIR) feedforward design. The design is intended for systems that have (non-)minimum phase zeros in the plant description. The zeros of the plant (either minimum or non-minimum phase) are used in the shaping of the

  13. Adaptive feedforward in the LANL rf control system

    International Nuclear Information System (INIS)

    Ziomek, C.D.

    1992-01-01

    This paper describes an adaptive feedforward system that corrects repetitive errors in the amplitude and phase of the RF field of a pulsed accelerator. High-frequency disturbances that are beyond the effective bandwidth of the RF field feedback control system can be eliminated with a feedforward system. Many RF field disturbances for a pulsed accelerator are repetitive, occurring at the same relative time in every pulse. This design employs digital signal processing hardware to adaptively determine and track the control signals required to eliminate the repetitive errors in the feedback control system. In order to provide the necessary high-frequency response, the adaptive feedforward hardware provides the calculated control signal prior to the repetitive disturbance that it corrects. This system has been demonstrated to reduce the transient disturbances caused by beam pulses. Furthermore, it has been shown to negate high-frequency phase and amplitude oscillations in a high-power klystron amplifier caused by PFN ripple on the high-voltage. The design and results of the adaptive feedforward system are presented

  14. Classes of feedforward neural networks and their circuit complexity

    NARCIS (Netherlands)

    Shawe-Taylor, John S.; Anthony, Martin H.G.; Kern, Walter

    1992-01-01

    This paper aims to place neural networks in the context of boolean circuit complexity. We define appropriate classes of feedforward neural networks with specified fan-in, accuracy of computation and depth and using techniques of communication complexity proceed to show that the classes fit into a

  15. Feedforward: helping students interpret written feedback

    OpenAIRE

    Hurford, Donna; Read, Andrew

    2008-01-01

    "Assessment for Learning is the process of seeking and interpreting evidence for use by learners... "(Assessment Reform Group, 2002, p.2): for the Higher Education tutor, written feedback forms an integral part of this. This short article reports on teaching methods to engage students in feedback and assessment of their written work.

  16. Motivational component profiles in university students learning histology: a comparative study between genders and different health science curricula

    OpenAIRE

    Campos-Sánchez, Antonio; López-Núñez, Juan Antonio; Carriel, Víctor; Martín-Piedra, Miguel-Ángel; Sola, Tomás; Alaminos, Miguel

    2014-01-01

    Background: The students' motivation to learn basic sciences in health science curricula is poorly understood. The purpose of this study was to investigate the influence of different components of motivation (intrinsic motivation, self-determination, self-efficacy and extrinsic -career and grade-motivation) on learning human histology in health science curricula and their relationship with the final performance of the students in histology. Methods: Glynn Science Motivation Questionnaire ...

  17. The Component Operational Experience Degradation and Ageing Program (CODAP). Review and lessons learned (2011-2014)

    International Nuclear Information System (INIS)

    Dragea, Tudor; Riznic, Jovica R.

    2015-01-01

    The structural integrity of piping systems is crucial to continuous and safe operation of nuclear power plants. Across all designs, the pressure boundary and its related piping and components, form one of the many levels of defense in the continuous and safe operation of a nuclear power plant. It is therefore necessary to identify, understand, evaluate and catalogue all of the various degradation mechanisms and failures that affect various piping systems and components across all nuclear power plants (NPP's). This need was first recognized in 1994 by the Swedish Nuclear Power Inspectorate (SKI) which launched a five-year Research and Development (R and D) project to explore the viability of creating an international pipe failure database (SKI-PIPE) (Riznic, 2007). The project was considered to be very successful and in 2002, the Organization for Economic Co-operation and Development (OECD) Pipe Failure Data Exchange (OPDE) was created. OPDE was operated under the umbrella of the OECD Nuclear Energy Agency (NEA) and was created in order to produce an international database on the piping service experience applicable to commercial nuclear power plants. After the successful completion of OPDE, the OECD, as well as other international members, agreed to participate in OPDE's successor: the Component Operational Experience Degradation and Ageing Program (CODAP). The objective of CODAP is to collect information on all possible events related to the failure and degradation of passive metallic components in NPP's. With CODAP winding down to the completion of its first phase in December 2014, this report will focus on the conclusions and the lessons learned throughout the many years of CODAP's implementation. There are currently 14 countries participating in CODAP, many of whom are industry leaders (France, Canada, U.S.A., Germany, Japan, Korea etc.). This cooperation on an international scale provides a library of OPerational EXperience (OPEX) for all participating NPP

  18. Feedforward-feedback hybrid control for magnetic shape memory alloy actuators based on the Krasnosel'skii-Pokrovskii model.

    Directory of Open Access Journals (Sweden)

    Miaolei Zhou

    Full Text Available As a new type of smart material, magnetic shape memory alloy has the advantages of a fast response frequency and outstanding strain capability in the field of microdrive and microposition actuators. The hysteresis nonlinearity in magnetic shape memory alloy actuators, however, limits system performance and further application. Here we propose a feedforward-feedback hybrid control method to improve control precision and mitigate the effects of the hysteresis nonlinearity of magnetic shape memory alloy actuators. First, hysteresis nonlinearity compensation for the magnetic shape memory alloy actuator is implemented by establishing a feedforward controller which is an inverse hysteresis model based on Krasnosel'skii-Pokrovskii operator. Secondly, the paper employs the classical Proportion Integration Differentiation feedback control with feedforward control to comprise the hybrid control system, and for further enhancing the adaptive performance of the system and improving the control accuracy, the Radial Basis Function neural network self-tuning Proportion Integration Differentiation feedback control replaces the classical Proportion Integration Differentiation feedback control. Utilizing self-learning ability of the Radial Basis Function neural network obtains Jacobian information of magnetic shape memory alloy actuator for the on-line adjustment of parameters in Proportion Integration Differentiation controller. Finally, simulation results show that the hybrid control method proposed in this paper can greatly improve the control precision of magnetic shape memory alloy actuator and the maximum tracking error is reduced from 1.1% in the open-loop system to 0.43% in the hybrid control system.

  19. Feedforward-feedback hybrid control for magnetic shape memory alloy actuators based on the Krasnosel'skii-Pokrovskii model.

    Science.gov (United States)

    Zhou, Miaolei; Zhang, Qi; Wang, Jingyuan

    2014-01-01

    As a new type of smart material, magnetic shape memory alloy has the advantages of a fast response frequency and outstanding strain capability in the field of microdrive and microposition actuators. The hysteresis nonlinearity in magnetic shape memory alloy actuators, however, limits system performance and further application. Here we propose a feedforward-feedback hybrid control method to improve control precision and mitigate the effects of the hysteresis nonlinearity of magnetic shape memory alloy actuators. First, hysteresis nonlinearity compensation for the magnetic shape memory alloy actuator is implemented by establishing a feedforward controller which is an inverse hysteresis model based on Krasnosel'skii-Pokrovskii operator. Secondly, the paper employs the classical Proportion Integration Differentiation feedback control with feedforward control to comprise the hybrid control system, and for further enhancing the adaptive performance of the system and improving the control accuracy, the Radial Basis Function neural network self-tuning Proportion Integration Differentiation feedback control replaces the classical Proportion Integration Differentiation feedback control. Utilizing self-learning ability of the Radial Basis Function neural network obtains Jacobian information of magnetic shape memory alloy actuator for the on-line adjustment of parameters in Proportion Integration Differentiation controller. Finally, simulation results show that the hybrid control method proposed in this paper can greatly improve the control precision of magnetic shape memory alloy actuator and the maximum tracking error is reduced from 1.1% in the open-loop system to 0.43% in the hybrid control system.

  20. Cell-type specific short-term plasticity at auditory nerve synapses controls feed-forward inhibition in the dorsal cochlear nucleus

    Directory of Open Access Journals (Sweden)

    Miloslav eSedlacek

    2014-07-01

    Full Text Available Feedforward inhibition represents a powerful mechanism by which control of the timing and fidelity of action potentials in local synaptic circuits of various brain regions is achieved. In the cochlear nucleus, the auditory nerve provides excitation to both principal neurons and inhibitory interneurons. Here, we investigated the synaptic circuit associated with fusiform cells (FCs, principal neurons of the dorsal cochlear nucleus (DCN that receive excitation from auditory nerve fibers and inhibition from tuberculoventral cells (TVCs on their basal dendrites in the deep layer of DCN. Despite the importance of these inputs in regulating fusiform cell firing behavior, the mechanisms determining the balance of excitation and feed-forward inhibition in this circuit are not well understood. Therefore, we examined the timing and plasticity of auditory nerve driven feed-forward inhibition (FFI onto FCs. We find that in some FCs, excitatory and inhibitory components of feed-forward inhibition had the same stimulation thresholds indicating they could be triggered by activation of the same fibers. In other FCs, excitation and inhibition exhibit different stimulus thresholds, suggesting FCs and TVCs might be activated by different sets of fibers. In addition we find that during repetitive activation, synapses formed by the auditory nerve onto TVCs and FCs exhibit distinct modes of short-term plasticity. Feed-forward inhibitory post-synaptic currents (IPSCs in FCs exhibit short-term depression because of prominent synaptic depression at the auditory nerve-TVC synapse. Depression of this feedforward inhibitory input causes a shift in the balance of fusiform cell synaptic input towards greater excitation and suggests that fusiform cell spike output will be enhanced by physiological patterns of auditory nerve activity.

  1. Motivational component profiles in university students learning histology: a comparative study between genders and different health science curricula.

    Science.gov (United States)

    Campos-Sánchez, Antonio; López-Núñez, Juan Antonio; Carriel, Víctor; Martín-Piedra, Miguel-Ángel; Sola, Tomás; Alaminos, Miguel

    2014-03-10

    The students' motivation to learn basic sciences in health science curricula is poorly understood. The purpose of this study was to investigate the influence of different components of motivation (intrinsic motivation, self-determination, self-efficacy and extrinsic -career and grade- motivation) on learning human histology in health science curricula and their relationship with the final performance of the students in histology. Glynn Science Motivation Questionnaire II was used to compare students' motivation components to learn histology in 367 first-year male and female undergraduate students enrolled in medical, dentistry and pharmacy degree programs. For intrinsic motivation, career motivation and self-efficacy, the highest values corresponded to medical students, whereas dentistry students showed the highest values for self-determination and grade motivation. Genders differences were found for career motivation in medicine, self-efficacy in dentistry, and intrinsic motivation, self-determination and grade motivation in pharmacy. Career motivation and self-efficacy components correlated with final performance in histology of the students corresponding to the three curricula. Our results show that the overall motivational profile for learning histology differs among medical, dentistry and pharmacy students. This finding is potentially useful to foster their learning process, because if they are metacognitively aware of their motivation they will be better equipped to self-regulate their science-learning behavior in histology. This information could be useful for instructors and education policy makers to enhance curricula not only on the cognitive component of learning but also to integrate students' levels and types of motivation into the processes of planning, delivery and evaluation of medical education.

  2. Motivational component profiles in university students learning histology: a comparative study between genders and different health science curricula

    Science.gov (United States)

    2014-01-01

    Background The students’ motivation to learn basic sciences in health science curricula is poorly understood. The purpose of this study was to investigate the influence of different components of motivation (intrinsic motivation, self-determination, self-efficacy and extrinsic -career and grade- motivation) on learning human histology in health science curricula and their relationship with the final performance of the students in histology. Methods Glynn Science Motivation Questionnaire II was used to compare students’ motivation components to learn histology in 367 first-year male and female undergraduate students enrolled in medical, dentistry and pharmacy degree programs. Results For intrinsic motivation, career motivation and self-efficacy, the highest values corresponded to medical students, whereas dentistry students showed the highest values for self-determination and grade motivation. Genders differences were found for career motivation in medicine, self-efficacy in dentistry, and intrinsic motivation, self-determination and grade motivation in pharmacy. Career motivation and self-efficacy components correlated with final performance in histology of the students corresponding to the three curricula. Conclusions Our results show that the overall motivational profile for learning histology differs among medical, dentistry and pharmacy students. This finding is potentially useful to foster their learning process, because if they are metacognitively aware of their motivation they will be better equipped to self-regulate their science-learning behavior in histology. This information could be useful for instructors and education policy makers to enhance curricula not only on the cognitive component of learning but also to integrate students’ levels and types of motivation into the processes of planning, delivery and evaluation of medical education. PMID:24612878

  3. Linearizing feedforward/feedback attitude control

    Science.gov (United States)

    Paielli, Russell A.; Bach, Ralph E.

    1991-01-01

    An approach to attitude control theory is introduced in which a linear form is postulated for the closed-loop rotation error dynamics, then the exact control law required to realize it is derived. The nonminimal (four-component) quaternion form is used to attitude because it is globally nonsingular, but the minimal (three-component) quaternion form is used for attitude error because it has no nonlinear constraints to prevent the rotational error dynamics from being linearized, and the definition of the attitude error is based on quaternion algebra. This approach produces an attitude control law that linearizes the closed-loop rotational error dynamics exactly, without any attitude singularities, even if the control errors become large.

  4. Feedforward compensation control of rotor imbalance for high-speed magnetically suspended centrifugal compressors using a novel adaptive notch filter

    Science.gov (United States)

    Zheng, Shiqiang; Feng, Rui

    2016-03-01

    This paper introduces a feedforward control strategy combined with a novel adaptive notch filter to solve the problem of rotor imbalance in high-speed Magnetically Suspended Centrifugal Compressors (MSCCs). Unbalance vibration force of rotor in MSCC is mainly composed of current stiffness force and displacement stiffness force. In this paper, the mathematical model of the unbalance vibration with the proportional-integral-derivative (PID) control laws is presented. In order to reduce the unbalance vibration, a novel adaptive notch filter is proposed to identify the synchronous frequency displacement of the rotor as a compensation signal to eliminate the current stiffness force. In addition, a feedforward channel from position component to control output is introduced to compensate displacement stiffness force to achieve a better performance. A simplified inverse model of power amplifier is included in the feedforward channel to reject the degrade performance caused by its low-pass characteristic. Simulation and experimental results on a MSCC demonstrate a significant effect on the synchronous vibration suppression of the magnetically suspended rotor at a high speed.

  5. TENCompetence Learning Design Toolkit, Runtime component, ccsi_v3_2_10c_v1_4

    NARCIS (Netherlands)

    Sharples, Paul; Popat, Kris; Llobet, Lau; Santos, Patricia; Hernández-Leo, Davinia; Miao, Yongwu; Griffiths, David; Beauvoir, Phillip

    2010-01-01

    Sharples, P., Popat, K., Llobet, L., Santos, P., Hernandez-Leo, D., Miao, Y., Griffiths, D. & Beauvoir, P. (2009) TENCompetence Learning Design Toolkit, Runtime component, ccsi_v3_2_10c_v1_4 This release is composed of three files corresponding to CopperCore Service Integration (CCSI) v3.2-10cv1.4,

  6. Design Of Combined Stochastic Feedforward/Feedback Control

    Science.gov (United States)

    Halyo, Nesim

    1989-01-01

    Methodology accommodates variety of control structures and design techniques. In methodology for combined stochastic feedforward/feedback control, main objectives of feedforward and feedback control laws seen clearly. Inclusion of error-integral feedback, dynamic compensation, rate-command control structure, and like integral element of methodology. Another advantage of methodology flexibility to develop variety of techniques for design of feedback control with arbitrary structures to obtain feedback controller: includes stochastic output feedback, multiconfiguration control, decentralized control, or frequency and classical control methods. Control modes of system include capture and tracking of localizer and glideslope, crab, decrab, and flare. By use of recommended incremental implementation, control laws simulated on digital computer and connected with nonlinear digital simulation of aircraft and its systems.

  7. Feedforward/feedback control synthesis for performance and robustness

    Science.gov (United States)

    Wie, Bong; Liu, Qiang

    1990-01-01

    Both feedforward and feedback control approaches for uncertain dynamical systems are investigated. The control design objective is to achieve a fast settling time (high performance) and robustness (insensitivity) to plant modeling uncertainty. Preshapong of an ideal, time-optimal control input using a 'tapped-delay' filter is shown to provide a rapid maneuver with robust performance. A robust, non-minimum-phase feedback controller is synthesized with particular emphasis on its proper implementation for a non-zero set-point control problem. The proposed feedforward/feedback control approach is robust for a certain class of uncertain dynamical systems, since the control input command computed for a given desired output does not depend on the plant parameters.

  8. Efficient Feedforward Linearization Technique Using Genetic Algorithms for OFDM Systems

    Directory of Open Access Journals (Sweden)

    García Paloma

    2010-01-01

    Full Text Available Feedforward is a linearization method that simultaneously offers wide bandwidth and good intermodulation distortion suppression; so it is a good choice for Orthogonal Frequency Division Multiplexing (OFDM systems. Feedforward structure consists of two loops, being necessary an accurate adjustment between them along the time, and when temperature, environmental, or operating changes are produced. Amplitude and phase imbalances of the circuit elements in both loops produce mismatched effects that lead to degrade its performance. A method is proposed to compensate these mismatches, introducing two complex coefficients calculated by means of a genetic algorithm. A full study is carried out to choose the optimal parameters of the genetic algorithm applied to wideband systems based on OFDM technologies, which are very sensitive to nonlinear distortions. The method functionality has been verified by means of simulation.

  9. Natural Language Processing with Small Feed-Forward Networks

    OpenAIRE

    Botha, Jan A.; Pitler, Emily; Ma, Ji; Bakalov, Anton; Salcianu, Alex; Weiss, David; McDonald, Ryan; Petrov, Slav

    2017-01-01

    We show that small and shallow feed-forward neural networks can achieve near state-of-the-art results on a range of unstructured and structured language processing tasks while being considerably cheaper in memory and computational requirements than deep recurrent models. Motivated by resource-constrained environments like mobile phones, we showcase simple techniques for obtaining such small neural network models, and investigate different tradeoffs when deciding how to allocate a small memory...

  10. Biomechanical constraints on the feedforward regulation of endpoint stiffness.

    Science.gov (United States)

    Hu, Xiao; Murray, Wendy M; Perreault, Eric J

    2012-10-01

    Although many daily tasks tend to destabilize arm posture, it is still possible to have stable interactions with the environment by regulating the multijoint mechanics of the arm in a task-appropriate manner. For postural tasks, this regulation involves the appropriate control of endpoint stiffness, which represents the stiffness of the arm at the hand. Although experimental studies have been used to evaluate endpoint stiffness control, including the orientation of maximal stiffness, the underlying neural strategies remain unknown. Specifically, the relative importance of feedforward and feedback mechanisms has yet to be determined due to the difficulty separately identifying the contributions of these mechanisms in human experiments. This study used a previously validated three-dimensional musculoskeletal model of the arm to quantify the degree to which the orientation of maximal endpoint stiffness could be changed using only steady-state muscle activations, used to represent feedforward motor commands. Our hypothesis was that the feedforward control of endpoint stiffness orientation would be significantly constrained by the biomechanical properties of the musculoskeletal system. Our results supported this hypothesis, demonstrating substantial biomechanical constraints on the ability to regulate endpoint stiffness throughout the workspace. The ability to regulate stiffness orientation was further constrained by additional task requirements, such as the need to support the arm against gravity or exert forces on the environment. Together, these results bound the degree to which slowly varying feedforward motor commands can be used to regulate the orientation of maximum arm stiffness and provide a context for better understanding conditions in which feedback control may be needed.

  11. Fuzzy PID Feedback Control of Piezoelectric Actuator with Feedforward Compensation

    OpenAIRE

    Ziqiang Chi; Minping Jia; Qingsong Xu

    2014-01-01

    Piezoelectric actuator is widely used in the field of micro/nanopositioning. However, piezoelectric hysteresis introduces nonlinearity to the system, which is the major obstacle to achieve a precise positioning. In this paper, the Preisach model is employed to describe the hysteresis characteristic of piezoelectric actuator and an inverse Preisach model is developed to construct a feedforward controller. Considering that the analytical expression of inverse Preisach model is difficult to deri...

  12. A novel feedforward compensation canceling input filter-regulator interaction

    Science.gov (United States)

    Kelkar, S. S.; Lee, F. C.

    1983-01-01

    The interaction between the input and the control loop of switching regulators often results in deterimental effects, such as loop instability, degradation of transient response, and audiosusceptibility, etc. The concept of pole-zero cancelation is employed to mitigate some of these detrimental effects and is implemented using a novel feedforward loop, in addition to existing feedback loops of a buck regulator. Experimental results are presented which show excellent correlation with theory.

  13. Designing Robustness to Temperature in a Feedforward Loop Circuit

    OpenAIRE

    Sen, Shaunak; Kim, Jongmin; Murray, Richard M.

    2013-01-01

    Incoherent feedforward loops represent important biomolecular circuit elements capable of a rich set of dynamic behavior including adaptation and pulsed responses. Temperature can modulate some of these properties through its effect on the underlying reaction rate parameters. It is generally unclear how to design such a circuit where the properties are robust to variations in temperature. Here, we address this issue using a combination of tools from control and dynamical systems theory as wel...

  14. An Introduction to Feedforward Control of Electric Drives

    Directory of Open Access Journals (Sweden)

    Michal Malek

    2010-01-01

    Full Text Available The field of electric drives provides a broad spectrum of applications with different power demands, utilized motor types or different environment requirements. Lot of applications are characterized by very high demands on accuracy and dynamic properties and have attribute of servo applications. This means that they are fully subordinate to wishes of the master. This rigorous condition is fulfill (with tolerated errors mainly thanks to the feedforward utilization.

  15. Predictive Feedback and Feedforward Control for Systems with Unknown Disturbances

    Science.gov (United States)

    Juang, Jer-Nan; Eure, Kenneth W.

    1998-01-01

    Predictive feedback control has been successfully used in the regulation of plate vibrations when no reference signal is available for feedforward control. However, if a reference signal is available it may be used to enhance regulation by incorporating a feedforward path in the feedback controller. Such a controller is known as a hybrid controller. This paper presents the theory and implementation of the hybrid controller for general linear systems, in particular for structural vibration induced by acoustic noise. The generalized predictive control is extended to include a feedforward path in the multi-input multi-output case and implemented on a single-input single-output test plant to achieve plate vibration regulation. There are cases in acoustic-induce vibration where the disturbance signal is not available to be used by the hybrid controller, but a disturbance model is available. In this case the disturbance model may be used in the feedback controller to enhance performance. In practice, however, neither the disturbance signal nor the disturbance model is available. This paper presents the theory of identifying and incorporating the noise model into the feedback controller. Implementations are performed on a test plant and regulation improvements over the case where no noise model is used are demonstrated.

  16. Fuzzy PID Feedback Control of Piezoelectric Actuator with Feedforward Compensation

    Directory of Open Access Journals (Sweden)

    Ziqiang Chi

    2014-01-01

    Full Text Available Piezoelectric actuator is widely used in the field of micro/nanopositioning. However, piezoelectric hysteresis introduces nonlinearity to the system, which is the major obstacle to achieve a precise positioning. In this paper, the Preisach model is employed to describe the hysteresis characteristic of piezoelectric actuator and an inverse Preisach model is developed to construct a feedforward controller. Considering that the analytical expression of inverse Preisach model is difficult to derive and not suitable for practical application, a digital inverse model is established based on the input and output data of a piezoelectric actuator. Moreover, to mitigate the compensation error of the feedforward control, a feedback control scheme is implemented using different types of control algorithms in terms of PID control, fuzzy control, and fuzzy PID control. Extensive simulation studies are carried out using the three kinds of control systems. Comparative investigation reveals that the fuzzy PID control system with feedforward compensation is capable of providing quicker response and better control accuracy than the other two ones. It provides a promising way of precision control for piezoelectric actuator.

  17. Feed-Forward Control of Kite Power Systems

    International Nuclear Information System (INIS)

    Fechner, Uwe; Schmehl, Roland

    2014-01-01

    Kite power technology is a novel solution to harvest wind energy from altitudes that can not be reached by conventional wind turbines. The use of a lightweight but strong tether in place of an expensive tower provides an additional cost advantage, next to the higher capacity factor. This paper describes a method to estimate the wind velocity at the kite using measurement data at the kite and at the ground. Focussing on a kite power system, which is converting the traction power of a kite in a pumping mode of operation, a reel-out speed predictor is presented for use in feed-forward control of the tether reel-out speed of the winch. The results show, that the developed feedforward controller improves the force control accuracy by a factor of two compared to the previously used feedback controller. This allows to use a higher set force during the reel-out phase which in turn increases the average power output by more than 4%. Due to its straightforward implementation and low computational requirements feedforward control is considered a promising technique for the reliable and efficient operation of traction-based kite power systems

  18. Hybrid Feedforward-Feedback Noise Control Using Virtual Sensors

    Science.gov (United States)

    Bean, Jacob; Fuller, Chris; Schiller, Noah

    2016-01-01

    Several approaches to active noise control using virtual sensors are evaluated for eventual use in an active headrest. Specifically, adaptive feedforward, feedback, and hybrid control structures are compared. Each controller incorporates the traditional filtered-x least mean squares algorithm. The feedback controller is arranged in an internal model configuration to draw comparisons with standard feedforward control theory results. Simulation and experimental results are presented that illustrate each controllers ability to minimize the pressure at both physical and virtual microphone locations. The remote microphone technique is used to obtain pressure estimates at the virtual locations. It is shown that a hybrid controller offers performance benefits over the traditional feedforward and feedback controllers. Stability issues associated with feedback and hybrid controllers are also addressed. Experimental results show that 15-20 dB reduction in broadband disturbances can be achieved by minimizing the measured pressure, whereas 10-15 dB reduction is obtained when minimizing the estimated pressure at a virtual location.

  19. Incoherent feedforward control governs adaptation of activated ras in a eukaryotic chemotaxis pathway.

    Science.gov (United States)

    Takeda, Kosuke; Shao, Danying; Adler, Micha; Charest, Pascale G; Loomis, William F; Levine, Herbert; Groisman, Alex; Rappel, Wouter-Jan; Firtel, Richard A

    2012-01-03

    Adaptation in signaling systems, during which the output returns to a fixed baseline after a change in the input, often involves negative feedback loops and plays a crucial role in eukaryotic chemotaxis. We determined the dynamical response to a uniform change in chemoattractant concentration of a eukaryotic chemotaxis pathway immediately downstream from G protein-coupled receptors. The response of an activated Ras showed near-perfect adaptation, leading us to attempt to fit the results using mathematical models for the two possible simple network topologies that can provide perfect adaptation. Only the incoherent feedforward network accurately described the experimental results. This analysis revealed that adaptation in this Ras pathway is achieved through the proportional activation of upstream components and not through negative feedback loops. Furthermore, these results are consistent with a local excitation, global inhibition mechanism for gradient sensing, possibly with a Ras guanosine triphosphatase-activating protein acting as a global inhibitor.

  20. Objective Model Selection for Identifying the Human Feedforward Response in Manual Control

    OpenAIRE

    Drop, F.M.; Pool, D.M.; van Paassen, M.M.; Mulder, M.; Bülthoff, Heinrich H.

    2017-01-01

    Realistic manual control tasks typically involve predictable target signals and random disturbances. The human controller (HC) is hypothesized to use a feedforward control strategy for target-following, in addition to feedback control for disturbance-rejection. Little is known about human feedforward control, partly because common system identification methods have difficulty in identifying whether, and (if so) how, the HC applies a feedforward strategy. In this paper, an identification proce...

  1. Thalamocortical control of feed-forward inhibition in awake somatosensory 'barrel' cortex.

    OpenAIRE

    Swadlow, Harvey A

    2002-01-01

    Intracortical inhibition plays a role in shaping sensory cortical receptive fields and is mediated by both feed-forward and feedback mechanisms. Feed-forward inhibition is the faster of the two processes, being generated by inhibitory interneurons driven by monosynaptic thalamocortical (TC) input. In principle, feed-forward inhibition can prevent targeted cortical neurons from ever reaching threshold when TC input is weak. To do so, however, inhibitory interneurons must respond to TC input at...

  2. Fruit Classification by Wavelet-Entropy and Feedforward Neural Network Trained by Fitness-Scaled Chaotic ABC and Biogeography-Based Optimization

    Directory of Open Access Journals (Sweden)

    Shuihua Wang

    2015-08-01

    Full Text Available Fruit classification is quite difficult because of the various categories and similar shapes and features of fruit. In this work, we proposed two novel machine-learning based classification methods. The developed system consists of wavelet entropy (WE, principal component analysis (PCA, feedforward neural network (FNN trained by fitness-scaled chaotic artificial bee colony (FSCABC and biogeography-based optimization (BBO, respectively. The K-fold stratified cross validation (SCV was utilized for statistical analysis. The classification performance for 1653 fruit images from 18 categories showed that the proposed “WE + PCA + FSCABC-FNN” and “WE + PCA + BBO-FNN” methods achieve the same accuracy of 89.5%, higher than state-of-the-art approaches: “(CH + MP + US + PCA + GA-FNN ” of 84.8%, “(CH + MP + US + PCA + PSO-FNN” of 87.9%, “(CH + MP + US + PCA + ABC-FNN” of 85.4%, “(CH + MP + US + PCA + kSVM” of 88.2%, and “(CH + MP + US + PCA + FSCABC-FNN” of 89.1%. Besides, our methods used only 12 features, less than the number of features used by other methods. Therefore, the proposed methods are effective for fruit classification.

  3. GABA(B) receptor modulation of feedforward inhibition through hippocampal neurogliaform cells.

    Science.gov (United States)

    Price, Christopher J; Scott, Ricardo; Rusakov, Dmitri A; Capogna, Marco

    2008-07-02

    Feedforward inhibition of neurons is a fundamental component of information flow control in the brain. We studied the roles played by neurogliaform cells (NGFCs) of stratum lacunosum moleculare of the hippocampus in providing feedforward inhibition to CA1 pyramidal cells. We recorded from synaptically coupled pairs of anatomically identified NGFCs and CA1 pyramidal cells and found that, strikingly, a single presynaptic action potential evoked a biphasic unitary IPSC (uIPSC), consisting of two distinct components mediated by GABA(A) and GABA(B) receptors. A GABA(B) receptor-mediated unitary response has not previously been observed in hippocampal excitatory neurons. The decay of the GABA(A) receptor-mediated response was slow (time constant = 50 ms), and was tightly regulated by presynaptic GABA(B) receptors. Surprisingly, the GABA(B) receptor ligands baclofen and (2S)-3-{[(1S)-1-(3,4-dichlorophenyl)ethyl]amino-2-hydroxypropyl}(phenylmethyl)phosphinic acid (CGP55845), while affecting the NGFC-mediated uIPSCs, had no effect on action potential-evoked presynaptic Ca2+ signals monitored in individual axonal boutons of NGFCs with two-photon microscopy. In contrast, baclofen clearly depressed presynaptic Ca2+ transients in non-NGF interneurons. Changes in extracellular Ca2+ concentration that mimicked the effects of baclofen or CGP55845 on uIPSCs significantly altered presynaptic Ca2+ transients. Electrophysiological data suggest that GABA(B) receptors expressed by NGFCs contribute to the dynamic control of the excitatory input to CA1 pyramidal neurons from the temporoammonic path. The NGFC-CA1 pyramidal cell connection therefore provides a unique and subtle mechanism to shape the integration time domain for signals arriving via a major excitatory input to CA1 pyramidal cells.

  4. Grid-Voltage-Feedforward Active Damping for Grid-Connected Inverter with LCL Filter

    DEFF Research Database (Denmark)

    Lu, Minghui; Wang, Xiongfei; Blaabjerg, Frede

    2016-01-01

    For the grid-connected voltage source inverters, the feedforward scheme of grid voltage is commonly adopted to mitigate the current distortion caused by grid background voltages harmonics. This paper investigates the grid-voltage-feedforward active damping for grid connected inverter with LCL...... filter. It reveals that proportional feedforward control can not only fulfill the mitigation of grid disturbance, but also offer damping effects on the LCL filter resonance. Digital delays are intrinsic to digital controlled inverters; with these delays, the feedforward control can be equivalent...

  5. Blended Learning: How Teachers Balance the Blend of Online and Classroom Components

    Science.gov (United States)

    Jeffrey, Lynn M.; Milne, John; Suddaby, Gordon

    2014-01-01

    Despite teacher resistance to the use of technology in education, blended learning has increased rapidly, driven by evidence of its advantages over either online or classroom teaching alone. However, blended learning courses still fail to maximize the benefits this format offers. Much research has been conducted on various aspects of this problem,…

  6. Computer-Aided College Algebra: Learning Components that Students Find Beneficial

    Science.gov (United States)

    Aichele, Douglas B.; Francisco, Cynthia; Utley, Juliana; Wescoatt, Benjamin

    2011-01-01

    A mixed-method study was conducted during the Fall 2008 semester to better understand the experiences of students participating in computer-aided instruction of College Algebra using the software MyMathLab. The learning environment included a computer learning system for the majority of the instruction, a support system via focus groups (weekly…

  7. CRITICAL COMPONENTS OF ONLINE LEARNING READINESS AND THEIR RELATIONSHIPS WITH LEARNER ACHIEVEMENT

    Directory of Open Access Journals (Sweden)

    Harun CIGDEM

    2016-04-01

    Full Text Available This study aimed to examine the relationship between certain factors of online learning readiness and learners’ end-of-course achievements. The study was conducted at a two-year post-secondary Turkish military school within the scope of the course titled Computer Literacy, which was designed and implemented in a blended way. The data were collected from 155 post-secondary military students through an online questionnaire. Three sub-scales of Hung et al.’s Online Learning Readiness Scale were used to collect the data during the first two weeks of the course. Descriptive and inferential statistics, such as Pearson correlation coefficients and linear regression analyses were performed to analyze the data. The descriptive results of the study indicated that students’ motivation for online learning was higher than both their computer/Internet self-efficacy and their orientations to self-directed learning. The inferential results revealed that the students’ end-of-course grades had significantly positive relationships with their computer/Internet self-efficacy and self-directed learning orientations. Finally, the students’ self-direction towards online learning appeared to be the strongest predictor of their achievements within the course; whereas computer/Internet self-efficacy and motivation for learning did not predict the learner achievement significantly.

  8. Hybrid feedback feedforward: An efficient design of adaptive neural network control.

    Science.gov (United States)

    Pan, Yongping; Liu, Yiqi; Xu, Bin; Yu, Haoyong

    2016-04-01

    This paper presents an efficient hybrid feedback feedforward (HFF) adaptive approximation-based control (AAC) strategy for a class of uncertain Euler-Lagrange systems. The control structure includes a proportional-derivative (PD) control term in the feedback loop and a radial-basis-function (RBF) neural network (NN) in the feedforward loop, which mimics the human motor learning control mechanism. At the presence of discontinuous friction, a sigmoid-jump-function NN is incorporated to improve control performance. The major difference of the proposed HFF-AAC design from the traditional feedback AAC (FB-AAC) design is that only desired outputs, rather than both tracking errors and desired outputs, are applied as RBF-NN inputs. Yet, such a slight modification leads to several attractive properties of HFF-AAC, including the convenient choice of an approximation domain, the decrease of the number of RBF-NN inputs, and semiglobal practical asymptotic stability dominated by control gains. Compared with previous HFF-AAC approaches, the proposed approach possesses the following two distinctive features: (i) all above attractive properties are achieved by a much simpler control scheme; (ii) the bounds of plant uncertainties are not required to be known. Consequently, the proposed approach guarantees a minimum configuration of the control structure and a minimum requirement of plant knowledge for the AAC design, which leads to a sharp decrease of implementation cost in terms of hardware selection, algorithm realization and system debugging. Simulation results have demonstrated that the proposed HFF-AAC can perform as good as or even better than the traditional FB-AAC under much simpler control synthesis and much lower computational cost. Copyright © 2015 Elsevier Ltd. All rights reserved.

  9. Is LabTutor a helpful component of the blended learning approach to biosciences?

    Science.gov (United States)

    Swift, Amelia; Efstathiou, Nikolaos; Lameu, Paula

    2016-09-01

    To evaluate the use of LabTutor (a physiological data capture and e-learning package) in bioscience education for student nurses. Knowledge of biosciences is important for nurses the world over, who have to monitor and assess their patient's clinical condition, and interpret that information to determine the most appropriate course of action. Nursing students have long been known to find acquiring useable bioscience knowledge challenging. Blended learning strategies are common in bioscience teaching to address the difficulties students have. Student nurses have a preference for hands-on learning, small group sessions and are helped by close juxtaposition of theory and practice. An evaluation of a new teaching method using in-classroom voluntary questionnaire. A structured survey instrument including statements and visual analogue response format and open questions was given to students who participated in Labtutor sessions. The students provided feedback in about the equipment, the learning and the session itself. First year (n = 93) and third year (n = 36) students completed the evaluation forms. The majority of students were confident about the equipment and using it to learn although a few felt anxious about computer-based learning. They all found the equipment helpful as part of their bioscience education and they all enjoyed the sessions. This equipment provides a helpful way to encourage guided independent learning through practice and discovery and because each session is case study based and the relationship of the data to the patient is made clear. Our students helped to evaluate our initial use of LabTutor and found the sessions enjoyable and helpful. LabTutor provides an effective learning tool as part of a blended learning strategy for biosciences teaching. Improving bioscience knowledge will lead to a greater understanding of pathophysiology, treatments and interventions and monitoring. © 2016 John Wiley & Sons Ltd.

  10. Feedforward Coordinate Control of a Robotic Cell Injection Catheter.

    Science.gov (United States)

    Cheng, Weyland; Law, Peter K

    2017-08-01

    Remote and robotically actuated catheters are the stepping-stones toward autonomous catheters, where complex intravascular procedures may be performed with minimal intervention from a physician. This article proposes a concept for the positional, feedforward control of a robotically actuated cell injection catheter used for the injection of myogenic or undifferentiated stem cells into the myocardial infarct boundary zones of the left ventricle. The prototype for the catheter system was built upon a needle-based catheter with a single degree of deflection, a 3-D printed handle combined with actuators, and the Arduino microcontroller platform. A bench setup was used to mimic a left ventricle catheter procedure starting from the femoral artery. Using Matlab and the open-source video modeling tool Tracker, the planar coordinates ( y, z) of the catheter position were analyzed, and a feedforward control system was developed based on empirical models. Using the Student's t test with a sample size of 26, it was determined that for both the y- and z-axes, the mean discrepancy between the calibrated and theoretical coordinate values had no significant difference compared to the hypothetical value of µ = 0. The root mean square error of the calibrated coordinates also showed an 88% improvement in the z-axis and 31% improvement in the y-axis compared to the unmodified trial run. This proof of concept investigation leads to the possibility of further developing a feedfoward control system in vivo using catheters with omnidirectional deflection. Feedforward positional control allows for more flexibility in the design of an automated catheter system where problems such as systemic time delay may be a hindrance in instances requiring an immediate reaction.

  11. Feedforward and feedback inhibition in neostriatal GABAergic spiny neurons.

    Science.gov (United States)

    Tepper, James M; Wilson, Charles J; Koós, Tibor

    2008-08-01

    There are two distinct inhibitory GABAergic circuits in the neostriatum. The feedforward circuit consists of a relatively small population of GABAergic interneurons that receives excitatory input from the neocortex and exerts monosynaptic inhibition onto striatal spiny projection neurons. The feedback circuit comprises the numerous spiny projection neurons and their interconnections via local axon collaterals. This network has long been assumed to provide the majority of striatal GABAergic inhibition and to sharpen and shape striatal output through lateral inhibition, producing increased activity in the most strongly excited spiny cells at the expense of their less strongly excited neighbors. Recent results, mostly from recording experiments of synaptically connected pairs of neurons, have revealed that the two GABAergic circuits differ markedly in terms of the total number of synapses made by each, the strength of the postsynaptic response detected at the soma, the extent of presynaptic convergence and divergence and the net effect of the activation of each circuit on the postsynaptic activity of the spiny neuron. These data have revealed that the feedforward inhibition is powerful and widespread, with spiking in a single interneuron being capable of significantly delaying or even blocking the generation of spikes in a large number of postsynaptic spiny neurons. In contrast, the postsynaptic effects of spiking in a single presynaptic spiny neuron on postsynaptic spiny neurons are weak when measured at the soma, and unable to significantly affect spike timing or generation. Further, reciprocity of synaptic connections between spiny neurons is only rarely observed. These results suggest that the bulk of the fast inhibition that has the strongest effects on spiny neuron spike timing comes from the feedforward interneuronal system whereas the axon collateral feedback system acts principally at the dendrites to control local excitability as well as the overall level of

  12. Recent progresses of neural network unsupervised learning: I. Independent component analyses generalizing PCA

    Science.gov (United States)

    Szu, Harold H.

    1999-03-01

    The early vision principle of redundancy reduction of 108 sensor excitations is understandable from computer vision viewpoint toward sparse edge maps. It is only recently derived using a truly unsupervised learning paradigm of artificial neural networks (ANN). In fact, the biological vision, Hubel- Wiesel edge maps, is reproduced seeking the underlying independent components analyses (ICA) among 102 image samples by maximizing the ANN output entropy (partial)H(V)/(partial)[W] equals (partial)[W]/(partial)t. When a pair of newborn eyes or ears meet the bustling and hustling world without supervision, they seek ICA by comparing 2 sensory measurements (x1(t), x2(t))T equalsV X(t). Assuming a linear and instantaneous mixture model of the external world X(t) equals [A] S(t), where both the mixing matrix ([A] equalsV [a1, a2] of ICA vectors and the source percentages (s1(t), s2(t))T equalsV S(t) are unknown, we seek the independent sources approximately equals [I] where the approximated sign indicates that higher order statistics (HOS) may not be trivial. Without a teacher, the ANN weight matrix [W] equalsV [w1, w2] adjusts the outputs V(t) equals tanh([W]X(t)) approximately equals [W]X(t) until no desired outputs except the (Gaussian) 'garbage' (neither YES '1' nor NO '-1' but at linear may-be range 'origin 0') defined by Gaussian covariance G equals [I] equals [W][A] the internal knowledge representation [W], as the inverse of the external world matrix [A]-1. To unify IC, PCA, ANN & HOS theories since 1991 (advanced by Jutten & Herault, Comon, Oja, Bell-Sejnowski, Amari-Cichocki, Cardoso), the LYAPONOV function L(v1,...,vn, w1,...wn,) equals E(v1,...,vn) - H(w1,...wn) is constructed as the HELMHOTZ free energy to prove both convergences of supervised energy E and unsupervised entropy H learning. Consequently, rather using the faithful but dumb computer: 'GARBAGE-IN, GARBAGE-OUT,' the smarter neurocomputer will be equipped with an unsupervised learning that extracts

  13. On spatial spillover in feedforward and feedback noise control

    Science.gov (United States)

    Xie, Antai; Bernstein, Dennis

    2017-03-01

    Active feedback noise control for rejecting broadband disturbances must contend with the Bode integral constraint, which implies that suppression over some frequency range gives rise to amplification over another range at the performance microphone. This is called spectral spillover. The present paper deals with spatial spillover, which refers to the amplification of noise at locations where no microphone is located. A spatial spillover function is defined, which is valid for both feedforward and feedback control with scalar and vector control inputs. This function is numerically analyzed and measured experimentally. Obstructions are introduced in the acoustic space to investigate their effect on spatial spillover.

  14. Adaptive training of feedforward neural networks by Kalman filtering

    International Nuclear Information System (INIS)

    Ciftcioglu, Oe.

    1995-02-01

    Adaptive training of feedforward neural networks by Kalman filtering is described. Adaptive training is particularly important in estimation by neural network in real-time environmental where the trained network is used for system estimation while the network is further trained by means of the information provided by the experienced/exercised ongoing operation. As result of this, neural network adapts itself to a changing environment to perform its mission without recourse to re-training. The performance of the training method is demonstrated by means of actual process signals from a nuclear power plant. (orig.)

  15. Combined Effects of Feedforward Inhibition and Excitation in Thalamocortical Circuit on the Transitions of Epileptic Seizures

    Science.gov (United States)

    Fan, Denggui; Duan, Lixia; Wang, Qian; Luan, Guoming

    2017-01-01

    The mechanisms underlying electrophysiologically observed two-way transitions between absence and tonic-clonic epileptic seizures in cerebral cortex remain unknown. The interplay within thalamocortical network is believed to give rise to these epileptic multiple modes of activity and transitions between them. In particular, it is thought that in some areas of cortex there exists feedforward inhibition from specific relay nucleus of thalamus (TC) to inhibitory neuronal population (IN) which has even more stronger functions on cortical activities than the known feedforward excitation from TC to excitatory neuronal population (EX). Inspired by this, we proposed a modified computational model by introducing feedforward inhibitory connectivity within thalamocortical circuit, to systematically investigate the combined effects of feedforward inhibition and excitation on transitions of epileptic seizures. We first found that the feedforward excitation can induce the transition from tonic oscillation to spike and wave discharges (SWD) in cortex, i.e., the epileptic tonic-absence seizures, with the fixed weak feedforward inhibition. Thereinto, the phase of absence seizures corresponding to strong feedforward excitation can be further transformed into the clonic oscillations with the increasing of feedforward inhibition, representing the epileptic absence-clonic seizures. We also observed the other fascinating dynamical states, such as periodic 2/3/4-spike and wave discharges, reversed SWD and clonic oscillations, as well as saturated firings. More importantly, we can identify the stable parameter regions representing the tonic-clonic oscillations and SWD discharges of epileptic seizures on the 2-D plane composed of feedforward inhibition and excitation, where the physiologically plausible transition pathways between tonic-clonic and absence seizures can be figured out. These results indicate the functional role of feedforward pathways in controlling epileptic seizures and

  16. Combined Effects of Feedforward Inhibition and Excitation in Thalamocortical Circuit on the Transitions of Epileptic Seizures

    Directory of Open Access Journals (Sweden)

    Denggui Fan

    2017-07-01

    Full Text Available The mechanisms underlying electrophysiologically observed two-way transitions between absence and tonic-clonic epileptic seizures in cerebral cortex remain unknown. The interplay within thalamocortical network is believed to give rise to these epileptic multiple modes of activity and transitions between them. In particular, it is thought that in some areas of cortex there exists feedforward inhibition from specific relay nucleus of thalamus (TC to inhibitory neuronal population (IN which has even more stronger functions on cortical activities than the known feedforward excitation from TC to excitatory neuronal population (EX. Inspired by this, we proposed a modified computational model by introducing feedforward inhibitory connectivity within thalamocortical circuit, to systematically investigate the combined effects of feedforward inhibition and excitation on transitions of epileptic seizures. We first found that the feedforward excitation can induce the transition from tonic oscillation to spike and wave discharges (SWD in cortex, i.e., the epileptic tonic-absence seizures, with the fixed weak feedforward inhibition. Thereinto, the phase of absence seizures corresponding to strong feedforward excitation can be further transformed into the clonic oscillations with the increasing of feedforward inhibition, representing the epileptic absence-clonic seizures. We also observed the other fascinating dynamical states, such as periodic 2/3/4-spike and wave discharges, reversed SWD and clonic oscillations, as well as saturated firings. More importantly, we can identify the stable parameter regions representing the tonic-clonic oscillations and SWD discharges of epileptic seizures on the 2-D plane composed of feedforward inhibition and excitation, where the physiologically plausible transition pathways between tonic-clonic and absence seizures can be figured out. These results indicate the functional role of feedforward pathways in controlling epileptic

  17. Implementing learning organization components in Ardabil Regional Water Company based on Marquardt systematic model

    OpenAIRE

    Shahram Mirzaie Daryani; Azadeh Zirak

    2015-01-01

    This main purpose of this study was to survey the implementation of learning organization characteristics based on Marquardt systematic model in Ardabil Regional Water Company. Two hundred and four staff (164 employees and 40 authorities) participated in the study. For data collection Marquardt questionnaire was used which its validity and reliability had been confirmed. The results of the data analysis showed that learning organization characteristics were used more than average level in som...

  18. A Feed-forward Geometrical Compensation and Adaptive Feedback Control Algorithm for Hydraulic Robot Manipulators

    DEFF Research Database (Denmark)

    Conrad, Finn; Zhou, Jianjun; Gabacik, Andrzej

    1998-01-01

    Invited paper presents a new control algorithm based on feed-forward geometrical compensation strategy combined with adaptive feedback control.......Invited paper presents a new control algorithm based on feed-forward geometrical compensation strategy combined with adaptive feedback control....

  19. Enhancing feedforward controller tuning via instrumental variables: with application to nanopositioning

    NARCIS (Netherlands)

    Boeren, F.A.J.; Bruijnen, D.J.H.; Oomen, T.A.E.

    2017-01-01

    Feedforward control enables high performance of a motion system. Recently, algorithms have been proposed that eliminate bias errors in tuning the parameters of a feedforward controller. The aim of this paper is to develop a new algorithm that combines unbiased parameter estimates with optimal

  20. Self-tuning MIMO disturbance feedforward control for active hard-mounted vibration isolators

    NARCIS (Netherlands)

    Beijen, M.A.; Heertjes, M.F.; Van Dijk, J.; Hakvoort, W. B.J.

    2018-01-01

    © 2017 Elsevier Ltd This paper proposes a multi-input multi-output (MIMO) disturbance feedforward controller to improve the rejection of floor vibrations in active vibration isolation systems for high-precision machinery. To minimize loss of performance due to model uncertainties, the feedforward

  1. MIMO feed-forward design in wafer scanners using a gradient approximation-based algorithm

    NARCIS (Netherlands)

    Heertjes, M.F.; Hennekens, D.W.T.; Steinbuch, M.

    2010-01-01

    An experimental demonstration is given of a data-based multi-input multi-output (MIMO) feed-forward control design applied to the motion systems of a wafer scanner. Atop a nominal single-input single-output (SISO) feed-forward controller, a MIMO controller is designed having a finite impulse

  2. Reference-tracking feedforward control design for linear dynamical systems through signal decomposition

    NARCIS (Netherlands)

    Kasemsinsup, Y.; Romagnoli, R.; Heertjes, M.F.; Weiland, S.; Butler, H.

    2017-01-01

    In this work, we study a novel approach towards the reference-tracking feedforward control design for linear dynamical systems. By utilizing the superposition property and exploiting signal decomposition together with a quadratic optimization process, we obtain a feedforward design procedure for

  3. Self-tuning MIMO disturbance feedforward control for active hard-mounted vibration isolators

    NARCIS (Netherlands)

    Beijen, M.A.; Heertjes, M.F.; van Dijk, J.W.; Hakvoort, W.B.J.

    2018-01-01

    This paper proposes a multi-input multi-output (MIMO) disturbance feedforward controller to improve the rejection of floor vibrations in active vibration isolation systems for high-precision machinery. To minimize loss of performance due to model uncertainties, the feedforward controller is

  4. Self-tuning disturbance feedforward control with drift prevention for air mount systems

    NARCIS (Netherlands)

    Beijen, M.A.; Heertjes, M.F.; Butler, H.

    2015-01-01

    A MIMO disturbance feedforward control strategy is presented to isolate an industrial active vibration isolation system with air mounts from broadband floor vibrations. The feedforward controller compensates for the static damping and stiffness of the air mount suspension, leading to significant

  5. Identifying the Components of Effective Learning Environments Based on Health Students\\' Perception

    Directory of Open Access Journals (Sweden)

    Yousefi Afrashteh M

    2015-08-01

    Full Text Available Aims: Effective learning environment can lead to establish and strengthen the appropriate conditions of learning in higher education. This study aimed to identify and define the factors associated with effective learning environment in the field of health education. Participants & Methods: This qualitative study with content analysis approach was conducted in 2013. Participants were 9 graduate and 7 undergraduate students of health majors that were selected using purposive sampling method. Data were recorded by interview and were analyzed using qualitative content analysis. Findings: Analysis of the data revealed 4 themes and 13 classes active and interactive teaching (participating viewpoints of students in educational planning, engaging students in class discussions, providing practical examples to understand the content, relaxing about expressed thoughts, the possibility of constructive criticism master plan of activities and according to the conditions and individual differences between students, Joyful atmosphere (academic motivation, the joy of learning and attendance, a sense of acceptance and respect from teachers and classroom dynamics and vitality and fatigue, relation of courses with professional needs (knowledge of the needs of the job in training course content and related training to the needs of job opportunities and professors’ scientific and power and expert (expertise and scientific capabilities in the field of teaching. Conclusion: 4 major themes and their characteristics can help to organize the learning environment in medical education.

  6. Anticipatory synergy adjustments reflect individual performance of feedforward force control.

    Science.gov (United States)

    Togo, Shunta; Imamizu, Hiroshi

    2016-10-06

    We grasp and dexterously manipulate an object through multi-digit synergy. In the framework of the uncontrolled manifold (UCM) hypothesis, multi-digit synergy is defined as the coordinated control mechanism of fingers to stabilize variable important for task success, e.g., total force. Previous studies reported anticipatory synergy adjustments (ASAs) that correspond to a drop of the synergy index before a quick change of the total force. The present study compared ASA's properties with individual performances of feedforward force control to investigate a relationship of those. Subjects performed a total finger force production task that consisted of a phase in which subjects tracked target line with visual information and a phase in which subjects produced total force pulse without visual information. We quantified their multi-digit synergy through UCM analysis and observed significant ASAs before producing total force pulse. The time of the ASA initiation and the magnitude of the drop of the synergy index were significantly correlated with the error of force pulse, but not with the tracking error. Almost all subjects showed a significant increase of the variance that affected the total force. Our study directly showed that ASA reflects the individual performance of feedforward force control independently of target-tracking performance and suggests that the multi-digit synergy was weakened to adjust the multi-digit movements based on a prediction error so as to reduce the future error. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  7. A Robust Feedforward Model of the Olfactory System.

    Directory of Open Access Journals (Sweden)

    Yilun Zhang

    2016-04-01

    Full Text Available Most natural odors have sparse molecular composition. This makes the principles of compressed sensing potentially relevant to the structure of the olfactory code. Yet, the largely feedforward organization of the olfactory system precludes reconstruction using standard compressed sensing algorithms. To resolve this problem, recent theoretical work has shown that signal reconstruction could take place as a result of a low dimensional dynamical system converging to one of its attractor states. However, the dynamical aspects of optimization slowed down odor recognition and were also found to be susceptible to noise. Here we describe a feedforward model of the olfactory system that achieves both strong compression and fast reconstruction that is also robust to noise. A key feature of the proposed model is a specific relationship between how odors are represented at the glomeruli stage, which corresponds to a compression, and the connections from glomeruli to third-order neurons (neurons in the olfactory cortex of vertebrates or Kenyon cells in the mushroom body of insects, which in the model corresponds to reconstruction. We show that should this specific relationship hold true, the reconstruction will be both fast and robust to noise, and in particular to the false activation of glomeruli. The predicted connectivity rate from glomeruli to third-order neurons can be tested experimentally.

  8. Implementing learning organization components in Ardabil Regional Water Company based on Marquardt systematic model

    Directory of Open Access Journals (Sweden)

    Shahram Mirzaie Daryani

    2015-09-01

    Full Text Available This main purpose of this study was to survey the implementation of learning organization characteristics based on Marquardt systematic model in Ardabil Regional Water Company. Two hundred and four staff (164 employees and 40 authorities participated in the study. For data collection Marquardt questionnaire was used which its validity and reliability had been confirmed. The results of the data analysis showed that learning organization characteristics were used more than average level in some subsystems of Marquardt model and there was a significant difference between current position and excellent position based on learning organization characteristic application. The results of this study can be used to improve work processes of organizations and institutions.

  9. Critical thinking as a self-regulatory process component in teaching and learning.

    Science.gov (United States)

    Phan, Huy P

    2010-05-01

    This article presents a theoretically grounded model of critical thinking and self-regulation in the context of teaching and learning. Critical thinking, deriving from an educational psychology perspective is a complex process of reflection that helps individuals become more analytical in their thinking and professional development. My conceptualisation in this discussion paper argues that both theoretical orientations (critical thinking and self-regulation) operate in a dynamic interactive system of teaching and learning. My argument, based on existing research evidence, suggests two important points: (i) critical thinking acts as another cognitive strategy of self-regulation that learners use in their learning, and (ii) critical thinking may be a product of various antecedents such as different self-regulatory strategies.

  10. Estimating the implicit component of visuomotor rotation learning by constraining movement preparation time.

    Science.gov (United States)

    Leow, Li-Ann; Gunn, Reece; Marinovic, Welber; Carroll, Timothy J

    2017-08-01

    When sensory feedback is perturbed, accurate movement is restored by a combination of implicit processes and deliberate reaiming to strategically compensate for errors. Here, we directly compare two methods used previously to dissociate implicit from explicit learning on a trial-by-trial basis: 1 ) asking participants to report the direction that they aim their movements, and contrasting this with the directions of the target and the movement that they actually produce, and 2 ) manipulating movement preparation time. By instructing participants to reaim without a sensory perturbation, we show that reaiming is possible even with the shortest possible preparation times, particularly when targets are narrowly distributed. Nonetheless, reaiming is effortful and comes at the cost of increased variability, so we tested whether constraining preparation time is sufficient to suppress strategic reaiming during adaptation to visuomotor rotation with a broad target distribution. The rate and extent of error reduction under preparation time constraints were similar to estimates of implicit learning obtained from self-report without time pressure, suggesting that participants chose not to apply a reaiming strategy to correct visual errors under time pressure. Surprisingly, participants who reported aiming directions showed less implicit learning according to an alternative measure, obtained during trials performed without visual feedback. This suggests that the process of reporting can affect the extent or persistence of implicit learning. The data extend existing evidence that restricting preparation time can suppress explicit reaiming and provide an estimate of implicit visuomotor rotation learning that does not require participants to report their aiming directions. NEW & NOTEWORTHY During sensorimotor adaptation, implicit error-driven learning can be isolated from explicit strategy-driven reaiming by subtracting self-reported aiming directions from movement directions, or

  11. A Layered Component-Based Architecture of a Virtual Learning Environment

    NARCIS (Netherlands)

    Avgeriou, Paris; Retalis, Simos; Skordalakis, Manolis; Psaromiligos, Yiannis

    2001-01-01

    There exists an urgent demand on defining architectures for Virtual Learning Environments (VLEs), so that high-level frameworks for understanding these systems can be discovered, portability, interoperability and reusability can be achieved and adaptability over time can be accomplished. In this

  12. Motivational and emotional components affecting male's and female's self-regulated learning

    NARCIS (Netherlands)

    Minnaert, A

    1999-01-01

    The relationship between self-referenced feelings and cognitions and self-regulated learning has become an important area of research. But to what extent can differences in self-regulation be explained by differences in motivation and emotion? And how facilitating or debilitating is the effect of

  13. Evaluating the Cooperative Component in Cooperative Learning: A Quasi-Experimental Study

    Science.gov (United States)

    Emerson, Tisha L. N.; English, Linda K.; McGoldrick, KimMarie

    2015-01-01

    In this study, the authors employed a quasi-experimental research design to examine the efficacy of a cooperative learning pedagogy (i.e., think-pair-share exercises) integrated into sections of microeconomic principles. Materials, exercises, and assessment instruments for all study sections are identical except for the nature of the…

  14. Affective Learning and Personal Information Management: Essential Components of Information Literacy

    Science.gov (United States)

    Cahoy, Ellysa Stern

    2013-01-01

    "Affective competence," managing the feelings and emotions that students encounter throughout the content creation/research process, is essential to academic success. Just as it is crucial for students to acquire core literacies, it is essential that they learn how to manage the anxieties and emotions that will emerge throughout all…

  15. Facilitative Components of Collaborative Learning: A Review of Nine Health Research Networks.

    Science.gov (United States)

    Leroy, Lisa; Rittner, Jessica Levin; Johnson, Karin E; Gerteis, Jessie; Miller, Therese

    2017-02-01

    Collaborative research networks are increasingly used as an effective mechanism for accelerating knowledge transfer into policy and practice. This paper explored the characteristics and collaborative learning approaches of nine health research networks. Semi-structured interviews with representatives from eight diverse US health services research networks conducted between November 2012 and January 2013 and program evaluation data from a ninth. The qualitative analysis assessed each network's purpose, duration, funding sources, governance structure, methods used to foster collaboration, and barriers and facilitators to collaborative learning. The authors reviewed detailed notes from the interviews to distill salient themes. Face-to-face meetings, intentional facilitation and communication, shared vision, trust among members and willingness to work together were key facilitators of collaborative learning. Competing priorities for members, limited funding and lack of long-term support and geographic dispersion were the main barriers to coordination and collaboration across research network members. The findings illustrate the importance of collaborative learning in research networks and the challenges to evaluating the success of research network functionality. Conducting readiness assessments and developing process and outcome evaluation metrics will advance the design and show the impact of collaborative research networks. Copyright © 2017 Longwoods Publishing.

  16. Enhanced Learning through Design Problems--Teaching a Components-Based Course through Design

    Science.gov (United States)

    Jensen, Bogi Bech; Hogberg, Stig; Jensen, Frida av Flotum; Mijatovic, Nenad

    2012-01-01

    This paper describes a teaching method used in an electrical machines course, where the students learn about electrical machines by designing them. The aim of the course is not to teach design, albeit this is a side product, but rather to teach the fundamentals and the function of electrical machines through design. The teaching method is…

  17. Large-scale assessment of olfactory preferences and learning in Drosophila melanogaster: behavioral and genetic components

    Directory of Open Access Journals (Sweden)

    Elisabetta Versace

    2015-09-01

    Full Text Available In the Evolve and Resequence method (E&R, experimental evolution and genomics are combined to investigate evolutionary dynamics and the genotype-phenotype link. As other genomic approaches, this methods requires many replicates with large population sizes, which imposes severe restrictions on the analysis of behavioral phenotypes. Aiming to use E&R for investigating the evolution of behavior in Drosophila, we have developed a simple and effective method to assess spontaneous olfactory preferences and learning in large samples of fruit flies using a T-maze. We tested this procedure on (a a large wild-caught population and (b 11 isofemale lines of Drosophila melanogaster. Compared to previous methods, this procedure reduces the environmental noise and allows for the analysis of large population samples. Consistent with previous results, we show that flies have a preference for orange vs. apple odor. With our procedure wild-derived flies exhibit olfactory learning in the absence of previous laboratory selection. Furthermore, we find genetic differences in the olfactory learning with relatively high heritability. We propose this large-scale method as an effective tool for E&R and genome-wide association studies on olfactory preferences and learning.

  18. Positioning the Learning Asset Portfolio as a Key Component in an Organization's Enterprise Risk Management Strategy

    Science.gov (United States)

    McAliney, Peter J.

    2009-01-01

    This article presents a process for valuing a portfolio of learning assets used by line executives across industries to value traditional business assets. Embedded within the context of enterprise risk management, this strategic asset allocation process is presented step by step, providing readers the operational considerations to implement this…

  19. Joint input shaping and feedforward for point-to-point motion : automated tuning for an industrial nanopositioning system

    NARCIS (Netherlands)

    Boeren, F.A.J.; Bruijnen, D.J.H.; Dijk, van N.J.M.; Oomen, T.A.E.

    2014-01-01

    Feedforward control can effectively compensate for the servo error induced by the reference signal if it is tuned appropriately. This paper aims to introduce a new joint input shaping and feedforward parametrization in iterative feedforward control. Such a parametrization has the potential to

  20. When Optimal Feedback Control Is Not Enough: Feedforward Strategies Are Required for Optimal Control with Active Sensing.

    Directory of Open Access Journals (Sweden)

    Sang-Hoon Yeo

    2016-12-01

    Full Text Available Movement planning is thought to be primarily determined by motor costs such as inaccuracy and effort. Solving for the optimal plan that minimizes these costs typically leads to specifying a time-varying feedback controller which both generates the movement and can optimally correct for errors that arise within a movement. However, the quality of the sensory feedback during a movement can depend substantially on the generated movement. We show that by incorporating such state-dependent sensory feedback, the optimal solution incorporates active sensing and is no longer a pure feedback process but includes a significant feedforward component. To examine whether people take into account such state-dependency in sensory feedback we asked people to make movements in which we controlled the reliability of sensory feedback. We made the visibility of the hand state-dependent, such that the visibility was proportional to the component of hand velocity in a particular direction. Subjects gradually adapted to such a sensory perturbation by making curved hand movements. In particular, they appeared to control the late visibility of the movement matching predictions of the optimal controller with state-dependent sensory noise. Our results show that trajectory planning is not only sensitive to motor costs but takes sensory costs into account and argues for optimal control of movement in which feedforward commands can play a significant role.

  1. When Optimal Feedback Control Is Not Enough: Feedforward Strategies Are Required for Optimal Control with Active Sensing.

    Science.gov (United States)

    Yeo, Sang-Hoon; Franklin, David W; Wolpert, Daniel M

    2016-12-01

    Movement planning is thought to be primarily determined by motor costs such as inaccuracy and effort. Solving for the optimal plan that minimizes these costs typically leads to specifying a time-varying feedback controller which both generates the movement and can optimally correct for errors that arise within a movement. However, the quality of the sensory feedback during a movement can depend substantially on the generated movement. We show that by incorporating such state-dependent sensory feedback, the optimal solution incorporates active sensing and is no longer a pure feedback process but includes a significant feedforward component. To examine whether people take into account such state-dependency in sensory feedback we asked people to make movements in which we controlled the reliability of sensory feedback. We made the visibility of the hand state-dependent, such that the visibility was proportional to the component of hand velocity in a particular direction. Subjects gradually adapted to such a sensory perturbation by making curved hand movements. In particular, they appeared to control the late visibility of the movement matching predictions of the optimal controller with state-dependent sensory noise. Our results show that trajectory planning is not only sensitive to motor costs but takes sensory costs into account and argues for optimal control of movement in which feedforward commands can play a significant role.

  2. A kinase-dependent feedforward loop affects CREBB stability and long term memory formation.

    Science.gov (United States)

    Lee, Pei-Tseng; Lin, Guang; Lin, Wen-Wen; Diao, Fengqiu; White, Benjamin H; Bellen, Hugo J

    2018-02-23

    In Drosophila , long-term memory (LTM) requires the cAMP-dependent transcription factor CREBB, expressed in the mushroom bodies (MB) and phosphorylated by PKA. To identify other kinases required for memory formation, we integrated Trojan exons encoding T2A-GAL4 into genes encoding putative kinases and selected for genes expressed in MB. These lines were screened for learning/memory deficits using UAS-RNAi knockdown based on an olfactory aversive conditioning assay. We identified a novel, conserved kinase, Meng-Po ( MP , CG11221 , SBK1 in human), the loss of which severely affects 3 hr memory and 24 hr LTM, but not learning. Remarkably, memory is lost upon removal of the MP protein in adult MB but restored upon its reintroduction. Overexpression of MP in MB significantly increases LTM in wild-type flies showing that MP is a limiting factor for LTM. We show that PKA phosphorylates MP and that both proteins synergize in a feedforward loop to control CREBB levels and LTM. key words: Drosophila, Mushroom bodies, SBK1, deGradFP, T2A-GAL4, MiMIC.

  3. Irradiation of electronic components and circuits at the Portuguese Research Reactor: Lessons learned

    Energy Technology Data Exchange (ETDEWEB)

    Marques, J.G.; Ramos, A.R.; Fernandes, A.C.; Santos, J.P. [Centro de Ciencias e Tecnologias Nucleares, Instituto Superior Tecnico, Universidade de Lisboa, Estrada Nacional 10, 2695-066 Bobadela LRS (Portugal)

    2015-07-01

    The behavior of electronic components and circuits under radiation is a concern shared by the nuclear industry, the space community and the high-energy physics community. Standard commercial components are used as much as possible instead of radiation hard components, since they are easier to obtain and allow a significant reduction of costs. However, these standard components need to be tested in order to determine their radiation tolerance. The Portuguese Research Reactor (RPI) is a 1 MW pool-type reactor, operating since 1961. The irradiation of electronic components and circuits is one area where a 1 MW reactor can be competitive, since the fast neutron fluences required for testing are in most cases well below 10{sup 16} n/cm{sup 2}. A program was started in 1999 to test electronics components and circuits for the LHC facility at CERN, initially using a dedicated in-pool irradiation device and later a beam line with tailored neutron and gamma filters. Neutron filters are essential to reduce the intensity of the thermal neutron flux, which does not produce significant defects in electronic components but produces unwanted radiation from activation of contacts and packages of integrated circuits and also of the printed circuit boards. In irradiations performed within the line-of-sight of the core of a fission reactor there is simultaneous gamma radiation which complicates testing in some cases. Filters can be used to reduce its importance and separate testing with a pure gamma radiation source can contribute to clarify some irradiation results. Practice has shown the need to introduce several improvements to the procedures and facilities over the years. We will review improvements done in the following areas: - Optimization of neutron and gamma filters; - Dosimetry procedures in mixed neutron / gamma fields; - Determination of hardness parameter and 1 MeV-equivalent neutron fluence; - Temperature measurement and control during irradiation; - Follow-up of reactor

  4. An Active Learning Activity to Reinforce the Design Components of the Corticosteroids.

    Science.gov (United States)

    Slauson, Stephen R; Mandela, Prashant

    2018-02-05

    Despite the popularity of active learning applications over the past few decades, few activities have been reported for the field of medicinal chemistry. The purpose of this study is to report a new active learning activity, describe participant contributions, and examine participant performance on the assessment questions mapped to the objective covered by the activity. In this particular activity, students are asked to design two novel corticosteroids as a group (6-8 students per group) based on the design characteristics of marketed corticosteroids covered in lecture coupled with their pharmaceutics knowledge from the previous semester and then defend their design to the class through an interactive presentation model. Although class performance on the objective mapped to this material on the assessment did not reach statistical significance, use of this activity has allowed fruitful discussion of misunderstood concepts and facilitated multiple changes to the lecture presentation. As pharmacy schools continue to emphasize alternative learning pedagogies, publication of previously implemented activities demonstrating their use will help others apply similar methodologies.

  5. Design Optimization of Mechanical Components Using an Enhanced Teaching-Learning Based Optimization Algorithm with Differential Operator

    Directory of Open Access Journals (Sweden)

    B. Thamaraikannan

    2014-01-01

    Full Text Available This paper studies in detail the background and implementation of a teaching-learning based optimization (TLBO algorithm with differential operator for optimization task of a few mechanical components, which are essential for most of the mechanical engineering applications. Like most of the other heuristic techniques, TLBO is also a population-based method and uses a population of solutions to proceed to the global solution. A differential operator is incorporated into the TLBO for effective search of better solutions. To validate the effectiveness of the proposed method, three typical optimization problems are considered in this research: firstly, to optimize the weight in a belt-pulley drive, secondly, to optimize the volume in a closed coil helical spring, and finally to optimize the weight in a hollow shaft. have been demonstrated. Simulation result on the optimization (mechanical components problems reveals the ability of the proposed methodology to find better optimal solutions compared to other optimization algorithms.

  6. Adaptive Feedforward Cancellation of Sinusoidal Disturbances in Superconducting RF Cavities

    CERN Document Server

    Kandil, T H; Hartung, W; Khalil, H; Popielarski, J; Vincent, J; York, R C

    2004-01-01

    A control method, known as adaptive feedforward cancellation (AFC) is applied to damp sinusoidal disturbances due to microphonics in superconducting RF (SRF) cavities. AFC provides a method for damping internal, and external sinusoidal disturbances with known frequencies. It is preferred over other schemes because it uses rudimentary information about the frequency response at the disturbance frequencies, without the necessity of knowing an analytic model (transfer function) of the system. It estimates the magnitude and phase of the sinusoidal disturbance inputs and generates a control signal to cancel their effect. AFC, along with a frequency estimation process, is shown to be very successful in the cancellation of sinusoidal signals from different sources. The results of this research may significantly reduce the power requirements and increase the stability for lightly loaded continuous-wave SRF systems.

  7. The mechanism of synchronization in feed-forward neuronal networks

    International Nuclear Information System (INIS)

    Goedeke, S; Diesmann, M

    2008-01-01

    Synchronization in feed-forward subnetworks of the brain has been proposed to explain the precisely timed spike patterns observed in experiments. While the attractor dynamics of these networks is now well understood, the underlying single neuron mechanisms remain unexplained. Previous attempts have captured the effects of the highly fluctuating membrane potential by relating spike intensity f(U) to the instantaneous voltage U generated by the input. This article shows that f is high during the rise and low during the decay of U(t), demonstrating that the U-dot-dependence of f, not refractoriness, is essential for synchronization. Moreover, the bifurcation scenario is quantitatively described by a simple f(U,U-dot) relationship. These findings suggest f(U,U-dot) as the relevant model class for the investigation of neural synchronization phenomena in a noisy environment

  8. Protecting nonlocality of multipartite states by feed-forward control

    Science.gov (United States)

    Li, Xiao-Gang; Zou, Jian; Shao, Bin

    2018-06-01

    Nonlocality is a useful resource in quantum communication and quantum information processing. In practical quantum communication, multipartite entangled states must be distributed between different users in different places through a channel. However, the channel is usually inevitably disturbed by the environment in quantum state distribution processing and then the nonlocality of states will be weakened and even lost. In this paper, we use a feed-forward control scheme to protect the nonlocality of the Bell and GHZ states against dissipation. We find that this protection scheme is very effective, specifically, for the Bell state, we can increase the noise threshold from 0.5 to 0.98, and for GHZ state from 0.29 to 0.96. And we also find that entanglement is relatively easier to be protected than nonlocality. For our scheme, protecting entanglement is equivalent to protecting the state in the case of Bell state, while protecting nonlocality is not.

  9. Objective Model Selection for Identifying the Human Feedforward Response in Manual Control.

    Science.gov (United States)

    Drop, Frank M; Pool, Daan M; van Paassen, Marinus Rene M; Mulder, Max; Bulthoff, Heinrich H

    2018-01-01

    Realistic manual control tasks typically involve predictable target signals and random disturbances. The human controller (HC) is hypothesized to use a feedforward control strategy for target-following, in addition to feedback control for disturbance-rejection. Little is known about human feedforward control, partly because common system identification methods have difficulty in identifying whether, and (if so) how, the HC applies a feedforward strategy. In this paper, an identification procedure is presented that aims at an objective model selection for identifying the human feedforward response, using linear time-invariant autoregressive with exogenous input models. A new model selection criterion is proposed to decide on the model order (number of parameters) and the presence of feedforward in addition to feedback. For a range of typical control tasks, it is shown by means of Monte Carlo computer simulations that the classical Bayesian information criterion (BIC) leads to selecting models that contain a feedforward path from data generated by a pure feedback model: "false-positive" feedforward detection. To eliminate these false-positives, the modified BIC includes an additional penalty on model complexity. The appropriate weighting is found through computer simulations with a hypothesized HC model prior to performing a tracking experiment. Experimental human-in-the-loop data will be considered in future work. With appropriate weighting, the method correctly identifies the HC dynamics in a wide range of control tasks, without false-positive results.

  10. Effects of controlled element dynamics on human feedforward behavior in ramp-tracking tasks.

    Science.gov (United States)

    Laurense, Vincent A; Pool, Daan M; Damveld, Herman J; van Paassen, Marinus René M; Mulder, Max

    2015-02-01

    In real-life manual control tasks, human controllers are often required to follow a visible and predictable reference signal, enabling them to use feedforward control actions in conjunction with feedback actions that compensate for errors. Little is known about human control behavior in these situations. This paper investigates how humans adapt their feedforward control dynamics to the controlled element dynamics in a combined ramp-tracking and disturbance-rejection task. A human-in-the-loop experiment is performed with a pursuit display and vehicle-like controlled elements, ranging from a single integrator through second-order systems with a break frequency at either 3, 2, or 1 rad/s, to a double integrator. Because the potential benefits of feedforward control increase with steeper ramp segments in the target signal, three steepness levels are tested to investigate their possible effect on feedforward control with the various controlled elements. Analyses with four novel models of the operator, fitted to time-domain data, reveal feedforward control for all tested controlled elements and both (nonzero) tested levels of ramp steepness. For the range of controlled element dynamics investigated, it is found that humans adapt to these dynamics in their feedforward response, with a close to perfect inversion of the controlled element dynamics. No significant effects of ramp steepness on the feedforward model parameters are found.

  11. Frequency-weighted feedforward control for dynamic compensation in ionic polymer–metal composite actuators

    International Nuclear Information System (INIS)

    Shan, Yingfeng; Leang, Kam K

    2009-01-01

    Ionic polymer–metal composites (IPMCs) are innovative materials that offer combined sensing and actuating ability in lightweight and flexible package. IPMCs have been exploited in robotics and a wide variety of biomedical devices, for example, as sensors for teleoperation, as actuators for positioning in active endoscopy, as fins for propelling aquatic robots, and as an injector for drug delivery. In the actuation mode, one of the main challenges is precise position control. In particular, IPMC actuators exhibit relaxation behavior and nonlinearities; and at relatively high operating frequencies dynamic effects limit accuracy and positioning bandwidth. A frequency-weighted feedforward controller is designed to account for the IPMC's structural dynamics to enable fast positioning. The control method is applied to a custom-made Nafion-based IPMC actuator. The controller takes into account the magnitude of the control input to avoid generating excessively large voltages which can damage the IPMC actuator. To account for unmodeled effects not captured by the dynamics model, a feedback controller is integrated with the feedforward controller. Experimental results show a significant improvement in the tracking performance when feedforward control is used. For instance, the feedforward controller shows over 75% reduction in the tracking error compared to the case without feedforward compensation. Finally, the integrated feedforward and feedback control system reduces the tracking error to less than 10% for tracking an 18-Hz triangle-like trajectory. Some of the advantages of feedforward control as well as its limitations are also discussed

  12. Optimisation of a machine learning algorithm in human locomotion using principal component and discriminant function analyses

    OpenAIRE

    Bisele, M; Bencsik, M; Lewis, MGC; Barnett, CT

    2017-01-01

    Assessment methods in human locomotion often involve the description of normalised graphical profiles and/or the extraction of discrete variables. Whilst useful, these approaches may not represent the full complexity of gait data. Multivariate statistical methods, such as Principal Component Analysis (PCA) and Discriminant Function Analysis (DFA), have been adopted since they have the potential to overcome these data handling issues. The aim of the current study was to develop and optimise a ...

  13. Creating and Sustaining an Experiential Learning Component on Aging in a BSW Course

    Directory of Open Access Journals (Sweden)

    Jimmy A. Young

    2016-11-01

    Full Text Available Regardless of their particular field of practice, social workers increasingly serve the growing population of older adults in the United States. This article describes the process of integrating an experiential component into a Baccalaureate Social Work (BSW course involving 75 BSW students. Reflections on the strengths and challenges during 3 years of the course and a successful sustainability strategy are discussed. Three methods of curriculum infusion were added to a required course: (a guest speakers, (b required volunteer hours, and (c written reflections and class presentations. We discovered that students’ attitudes toward working with older adults were changed following their experience in this course. Cognizant of the difficulty introducing additional hours and content to a full course agenda, we advocate for curriculum change that includes an experiential component together with classroom discussion and activities. We provide details of our process of implementation and sustainability that might help guide similar course adaptations to increase BSW student exposure to working with older adults.

  14. How employees perceive organizational learning: construct validation of the 25-item short form of the strategic learning assessment map (SF-SLAM)

    NARCIS (Netherlands)

    Mainert, Jakob; Niepel, Christoph; Lans, T.; Greiff, Samuel

    2018-01-01

    Purpose: The Strategic Learning Assessment Map (SLAM) originally assessed organizational learning (OL) at the level of the firm by addressing managers, who rated OL in the SLAM on five dimensions of individual learning, group learning, organizational learning, feed-forward learning, and feedback

  15. The Relationship between Epistemological Beliefs and Motivational Components of Self-Regulated Learning Strategies of Male and Female EFL Learners across

    Directory of Open Access Journals (Sweden)

    Roya Nayebi Limoodehi

    2014-11-01

    Full Text Available The purpose of the present study was to determine the relationship between five dimensions of the epistemological beliefs regarding structure of knowledge, stability of knowledge, source of knowledge, ability to learn and, speed of learning and six measures of the motivational components of self-regulated learning strategies (intrinsic goal orientation, extrinsic goal orientation, task value, self-efficacy, control of learning, and test anxiety among male and female EFL learners across years of study (freshman and sophomore students. The participants of this study were 101 EFL students studying English literature and English translation in the Islamic Azad University, Rasht Branch, Iran, during the spring semester of 2013. The participants completed Persian version of Motivated Strategies for Learning Questionnaire (MSLQ (Pintrich, Smith, Garcia & McKeachie, 1991 and Persian version of Epistemological Questionnaire (Schommer, 1990. Results showed that, in general, the more naïve the epistemological beliefs of students, the less likely they are to use motivational learning strategies. Moreover, there was no significant relationship between dimensions of epistemological beliefs and motivational components of self-regulated learning strategies among male and female students. On the other hand, a statistically significant relationship was found between dimensions of epistemological beliefs and motivational components of self-regulated learning strategies for both freshman and sophomore students.

  16. Lessons Learned: Mechanical Component and Tribology Activities in Support of Return to Flight

    Science.gov (United States)

    Handschuh, Robert F.; Zaretsky, Erwin V.

    2017-01-01

    The February 2003 loss of the Space Shuttle Columbia resulted in NASA Management revisiting every critical system onboard this very complex, reusable space vehicle in a an effort to Return to Flight. Many months after the disaster, contact between NASA Johnson Space Center and NASA Glenn Research Center evolved into an in-depth assessment of the actuator drive systems for the Rudder Speed Brake and Body Flap Systems. The actuators are CRIT 1-1 systems that classifies them as failure of any of the actuators could result in loss of crew and vehicle. Upon further evaluation of these actuator systems and the resulting issues uncovered, several research activities were initiated, conducted, and reported to the NASA Space Shuttle Program Management. The papers contained in this document are the contributions of many researchers from NASA Glenn Research Center and Marshall Space Flight Center as part of a Lessons Learned on mechanical actuation systems as used in space applications. Many of the findings contained in this document were used as a basis to safely Return to Flight for the remaining Space Shuttle Fleet until their retirement.

  17. Design and Validation of Optimized Feedforward with Robust Feedback Control of a Nuclear Reactor

    International Nuclear Information System (INIS)

    Shaffer, Roman; He Weidong; Edwards, Robert M.

    2004-01-01

    Design applications for robust feedback and optimized feedforward control, with confirming results from experiments conducted on the Pennsylvania State University TRIGA reactor, are presented. The combination of feedforward and feedback control techniques complement each other in that robust control offers guaranteed closed-loop stability in the presence of uncertainties, and optimized feedforward offers an approach to achieving performance that is sometimes limited by overly conservative robust feedback control. The design approach taken in this work combines these techniques by first designing robust feedback control. Alternative methods for specifying a low-order linear model and uncertainty specifications, while seeking as much performance as possible, are discussed and evaluated. To achieve desired performance characteristics, the optimized feedforward control is then computed by using the nominal nonlinear plant model that incorporates the robust feedback control

  18. Glucocorticoid and cytokine crosstalk: Feedback, feedforward, and co-regulatory interactions determine repression or resistance.

    Science.gov (United States)

    Newton, Robert; Shah, Suharsh; Altonsy, Mohammed O; Gerber, Antony N

    2017-04-28

    Inflammatory signals induce feedback and feedforward systems that provide temporal control. Although glucocorticoids can repress inflammatory gene expression, glucocorticoid receptor recruitment increases expression of negative feedback and feedforward regulators, including the phosphatase, DUSP1, the ubiquitin-modifying enzyme, TNFAIP3, or the mRNA-destabilizing protein, ZFP36. Moreover, glucocorticoid receptor cooperativity with factors, including nuclear factor-κB (NF-κB), may enhance regulator expression to promote repression. Conversely, MAPKs, which are inhibited by glucocorticoids, provide feedforward control to limit expression of the transcription factor IRF1, and the chemokine, CXCL10. We propose that modulation of feedback and feedforward control can determine repression or resistance of inflammatory gene expression toglucocorticoid. © 2017 by The American Society for Biochemistry and Molecular Biology, Inc.

  19. Notions of local controllability and optimal feedforward control for quantum systems

    International Nuclear Information System (INIS)

    Chakrabarti, Raj

    2011-01-01

    Local controllability is an essential concept for regulation and control of time-varying nonlinear dynamical systems; in the classical control logic it is at the foundation of neighboring optimal feedback and feedforward control. We introduce notions of local controllability suited to feedforward control of classical input disturbances in bilinear quantum systems evolving on projective spaces and Lie groups. Tests for local controllability based on a Gramian matrix analogous to the nonlinear local controllability Gramian, which allow assessment of which trajectories can be regulated by perturbative feedforward in the presence of classical input noise, are presented. These notions explicitly incorporate system bilinearity and the geometry of quantum states into the definition of local controllability of quantum systems. Associated feedforward strategies are described.

  20. Feedforward control of a closed-loop piezoelectric translation stage for atomic force microscope.

    Science.gov (United States)

    Li, Yang; Bechhoefer, John

    2007-01-01

    Simple feedforward ideas are shown to lead to a nearly tenfold increase in the effective bandwidth of a closed-loop piezoelectric positioning stage used in scanning probe microscopy. If the desired control signal is known in advance, the feedforward filter can be acausal: the information about the future can be used to make the output of the stage have almost no phase lag with respect to the input. This keeps in register the images assembled from right and left scans. We discuss the design constraints imposed by the need for the feedforward filter to work robustly under a variety of circumstances. Because the feedforward needs only to modify the input signal, it can be added to any piezoelectric stage, whether closed or open loop.

  1. Notions of local controllability and optimal feedforward control for quantum systems

    Energy Technology Data Exchange (ETDEWEB)

    Chakrabarti, Raj, E-mail: rchakra@purdue.edu [School of Chemical Engineering, Purdue University, West Lafayette, IN 47907 (United States)

    2011-05-06

    Local controllability is an essential concept for regulation and control of time-varying nonlinear dynamical systems; in the classical control logic it is at the foundation of neighboring optimal feedback and feedforward control. We introduce notions of local controllability suited to feedforward control of classical input disturbances in bilinear quantum systems evolving on projective spaces and Lie groups. Tests for local controllability based on a Gramian matrix analogous to the nonlinear local controllability Gramian, which allow assessment of which trajectories can be regulated by perturbative feedforward in the presence of classical input noise, are presented. These notions explicitly incorporate system bilinearity and the geometry of quantum states into the definition of local controllability of quantum systems. Associated feedforward strategies are described.

  2. A feed-forward circuit linking wingless, fat-dachsous signaling, and the warts-hippo pathway to Drosophila wing growth.

    Directory of Open Access Journals (Sweden)

    Myriam Zecca

    2010-06-01

    Full Text Available During development, the Drosophila wing primordium undergoes a dramatic increase in cell number and mass under the control of the long-range morphogens Wingless (Wg, a Wnt and Decapentaplegic (Dpp, a BMP. This process depends in part on the capacity of wing cells to recruit neighboring, non-wing cells into the wing primordium. Wing cells are defined by activity of the selector gene vestigial (vg and recruitment entails the production of a vg-dependent "feed-forward signal" that acts together with morphogen to induce vg expression in neighboring non-wing cells. Here, we identify the protocadherins Fat (Ft and Dachsous (Ds, the Warts-Hippo tumor suppressor pathway, and the transcriptional co-activator Yorkie (Yki, a YES associated protein, or YAP as components of the feed-forward signaling mechanism, and we show how this mechanism promotes wing growth in response to Wg. We find that vg generates the feed-forward signal by creating a steep differential in Ft-Ds signaling between wing and non-wing cells. This differential down-regulates Warts-Hippo pathway activity in non-wing cells, leading to a burst of Yki activity and the induction of vg in response to Wg. We posit that Wg propels wing growth at least in part by fueling a wave front of Ft-Ds signaling that propagates vg expression from one cell to the next.

  3. On the approximation by single hidden layer feedforward neural networks with fixed weights

    OpenAIRE

    Guliyev, Namig J.; Ismailov, Vugar E.

    2017-01-01

    International audience; Feedforward neural networks have wide applicability in various disciplines of science due to their universal approximation property. Some authors have shown that single hidden layer feedforward neural networks (SLFNs) with fixed weights still possess the universal approximation property provided that approximated functions are univariate. But this phenomenon does not lay any restrictions on the number of neurons in the hidden layer. The more this number, the more the p...

  4. Cortical feedback signals generalise across different spatial frequencies of feedforward inputs

    OpenAIRE

    Revina, Yulia; Petro, Lucy S.; Muckli, Lars

    2017-01-01

    Visual processing in cortex relies on feedback projections contextualising feedforward information flow. Primary visual cortex (V1) has small receptive fields and processes feedforward information at a fine-grained spatial scale, whereas higher visual areas have larger, spatially invariant receptive fields. Therefore, feedback could provide coarse information about the global scene structure or alternatively recover fine-grained structure by targeting small receptive fields in V1. We tested i...

  5. Change detection of medical images using dictionary learning techniques and principal component analysis.

    Science.gov (United States)

    Nika, Varvara; Babyn, Paul; Zhu, Hongmei

    2014-07-01

    Automatic change detection methods for identifying the changes of serial MR images taken at different times are of great interest to radiologists. The majority of existing change detection methods in medical imaging, and those of brain images in particular, include many preprocessing steps and rely mostly on statistical analysis of magnetic resonance imaging (MRI) scans. Although most methods utilize registration software, tissue classification remains a difficult and overwhelming task. Recently, dictionary learning techniques are being used in many areas of image processing, such as image surveillance, face recognition, remote sensing, and medical imaging. We present an improved version of the EigenBlockCD algorithm, named the EigenBlockCD-2. The EigenBlockCD-2 algorithm performs an initial global registration and identifies the changes between serial MR images of the brain. Blocks of pixels from a baseline scan are used to train local dictionaries to detect changes in the follow-up scan. We use PCA to reduce the dimensionality of the local dictionaries and the redundancy of data. Choosing the appropriate distance measure significantly affects the performance of our algorithm. We examine the differences between [Formula: see text] and [Formula: see text] norms as two possible similarity measures in the improved EigenBlockCD-2 algorithm. We show the advantages of the [Formula: see text] norm over the [Formula: see text] norm both theoretically and numerically. We also demonstrate the performance of the new EigenBlockCD-2 algorithm for detecting changes of MR images and compare our results with those provided in the recent literature. Experimental results with both simulated and real MRI scans show that our improved EigenBlockCD-2 algorithm outperforms the previous methods. It detects clinical changes while ignoring the changes due to the patient's position and other acquisition artifacts.

  6. ISC feedforward control of gasoline engine. Adaptive system using neural network; Jidoshayo gasoline engine no ISC feedforward seigyo. Neural network wo mochiita tekioka

    Energy Technology Data Exchange (ETDEWEB)

    Kinugawa, N; Morita, S; Takiyama, T [Osaka City University, Osaka (Japan)

    1997-10-01

    For fuel economy and a good driver`s feeling, it is necessary for idle-speed to keep at a constant low speed. But keeping low speed has danger of engine stall when the engine torque is disturbed by the alternator, and so on. In this paper, adaptive feedforward idle-speed control system against electrical loads was investigated. This system was based on the reversed tansfer functions of the object system, and a neural network was used to adapt this system for aging. Then, this neural network was also used for creating feedforward table map. Good experimental results were obtained. 2 refs., 11 figs.

  7. A feedforward IMC structure for controlling the charging temperature of a TES system of a solar cooker

    International Nuclear Information System (INIS)

    Mawire, A.; McPherson, M.

    2008-01-01

    A feedforward internal model control (IMC) structure for controlling and maintaining the outlet charging temperature of a thermal energy storage (TES) system of a solar cooker is presented. The TES system consists of a packed pebble bed in thermal contact with a heat transfer oil contained in a storage tank. An electrical hot plate simulates the collector/concentrator which heats up the oil circulating in a hollow copper spiral coil thus charging the storage. A model for the collector/concentrator system is developed to enable simulation of the feedforward IMC structure. Using a Simulink block model, the simulation results reveal that a feedforward IMC structure performs better than a feedforward structure. The feedforward IMC structure is tested experimentally and the performance of the control structure is acceptable within a few degrees of the set temperatures. Experimental results are also compared with the simulation results. The simulated responses are found to relate closely to the experimental ones and any discrepancies between the two are discussed. Furthermore, the feedforward IMC structure is also compared experimentally with a combined feedforward and PID feedback structure. Results of the comparison indicate that the feedforward IMC structure performs better than the combined feedforward and PID feedback structure. The thermal profile of the storage during the charging experiment with the feedforward IMC structure is also presented and the results obtained from the storage profile indicate that the storage tank is thermally stratified

  8. Proinflammatory Cytokine Infusion Attenuates LH's Feedforward on Testosterone Secretion: Modulation by Age

    Science.gov (United States)

    Yang, Rebecca; Roelfsema, Ferdinand; Takahashi, Paul

    2016-01-01

    Context: In the experimental animal, inflammatory signals quench LH's feedforward drive of testosterone (T) secretion and appear to impair GnRH-LH output. The degree to which such suppressive effects operate in the human is not known. Objective: To test the hypothesis that IL-2 impairs LH's feedforward drive on T and T's feedback inhibition of LH secretion in healthy men. Setting: Mayo Center for Translational Science Activities. Patients or Other Participants: A total of 35 healthy men, 17 young and 18 older. Interventions: Randomized prospective double-blind saline-controlled study of IL-2 infusion in 2 doses with concurrent 10-minute blood sampling for 24 hours. Main Outcome Measures: Deconvolution analysis of LH and T secretion. Results: After saline injection, older compared with young men exhibited reduced LH feedforward drive on T secretion (P feedback inhibition of LH secretion (P feedforward onto T secretion declined markedly especially in young subjects (P feedback on LH secretion especially in older volunteers. Conclusion: This investigation confirms combined feedforward and feedback deficits in older relative to young men given saline and demonstrates 1) joint mechanisms by which IL-2 enforces biochemical hypogonadism, viz, combined feedforward block and feedback amplification; and 2) unequal absolute inhibition of T and LH secretion by IL-2 in young and older men. These outcomes establish that the male gonadal axis is susceptible to dual-site suppression by a prototypic inflammatory mediator. Thus, we postulate that selected ILs might also enforce male hypogonadism in chronic systemic inflammation. PMID:26600270

  9. Development of an Accurate Feed-Forward Temperature Control Tankless Water Heater

    Energy Technology Data Exchange (ETDEWEB)

    David Yuill

    2008-06-30

    design was then implemented on a prototype heater that was being developed simultaneously with the controller development. (The prototype's geometry and components are based on a currently marketed heater, but several improvements have been made.) The MPC's temperature control performance was a vast improvement over the existing controller. With a benchmark for superior control performance established, five additional control methods were tested. One problem with MPC control is that it was found to be extremely difficult to implement in a TWH, so that it is unlikely to be widely adopted by manufacturers. Therefore the five additional control methods were selected based on their simplicity; each could be implemented by a typical manufacturer. It was found that one of these methods performed as well as MPC, or even better under many circumstances. This method uses a Feedback-Compensated Feed-Forward algorithm that was developed for this project. Due to its simplicity and excellent performance this method was selected as the controller of choice. A final higher-capacity prototype heater that uses Feedback-Compensated Feed-Forward control was constructed. This prototype has many improvements over the currently marketed heaters: (1) excellent control; (2) a modular design that allows for different capacity heaters to be built easily; (3) built-in fault detection and diagnosis; (4) a secondary remote user-interface; and (5) a TRIAC switching algorithm that will minimize 'flicker factor'. The design and engineering of this prototype unit will allow it to be built without an increase in cost, compared with the currently marketed heater. A design rendering of the new product is shown below. It will be launched with a new marketing campaign by Keltech in early 2009.

  10. Predicting ground contact events for a continuum of gait types: An application of targeted machine learning using principal component analysis.

    Science.gov (United States)

    Osis, Sean T; Hettinga, Blayne A; Ferber, Reed

    2016-05-01

    An ongoing challenge in the application of gait analysis to clinical settings is the standardized detection of temporal events, with unobtrusive and cost-effective equipment, for a wide range of gait types. The purpose of the current study was to investigate a targeted machine learning approach for the prediction of timing for foot strike (or initial contact) and toe-off, using only kinematics for walking, forefoot running, and heel-toe running. Data were categorized by gait type and split into a training set (∼30%) and a validation set (∼70%). A principal component analysis was performed, and separate linear models were trained and validated for foot strike and toe-off, using ground reaction force data as a gold-standard for event timing. Results indicate the model predicted both foot strike and toe-off timing to within 20ms of the gold-standard for more than 95% of cases in walking and running gaits. The machine learning approach continues to provide robust timing predictions for clinical use, and may offer a flexible methodology to handle new events and gait types. Copyright © 2016 Elsevier B.V. All rights reserved.

  11. Adaptive online monitoring for ICU patients by combining just-in-time learning and principal component analysis.

    Science.gov (United States)

    Li, Xuejian; Wang, Youqing

    2016-12-01

    Offline general-type models are widely used for patients' monitoring in intensive care units (ICUs), which are developed by using past collected datasets consisting of thousands of patients. However, these models may fail to adapt to the changing states of ICU patients. Thus, to be more robust and effective, the monitoring models should be adaptable to individual patients. A novel combination of just-in-time learning (JITL) and principal component analysis (PCA), referred to learning-type PCA (L-PCA), was proposed for adaptive online monitoring of patients in ICUs. JITL was used to gather the most relevant data samples for adaptive modeling of complex physiological processes. PCA was used to build an online individual-type model and calculate monitoring statistics, and then to judge whether the patient's status is normal or not. The adaptability of L-PCA lies in the usage of individual data and the continuous updating of the training dataset. Twelve subjects were selected from the Physiobank's Multi-parameter Intelligent Monitoring for Intensive Care II (MIMIC II) database, and five vital signs of each subject were chosen. The proposed method was compared with the traditional PCA and fast moving-window PCA (Fast MWPCA). The experimental results demonstrated that the fault detection rates respectively increased by 20 % and 47 % compared with PCA and Fast MWPCA. L-PCA is first introduced into ICU patients monitoring and achieves the best monitoring performance in terms of adaptability to changes in patient status and sensitivity for abnormality detection.

  12. Principal component analysis study of visual and verbal metaphoric comprehension in children with autism and learning disabilities.

    Science.gov (United States)

    Mashal, Nira; Kasirer, Anat

    2012-01-01

    This research extends previous studies regarding the metaphoric competence of autistic and learning disable children on different measures of visual and verbal non-literal language comprehension, as well as cognitive abilities that include semantic knowledge, executive functions, similarities, and reading fluency. Thirty seven children with autism (ASD), 20 children with learning disabilities (LD), and 21 typically developed (TD) children participated in the study. Principal components analysis was used to examine the interrelationship among the various tests in each group. Results showed different patterns in the data according to group. In particular, the results revealed that there is no dichotomy between visual and verbal metaphors in TD children but rather metaphor are classified according to their familiarity level. In the LD group visual metaphors were classified independently of the verbal metaphors. Verbal metaphoric understanding in the ASD group resembled the LD group. In addition, our results revealed the relative weakness of the ASD and LD children in suppressing irrelevant information. Copyright © 2011 Elsevier Ltd. All rights reserved.

  13. Effects of topologies on signal propagation in feedforward networks

    Science.gov (United States)

    Zhao, Jia; Qin, Ying-Mei; Che, Yan-Qiu

    2018-01-01

    We systematically investigate the effects of topologies on signal propagation in feedforward networks (FFNs) based on the FitzHugh-Nagumo neuron model. FFNs with different topological structures are constructed with same number of both in-degrees and out-degrees in each layer and given the same input signal. The propagation of firing patterns and firing rates are found to be affected by the distribution of neuron connections in the FFNs. Synchronous firing patterns emerge in the later layers of FFNs with identical, uniform, and exponential degree distributions, but the number of synchronous spike trains in the output layers of the three topologies obviously differs from one another. The firing rates in the output layers of the three FFNs can be ordered from high to low according to their topological structures as exponential, uniform, and identical distributions, respectively. Interestingly, the sequence of spiking regularity in the output layers of the three FFNs is consistent with the firing rates, but their firing synchronization is in the opposite order. In summary, the node degree is an important factor that can dramatically influence the neuronal network activity.

  14. An incoherent feedforward loop facilitates adaptive tuning of gene expression.

    Science.gov (United States)

    Hong, Jungeui; Brandt, Nathan; Abdul-Rahman, Farah; Yang, Ally; Hughes, Tim; Gresham, David

    2018-04-05

    We studied adaptive evolution of gene expression using long-term experimental evolution of Saccharomyces cerevisiae in ammonium-limited chemostats. We found repeated selection for non-synonymous variation in the DNA binding domain of the transcriptional activator, GAT1, which functions with the repressor, DAL80 in an incoherent type-1 feedforward loop (I1-FFL) to control expression of the high affinity ammonium transporter gene, MEP2. Missense mutations in the DNA binding domain of GAT1 reduce its binding to the GATAA consensus sequence. However, we show experimentally, and using mathematical modeling, that decreases in GAT1 binding result in increased expression of MEP2 as a consequence of properties of I1-FFLs. Our results show that I1-FFLs, one of the most commonly occurring network motifs in transcriptional networks, can facilitate adaptive tuning of gene expression through modulation of transcription factor binding affinities. Our findings highlight the importance of gene regulatory architectures in the evolution of gene expression. © 2018, Hong et al.

  15. Why vision is not both hierarchical and feedforward

    Directory of Open Access Journals (Sweden)

    Michael H Herzog

    2014-10-01

    Full Text Available In classical models of object recognition, first, basic features (e.g., edges and lines are analyzed by independent filters that mimic the receptive field profiles of V1 neurons. In a feedforward fashion, the outputs of these filters are fed to filters at the next processing stage, pooling information across several filters from the previous level, and so forth at subsequent processing stages. Low-level processing determines high-level processing. Information lost on lower stages is irretrievably lost. Models of this type have proven to be very successful in many fields of vision, but have failed to explain object recognition in general. Here, we present experiments that, first, show that, similar to demonstrations from the Gestaltists, figural aspects determine low-level processing (as much as the other way around. Second, performance on a single element depends on all the other elements in the visual scene. Small changes in the overall configuration can lead to large changes in performance. Third, grouping of elements is key. Only if we know how elements group across the entire visual field, we can determine performance on individual elements, i.e., challenging the classical stereotypical filtering approach, which is at the very heart of most vision models.

  16. Adaptive Feed-Forward Control of Low Frequency Interior Noise

    CERN Document Server

    Kletschkowski, Thomas

    2012-01-01

    This book presents a mechatronic approach to Active Noise Control (ANC). It describes the required elements of system theory, engineering acoustics, electroacoustics and adaptive signal processing in a comprehensive, consistent and systematic manner using a unified notation. Furthermore, it includes a design methodology for ANC-systems, explains its application and describes tools to be used for ANC-system design. From the research point of view, the book presents new approaches to sound source localization in weakly damped interiors. One is based on the inverse finite element method, the other is based on a sound intensity probe with an active free field. Furthermore, a prototype of an ANC-system able to reach the physical limits of local (feed-forward) ANC is described. This is one example for applied research in ANC-system design. Other examples are given for (i) local ANC in a semi-enclosed subspace of an aircraft cargo hold and (ii) for the combination of audio entertainment with ANC.

  17. Prediction of metal corrosion using feed-forward neural networks

    International Nuclear Information System (INIS)

    Mahjani, M.G.; Jalili, S.; Jafarian, M.; Jaberi, A.

    2004-01-01

    The reliable prediction of corrosion behavior for the effective control of corrosion is a fundamental requirement. Since real world corrosion never seems to involve quite the same conditions that have previously been tested, using corrosion literature does not provide the necessary answers. In order to provide a methodology for predicting corrosion in real and complex situations, artificial neural networks can be utilized. Feed-forward artificial neural network (FFANN) is an information-processing paradigm inspired by the way the densely interconnected, parallel structure of the human brain process information.The aim of the present work is to predict corrosion behavior in critical conditions, such as industrial applications, based on some laboratory experimental data. Electrochemical behavior of stainless steel in different conditions were studied, using polarization technique and Tafel curves. Back-propagation neural networks models were developed to predict the corrosion behavior. The trained networks result in predicted value in good comparison to the experimental data. They have generally been claimed to be successful in modeling the corrosion behavior. The results are presented in two tables. Table 1 gives corrosion behavior of stainless-steel as a function of pH and CuSO 4 concentration and table 2 gives corrosion behavior of stainless - steel as a function of electrode surface area and CuSO 4 concentration. (authors)

  18. Deep learning

    CERN Document Server

    Goodfellow, Ian; Courville, Aaron

    2016-01-01

    Deep learning is a form of machine learning that enables computers to learn from experience and understand the world in terms of a hierarchy of concepts. Because the computer gathers knowledge from experience, there is no need for a human computer operator to formally specify all the knowledge that the computer needs. The hierarchy of concepts allows the computer to learn complicated concepts by building them out of simpler ones; a graph of these hierarchies would be many layers deep. This book introduces a broad range of topics in deep learning. The text offers mathematical and conceptual background, covering relevant concepts in linear algebra, probability theory and information theory, numerical computation, and machine learning. It describes deep learning techniques used by practitioners in industry, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology; and it surveys such applications as natural language proces...

  19. Reliability analysis of C-130 turboprop engine components using artificial neural network

    Science.gov (United States)

    Qattan, Nizar A.

    In this study, we predict the failure rate of Lockheed C-130 Engine Turbine. More than thirty years of local operational field data were used for failure rate prediction and validation. The Weibull regression model and the Artificial Neural Network model including (feed-forward back-propagation, radial basis neural network, and multilayer perceptron neural network model); will be utilized to perform this study. For this purpose, the thesis will be divided into five major parts. First part deals with Weibull regression model to predict the turbine general failure rate, and the rate of failures that require overhaul maintenance. The second part will cover the Artificial Neural Network (ANN) model utilizing the feed-forward back-propagation algorithm as a learning rule. The MATLAB package will be used in order to build and design a code to simulate the given data, the inputs to the neural network are the independent variables, the output is the general failure rate of the turbine, and the failures which required overhaul maintenance. In the third part we predict the general failure rate of the turbine and the failures which require overhaul maintenance, using radial basis neural network model on MATLAB tool box. In the fourth part we compare the predictions of the feed-forward back-propagation model, with that of Weibull regression model, and radial basis neural network model. The results show that the failure rate predicted by the feed-forward back-propagation artificial neural network model is closer in agreement with radial basis neural network model compared with the actual field-data, than the failure rate predicted by the Weibull model. By the end of the study, we forecast the general failure rate of the Lockheed C-130 Engine Turbine, the failures which required overhaul maintenance and six categorical failures using multilayer perceptron neural network (MLP) model on DTREG commercial software. The results also give an insight into the reliability of the engine

  20. Predicting perceptual learning from higher-order cortical processing.

    Science.gov (United States)

    Wang, Fang; Huang, Jing; Lv, Yaping; Ma, Xiaoli; Yang, Bin; Wang, Encong; Du, Boqi; Li, Wu; Song, Yan

    2016-01-01

    Visual perceptual learning has been shown to be highly specific to the retinotopic location and attributes of the trained stimulus. Recent psychophysical studies suggest that these specificities, which have been associated with early retinotopic visual cortex, may in fact not be inherent in perceptual learning and could be related to higher-order brain functions. Here we provide direct electrophysiological evidence in support of this proposition. In a series of event-related potential (ERP) experiments, we recorded high-density electroencephalography (EEG) from human adults over the course of learning in a texture discrimination task (TDT). The results consistently showed that the earliest C1 component (68-84ms), known to reflect V1 activity driven by feedforward inputs, was not modulated by learning regardless of whether the behavioral improvement is location specific or not. In contrast, two later posterior ERP components (posterior P1 and P160-350) over the occipital cortex and one anterior ERP component (anterior P160-350) over the prefrontal cortex were progressively modified day by day. Moreover, the change of the anterior component was closely correlated with improved behavioral performance on a daily basis. Consistent with recent psychophysical and imaging observations, our results indicate that perceptual learning can mainly involve changes in higher-level visual cortex as well as in the neural networks responsible for cognitive functions such as attention and decision making. Copyright © 2015 Elsevier Inc. All rights reserved.

  1. Dropout Prediction in E-Learning Courses through the Combination of Machine Learning Techniques

    Science.gov (United States)

    Lykourentzou, Ioanna; Giannoukos, Ioannis; Nikolopoulos, Vassilis; Mpardis, George; Loumos, Vassili

    2009-01-01

    In this paper, a dropout prediction method for e-learning courses, based on three popular machine learning techniques and detailed student data, is proposed. The machine learning techniques used are feed-forward neural networks, support vector machines and probabilistic ensemble simplified fuzzy ARTMAP. Since a single technique may fail to…

  2. A self-adaptive feedforward rf control system for linacs

    International Nuclear Information System (INIS)

    Zhang Renshan; Ben-Zvi, I.; Xie Jialin

    1993-01-01

    The design and performance of a self-adaptive feedforward rf control system are reported. The system was built for the linac of the Accelerator Test Facility (ATF) at Brookhaven National Laboratory. Variables of time along the linac macropulse, such as field or phase are discretized and represented as vectors. Upon turn-on or after a large change in the operating-point, the control system acquires the response of the system to test signal vectors and generates a linearized system response matrix. During operation an error vector is generated by comparing the linac variable vectors and a target vector. The error vector is multiplied by the inverse of the system's matrix to generate a correction vector is added to an operating point vector. This control system can be used to control a klystron to produce flat rf amplitude and phase pulses, to control a rf cavity to reduce the rf field fluctuation, and to compensate the energy spread among bunches in a rf linac. Beam loading effects can be corrected and a programmed ramp can be produced. The performance of the control system has been evaluated on the control of a klystron's output as well as an rf cavity. Both amplitude and phase have been regulated simultaneously. In initial tests, the rf output from a klystron has been regulated to an amplitude fluctuation of less than ±0.3% and phase variation of less than ±0.6deg. The rf field of the ATF's photo-cathode microwave gun cavity has been regulated to ±5% in amplitude and simultaneously to ±1deg in phase. Regulating just the rf field amplitude in the rf gun cavity, we have achieved amplitude fluctuation of less than ±2%. (orig.)

  3. Feedforward neural control of toe walking in humans.

    Science.gov (United States)

    Lorentzen, Jakob; Willerslev-Olsen, Maria; Hüche Larsen, Helle; Svane, Christian; Forman, Christian; Frisk, Rasmus; Farmer, Simon Francis; Kersting, Uwe; Nielsen, Jens Bo

    2018-03-23

    Activation of ankle muscles at ground contact during toe walking is unaltered when sensory feedback is blocked or the ground is suddenly dropped. Responses in the soleus muscle to transcranial magnetic stimulation, but not peripheral nerve stimulation, are facilitated at ground contact during toe walking. We argue that toe walking is supported by feedforward control at ground contact. Toe walking requires careful control of the ankle muscles in order to absorb the impact of ground contact and maintain a stable position of the joint. The present study aimed to clarify the peripheral and central neural mechanisms involved. Fifteen healthy adults walked on a treadmill (3.0 km h -1 ). Tibialis anterior (TA) and soleus (Sol) EMG, knee and ankle joint angles, and gastrocnemius-soleus muscle fascicle lengths were recorded. Peripheral and central contributions to the EMG activity were assessed by afferent blockade, H-reflex testing, transcranial magnetic brain stimulation (TMS) and sudden unloading of the planter flexor muscle-tendon complex. Sol EMG activity started prior to ground contact and remained high throughout stance. TA EMG activity, which is normally seen around ground contact during heel strike walking, was absent. Although stretch of the Achilles tendon-muscle complex was observed after ground contact, this was not associated with lengthening of the ankle plantar flexor muscle fascicles. Sol EMG around ground contact was not affected by ischaemic blockade of large-diameter sensory afferents, or the sudden removal of ground support shortly after toe contact. Soleus motor-evoked potentials elicited by TMS were facilitated immediately after ground contact, whereas Sol H-reflexes were not. These findings indicate that at the crucial time of ankle stabilization following ground contact, toe walking is governed by centrally mediated motor drive rather than sensory driven reflex mechanisms. These findings have implications for our understanding of the control of

  4. A combined stochastic feedforward and feedback control design methodology with application to autoland design

    Science.gov (United States)

    Halyo, Nesim

    1987-01-01

    A combined stochastic feedforward and feedback control design methodology was developed. The objective of the feedforward control law is to track the commanded trajectory, whereas the feedback control law tries to maintain the plant state near the desired trajectory in the presence of disturbances and uncertainties about the plant. The feedforward control law design is formulated as a stochastic optimization problem and is embedded into the stochastic output feedback problem where the plant contains unstable and uncontrollable modes. An algorithm to compute the optimal feedforward is developed. In this approach, the use of error integral feedback, dynamic compensation, control rate command structures are an integral part of the methodology. An incremental implementation is recommended. Results on the eigenvalues of the implemented versus designed control laws are presented. The stochastic feedforward/feedback control methodology is used to design a digital automatic landing system for the ATOPS Research Vehicle, a Boeing 737-100 aircraft. The system control modes include localizer and glideslope capture and track, and flare to touchdown. Results of a detailed nonlinear simulation of the digital control laws, actuator systems, and aircraft aerodynamics are presented.

  5. A comprehensive inversion approach for feedforward compensation of piezoactuator system at high frequency

    Science.gov (United States)

    Tian, Lizhi; Xiong, Zhenhua; Wu, Jianhua; Ding, Han

    2016-09-01

    Motion control of the piezoactuator system over broadband frequencies is limited due to its inherent hysteresis and system dynamics. One of the suggested ways is to use feedforward controller to linearize the input-output relationship of the piezoactuator system. Although there have been many feedforward approaches, it is still a challenge to develop feedforward controller for the piezoactuator system at high frequency. Hence, this paper presents a comprehensive inversion approach in consideration of the coupling of hysteresis and dynamics. In this work, the influence of dynamics compensation on the input-output relationship of the piezoactuator system is investigated first. With system dynamics compensation, the input-output relationship of the piezoactuator system will be further represented as rate-dependent nonlinearity due to the inevitable dynamics compensation error, especially at high frequency. Base on this result, the feedforward controller composed by a cascade of linear dynamics inversion and rate-dependent nonlinearity inversion is developed. Then, the system identification of the comprehensive inversion approach is proposed. Finally, experimental results show that the proposed approach can improve the performance on tracking of both periodic and non-periodic trajectories at medium and high frequency compared with the conventional feedforward approaches.

  6. An Approach to Integrating Tactical Decision-Making in Industrial Maintenance Balance Scorecards Using Principal Components Analysis and Machine Learning

    Directory of Open Access Journals (Sweden)

    Néstor Rodríguez-Padial

    2017-01-01

    Full Text Available The uncertainty of demand has led production systems to become increasingly complex; this can affect the availability of the machines and thus their maintenance. Therefore, it is necessary to adequately manage the information that facilitates decision-making. This paper presents a system for making decisions related to the design of customized maintenance plans in a production plant. This paper addresses this tactical goal and aims to provide greater knowledge and better predictions by projecting reliable behavior in the medium-term, integrating this new functionality into classic Balance Scorecards, and making it possible to extend their current measuring function to a new aptitude: predicting evolution based on historical data. In the proposed Custom Balance Scorecard design, an exploratory data phase is integrated with another analysis and prediction phase using Principal Component Analysis algorithms and Machine Learning that uses Artificial Neural Network algorithms. This new extension allows better control over the maintenance function of an industrial plant in the medium-term with a yearly horizon taken over monthly intervals which allows the measurement of the indicators of strategic productive areas and the discovery of hidden behavior patterns in work orders. In addition, this extension enables the prediction of indicator outcomes such as overall equipment efficiency and mean time to failure.

  7. Feedforward Object-Vision Models Only Tolerate Small Image Variations Compared to Human

    Directory of Open Access Journals (Sweden)

    Masoud eGhodrati

    2014-07-01

    Full Text Available Invariant object recognition is a remarkable ability of primates' visual system that its underlying mechanism has constantly been under intense investigations. Computational modelling is a valuable tool toward understanding the processes involved in invariant object recognition. Although recent computational models have shown outstanding performances on challenging image databases, they fail to perform well when images with more complex variations of the same object are applied to them. Studies have shown that making sparse representation of objects by extracting more informative visual features through a feedforward sweep can lead to higher recognition performances. Here, however, we show that when the complexity of image variations is high, even this approach results in poor performance compared to humans. To assess the performance of models and humans in invariant object recognition tasks, we built a parametrically controlled image database consisting of several object categories varied in different dimensions and levels, rendered from 3D planes. Comparing the performance of several object recognition models with human observers shows that only in low-level image variations the models perform similar to humans in categorization tasks. Furthermore, the results of our behavioral experiments demonstrate that, even under difficult experimental conditions (i.e. briefly presented masked stimuli with complex image variations, human observers performed outstandingly well, suggesting that the models are still far from resembling humans in invariant object recognition. Taken together, we suggest that learning sparse informative visual features, although desirable, is not a complete solution for future progresses in object-vision modelling. We show that this approach is not of significant help in solving the computational crux of object recognition (that is invariant object recognition when the identity-preserving image variations become more complex.

  8. The Psychometric Assessment of Children with Learning Disabilities: An Index Derived from a Principal Components Analysis of the WISC-R.

    Science.gov (United States)

    Lawson, J. S.; Inglis, James

    1984-01-01

    A learning disability index (LDI) for the assessment of intellectual deficits on the Wechsler Intelligence Scale for Children-Revised (WISC-R) is described. The Factor II score coefficients derived from an unrotated principal components analysis of the WISC-R normative data, in combination with the individual's scaled scores, are used for this…

  9. An empirical investigation on the effects of spiritual leadership components on organizational learning capacity: A case study of Payame Noor University

    Directory of Open Access Journals (Sweden)

    Amir Hossein

    2013-06-01

    Full Text Available This paper presents an empirical investigation on the effects of spiritual leadership components on organizational learning capacity for a case study of Payame Noor University, Iran. The proposed study uses a standard questionnaire for measuring spirituality leadership proposed by Fry (2003 [Fry, L. W. (2003. Toward a theory of spiritual leadership. The leadership quarterly, 14(6, 693-727.] and for measuring the impact of organizational learning capacity, the proposed study uses another questionnaire proposed by Teo et al. (2006 [Teo, H. H., Wang, X., Wei, K. K., Sia, C. L., & Lee, M. K. (2006. Organizational learning capacity and attitude toward complex technological innovations: an empirical study. Journal of the American Society for Information Science and Technology, 57(2, 264-279.]. The results of our survey have indicated that all components of spiritual leadership, except love and altruism as meaningful, influence spirituality leadership, significantly.

  10. Low-Latency Digital Signal Processing for Feedback and Feedforward in Quantum Computing and Communication

    Science.gov (United States)

    Salathé, Yves; Kurpiers, Philipp; Karg, Thomas; Lang, Christian; Andersen, Christian Kraglund; Akin, Abdulkadir; Krinner, Sebastian; Eichler, Christopher; Wallraff, Andreas

    2018-03-01

    Quantum computing architectures rely on classical electronics for control and readout. Employing classical electronics in a feedback loop with the quantum system allows us to stabilize states, correct errors, and realize specific feedforward-based quantum computing and communication schemes such as deterministic quantum teleportation. These feedback and feedforward operations are required to be fast compared to the coherence time of the quantum system to minimize the probability of errors. We present a field-programmable-gate-array-based digital signal processing system capable of real-time quadrature demodulation, a determination of the qubit state, and a generation of state-dependent feedback trigger signals. The feedback trigger is generated with a latency of 110 ns with respect to the timing of the analog input signal. We characterize the performance of the system for an active qubit initialization protocol based on the dispersive readout of a superconducting qubit and discuss potential applications in feedback and feedforward algorithms.

  11. Combined feedforward and feedback control of a redundant, nonlinear, dynamic musculoskeletal system.

    Science.gov (United States)

    Blana, Dimitra; Kirsch, Robert F; Chadwick, Edward K

    2009-05-01

    A functional electrical stimulation controller is presented that uses a combination of feedforward and feedback for arm control in high-level injury. The feedforward controller generates the muscle activations nominally required for desired movements, and the feedback controller corrects for errors caused by muscle fatigue and external disturbances. The feedforward controller is an artificial neural network (ANN) which approximates the inverse dynamics of the arm. The feedback loop includes a PID controller in series with a second ANN representing the nonlinear properties and biomechanical interactions of muscles and joints. The controller was designed and tested using a two-joint musculoskeletal model of the arm that includes four mono-articular and two bi-articular muscles. Its performance during goal-oriented movements of varying amplitudes and durations showed a tracking error of less than 4 degrees in ideal conditions, and less than 10 degrees even in the case of considerable fatigue and external disturbances.

  12. Performance assessment of static lead-lag feedforward controllers for disturbance rejection in PID control loops.

    Science.gov (United States)

    Yu, Zhenpeng; Wang, Jiandong

    2016-09-01

    This paper assesses the performance of feedforward controllers for disturbance rejection in univariate feedback plus feedforward control loops. The structures of feedback and feedforward controllers are confined to proportional-integral-derivative and static-lead-lag forms, respectively, and the effects of feedback controllers are not considered. The integral squared error (ISE) and total squared variation (TSV) are used as performance metrics. A performance index is formulated by comparing the current ISE and TSV metrics to their own lower bounds as performance benchmarks. A controller performance assessment (CPA) method is proposed to calculate the performance index from measurements. The proposed CPA method resolves two critical limitations in the existing CPA methods, in order to be consistent with industrial scenarios. Numerical and experimental examples illustrate the effectiveness of the obtained results. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

  13. Slewing maneuvers and vibration control of space structures by feedforward/feedback moment-gyro controls

    Science.gov (United States)

    Yang, Li-Farn; Mikulas, Martin M., Jr.; Park, K. C.; Su, Renjeng

    1993-01-01

    This paper presents a moment-gyro control approach to the maneuver and vibration suppression of a flexible truss arm undergoing a constant slewing motion. The overall slewing motion is triggered by a feedforward input, and a companion feedback controller is employed to augment the feedforward input and subsequently to control vibrations. The feedforward input for the given motion requirement is determined from the combined CMG (Control Momentum Gyro) devices and the desired rigid-body motion. The rigid-body dynamic model has enabled us to identify the attendant CMG momentum saturation constraints. The task for vibration control is carried out in two stages; first in the search of a suitable CMG placement along the beam span for various slewing maneuvers, and subsequently in the development of Liapunov-based control algorithms for CMG spin-stabilization. Both analytical and numerical results are presented to show the effectiveness of the present approach.

  14. Hypocortisolemic clamp unmasks jointly feedforward- and feedback-dependent control of overnight ACTH secretion.

    Science.gov (United States)

    Iranmanesh, Ali; Veldhuis, Johannes D

    2008-11-01

    ACTH secretion is under hypothalamic stimulatory (feedforward) and adrenal inhibitory (feedback) control. Assessment of overnight ACTH secretion during a hypocortisolemic clamp will permit the estimation of changing feedforward and feedback. Seven healthy men. An oral dose of placebo (PLAC), metyrapone (METY, 3 g), or ketoconazole (KTCZ, 1.2 g) was given at midnight (MN) to block glucocorticoid synthesis. Plasma ACTH was sampled every 10 min (MN to 0800 h). Variable-waveform deconvolution analysis of ACTH secretion and approximate entropy (ApEn) analysis of pattern regularity. Compared with PLAC, administration of METY and KTCZ reduced morning cortisol concentrations by >or=77 and 54% respectively (Pfeedforward coordination. The combined data predict overnight amplification and coordination of hypothalamic feedforward drive onto ACTH release. Therefore, disruption of either mechanism might contribute to clinical pathophysiology, such as late-day elevations of cortisol output in fasting, alcoholism, depression, or aging.

  15. Robust wide-range control of nuclear reactors by using the feedforward-feedback concept

    International Nuclear Information System (INIS)

    Weng, C.K.; Edwards, R.M.; Ray, A.

    1994-01-01

    A robust feedforward-feedback controller is proposed for wide-range operations of nuclear reactors. This control structure provides (a) optimized performance over a wide operating range resulting form the feedforward element and (b) guaranteed robust stability and performance resulting from the feedback element. The feedforward control law is synthesized via nonlinear programming, which generates an optimal control sequence over a finite-time horizon under specified constraints. The feedback control is synthesized via the structured singular value μ approach to guarantee robustness in the presence of disturbances and modeling uncertainties. The results of simulation experiments are presented to demonstrate efficacy of the proposed control structure for a large rapid power reduction to avoid unnecessary plant trips

  16. Evaluation of the Performance of Feedforward and Recurrent Neural Networks in Active Cancellation of Sound Noise

    Directory of Open Access Journals (Sweden)

    Mehrshad Salmasi

    2012-07-01

    Full Text Available Active noise control is based on the destructive interference between the primary noise and generated noise from the secondary source. An antinoise of equal amplitude and opposite phase is generated and combined with the primary noise. In this paper, performance of the neural networks is evaluated in active cancellation of sound noise. For this reason, feedforward and recurrent neural networks are designed and trained. After training, performance of the feedforwrad and recurrent networks in noise attenuation are compared. We use Elman network as a recurrent neural network. For simulations, noise signals from a SPIB database are used. In order to compare the networks appropriately, equal number of layers and neurons are considered for the networks. Moreover, training and test samples are similar. Simulation results show that feedforward and recurrent neural networks present good performance in noise cancellation. As it is seen, the ability of recurrent neural network in noise attenuation is better than feedforward network.

  17. Feed-forward segmentation of figure-ground and assignment of border-ownership.

    Directory of Open Access Journals (Sweden)

    Hans Supèr

    Full Text Available Figure-ground is the segmentation of visual information into objects and their surrounding backgrounds. Two main processes herein are boundary assignment and surface segregation, which rely on the integration of global scene information. Recurrent processing either by intrinsic horizontal connections that connect surrounding neurons or by feedback projections from higher visual areas provide such information, and are considered to be the neural substrate for figure-ground segmentation. On the contrary, a role of feedforward projections in figure-ground segmentation is unknown. To have a better understanding of a role of feedforward connections in figure-ground organization, we constructed a feedforward spiking model using a biologically plausible neuron model. By means of surround inhibition our simple 3-layered model performs figure-ground segmentation and one-sided border-ownership coding. We propose that the visual system uses feed forward suppression for figure-ground segmentation and border-ownership assignment.

  18. Feed-forward segmentation of figure-ground and assignment of border-ownership.

    Science.gov (United States)

    Supèr, Hans; Romeo, August; Keil, Matthias

    2010-05-19

    Figure-ground is the segmentation of visual information into objects and their surrounding backgrounds. Two main processes herein are boundary assignment and surface segregation, which rely on the integration of global scene information. Recurrent processing either by intrinsic horizontal connections that connect surrounding neurons or by feedback projections from higher visual areas provide such information, and are considered to be the neural substrate for figure-ground segmentation. On the contrary, a role of feedforward projections in figure-ground segmentation is unknown. To have a better understanding of a role of feedforward connections in figure-ground organization, we constructed a feedforward spiking model using a biologically plausible neuron model. By means of surround inhibition our simple 3-layered model performs figure-ground segmentation and one-sided border-ownership coding. We propose that the visual system uses feed forward suppression for figure-ground segmentation and border-ownership assignment.

  19. Mechanism for propagation of rate signals through a 10-layer feedforward neuronal network

    International Nuclear Information System (INIS)

    Jie, Li; Wan-Qing, Yu; Ding, Xu; Feng, Liu; Wei, Wang

    2009-01-01

    Using numerical simulations, we explore the mechanism for propagation of rate signals through a 10-layer feedforward network composed of Hodgkin–Huxley (HH) neurons with sparse connectivity. When white noise is afferent to the input layer, neuronal firing becomes progressively more synchronous in successive layers and synchrony is well developed in deeper layers owing to the feedforward connections between neighboring layers. The synchrony ensures the successful propagation of rate signals through the network when the synaptic conductance is weak. As the synaptic time constant τ syn varies, coherence resonance is observed in the network activity due to the intrinsic property of HH neurons. This makes the output firing rate single-peaked as a function of τ syn , suggesting that the signal propagation can be modulated by the synaptic time constant. These results are consistent with experimental results and advance our understanding of how information is processed in feedforward networks. (cross-disciplinary physics and related areas of science and technology)

  20. Comparison between Two Linear Supervised Learning Machines' Methods with Principle Component Based Methods for the Spectrofluorimetric Determination of Agomelatine and Its Degradants.

    Science.gov (United States)

    Elkhoudary, Mahmoud M; Naguib, Ibrahim A; Abdel Salam, Randa A; Hadad, Ghada M

    2017-05-01

    Four accurate, sensitive and reliable stability indicating chemometric methods were developed for the quantitative determination of Agomelatine (AGM) whether in pure form or in pharmaceutical formulations. Two supervised learning machines' methods; linear artificial neural networks (PC-linANN) preceded by principle component analysis and linear support vector regression (linSVR), were compared with two principle component based methods; principle component regression (PCR) as well as partial least squares (PLS) for the spectrofluorimetric determination of AGM and its degradants. The results showed the benefits behind using linear learning machines' methods and the inherent merits of their algorithms in handling overlapped noisy spectral data especially during the challenging determination of AGM alkaline and acidic degradants (DG1 and DG2). Relative mean squared error of prediction (RMSEP) for the proposed models in the determination of AGM were 1.68, 1.72, 0.68 and 0.22 for PCR, PLS, SVR and PC-linANN; respectively. The results showed the superiority of supervised learning machines' methods over principle component based methods. Besides, the results suggested that linANN is the method of choice for determination of components in low amounts with similar overlapped spectra and narrow linearity range. Comparison between the proposed chemometric models and a reported HPLC method revealed the comparable performance and quantification power of the proposed models.

  1. Top-down modulation on perceptual decision with balanced inhibition through feedforward and feedback inhibitory neurons.

    Directory of Open Access Journals (Sweden)

    Cheng-Te Wang

    Full Text Available Recent physiological studies have shown that neurons in various regions of the central nervous systems continuously receive noisy excitatory and inhibitory synaptic inputs in a balanced and covaried fashion. While this balanced synaptic input (BSI is typically described in terms of maintaining the stability of neural circuits, a number of experimental and theoretical studies have suggested that BSI plays a proactive role in brain functions such as top-down modulation for executive control. Two issues have remained unclear in this picture. First, given the noisy nature of neuronal activities in neural circuits, how do the modulatory effects change if the top-down control implements BSI with different ratios between inhibition and excitation? Second, how is a top-down BSI realized via only excitatory long-range projections in the neocortex? To address the first issue, we systematically tested how the inhibition/excitation ratio affects the accuracy and reaction times of a spiking neural circuit model of perceptual decision. We defined an energy function to characterize the network dynamics, and found that different ratios modulate the energy function of the circuit differently and form two distinct functional modes. To address the second issue, we tested BSI with long-distance projection to inhibitory neurons that are either feedforward or feedback, depending on whether these inhibitory neurons do or do not receive inputs from local excitatory cells, respectively. We found that BSI occurs in both cases. Furthermore, when relying on feedback inhibitory neurons, through the recurrent interactions inside the circuit, BSI dynamically and automatically speeds up the decision by gradually reducing its inhibitory component in the course of a trial when a decision process takes too long.

  2. Top-down modulation on perceptual decision with balanced inhibition through feedforward and feedback inhibitory neurons.

    Science.gov (United States)

    Wang, Cheng-Te; Lee, Chung-Ting; Wang, Xiao-Jing; Lo, Chung-Chuan

    2013-01-01

    Recent physiological studies have shown that neurons in various regions of the central nervous systems continuously receive noisy excitatory and inhibitory synaptic inputs in a balanced and covaried fashion. While this balanced synaptic input (BSI) is typically described in terms of maintaining the stability of neural circuits, a number of experimental and theoretical studies have suggested that BSI plays a proactive role in brain functions such as top-down modulation for executive control. Two issues have remained unclear in this picture. First, given the noisy nature of neuronal activities in neural circuits, how do the modulatory effects change if the top-down control implements BSI with different ratios between inhibition and excitation? Second, how is a top-down BSI realized via only excitatory long-range projections in the neocortex? To address the first issue, we systematically tested how the inhibition/excitation ratio affects the accuracy and reaction times of a spiking neural circuit model of perceptual decision. We defined an energy function to characterize the network dynamics, and found that different ratios modulate the energy function of the circuit differently and form two distinct functional modes. To address the second issue, we tested BSI with long-distance projection to inhibitory neurons that are either feedforward or feedback, depending on whether these inhibitory neurons do or do not receive inputs from local excitatory cells, respectively. We found that BSI occurs in both cases. Furthermore, when relying on feedback inhibitory neurons, through the recurrent interactions inside the circuit, BSI dynamically and automatically speeds up the decision by gradually reducing its inhibitory component in the course of a trial when a decision process takes too long.

  3. A TORC2-Akt feedforward topology underlies HER3 resiliency in HER2-amplified cancers

    Science.gov (United States)

    Amin, Dhara N.; Ahuja, Deepika; Yaswen, Paul; Moasser, Mark M.

    2015-01-01

    The requisite role of HER3 in HER2-amplified cancers is beyond what would be expected as a dimerization partner or effector substrate and it exhibits a substantial degree of resiliency that mitigates the effects of HER2-inhibitor therapies. To better understand the roots of this resiliency, we conducted an in-depth chemical-genetic interrogation of the signaling network downstream of HER3. A unique attribute of these tumors is the deregulation of TORC2. The upstream signals that ordinarily maintain TORC2 signaling are lost in these tumors, and instead TORC2 is driven by Akt. We find that in these cancers HER3 functions as a buffering arm of an Akt-TORC2 feed-forward loop that functions as a self-perpetuating module. This network topology alters the role of HER3 from a conditionally engaged ligand-driven upstream physiologic signaling input to an essential component of a concentric signaling throughput highly competent at preservation of homeostasis. The competence of this signaling topology is evident in its response to perturbation at any of its nodes. Thus a critical pathophysiological event in the evolution of HER2-amplified cancers is the loss of the input signals that normally drive TORC2 signaling, repositioning it under Akt dependency and fundamentally altering the role of HER3. This reprogramming of the downstream network topology is a key aspect in the pathogenesis of HER2-amplified cancers and constitutes a formidable barrier in the targeted therapy of these cancers. PMID:26438156

  4. Fixed structure feedforward controller design exploiting iterative trials: application to a wafer stage and a desktop printer

    NARCIS (Netherlands)

    Meulen, van der S.H.; Tousain, R.L.; Bosgra, O.H.

    2008-01-01

    In this paper, the feedforward controller design problem for high-precision electromechanical servo systems that execute finite time tasks is addressed. The presented procedure combines the selection of the fixed structure of the feedforward controller and the optimization of the controller

  5. Position Control of Servo Systems Using Feed-Forward Friction Compensation

    International Nuclear Information System (INIS)

    Park, Min Gyu; Kim, Han Me; Shin, Jong Min; Kim, Jong Shik

    2009-01-01

    Friction is an important factor for precise position tracking control of servo systems. Servo systems with highly nonlinear friction are sensitive to the variation of operating condition. To overcome this problem, we use the LuGre friction model which can consider dynamic characteristics of friction. The LuGre friction model is used as a feed-forward compensator to improve tracking performance of servo systems. The parameters of the LuGre friction model are identified through experiments. The experimental result shows that the tracking performance of servo systems with higherly nonlinear friction can be improved by using feed-forward friction compensation

  6. 53 MHZ Feedforward beam loading compensation in the Fermilab main injector

    International Nuclear Information System (INIS)

    Joseph E Dey et al.

    2003-01-01

    53 MHz feedforward beam loading compensation is crucial to all operations of the Main Injector. Recently a system using a fundamental frequency down converter mixer, a digital bucket delay module and a fundamental frequency up converter mixer were used to produce a one-turn-delay feedforward signal. This signal was then combined with the low level RF signal to the cavities to cancel the transient beam induced voltage. During operation they have shown consistently over 20 dB reduction in side-band voltage around the fundamental frequency during Proton coalescing and over 14 dB in multi-batch antiproton coalescing

  7. Feedback/feedforward control of hysteresis-compensated piezoelectric actuators for high-speed scanning applications

    International Nuclear Information System (INIS)

    Liu, Yanfang; Shan, Jinjun; Gabbert, Ulrich

    2015-01-01

    This paper presents the control system design for a piezoelectric actuator (PEA) for a high-speed trajectory scanning application. First nonlinear hysteresis is compensated for by using the Maxwell resistive capacitor model. Then the linear dynamics of the hysteresis-compensated piezoelectric actuator are identified. A proportional plus integral (PI) controller is designed based on the linear system, enhanced by feedforward hysteresis compensation. It is found that the feedback controller does not always improve tracking accuracy. When the input frequency exceeds a certain value, feedforward control only may result in better control performance. Experiments are conducted, and the results demonstrate the effectiveness of the proposed control approach. (paper)

  8. Movement goals and feedback and feedforward control mechanisms in speech production.

    Science.gov (United States)

    Perkell, Joseph S

    2012-09-01

    Studies of speech motor control are described that support a theoretical framework in which fundamental control variables for phonemic movements are multi-dimensional regions in auditory and somatosensory spaces. Auditory feedback is used to acquire and maintain auditory goals and in the development and function of feedback and feedforward control mechanisms. Several lines of evidence support the idea that speakers with more acute sensory discrimination acquire more distinct goal regions and therefore produce speech sounds with greater contrast. Feedback modification findings indicate that fluently produced sound sequences are encoded as feedforward commands, and feedback control serves to correct mismatches between expected and produced sensory consequences.

  9. Performance improvement of VAV air conditioning system through feedforward compensation decoupling and genetic algorithm

    International Nuclear Information System (INIS)

    Wang Jun; Wang Yan

    2008-01-01

    VAV (variable air volume) control system has the feature of multi-control loops. While all the control loops are working together, they interfere and influence each other. This paper designs the decoupling compensation unit in VAV system in the method of feedforward compensation. This paper also designs the controller parameters of VAV system by means of inverse deducing and the genetic algorithm. Experimental results demonstrate that the combination of the feedforward compensation decoupling and the controller optimization by genetic algorithm can improve the performance of the VAV control system

  10. Impaired Feedforward Control and Enhanced Feedback Control of Speech in Patients with Cerebellar Degeneration.

    Science.gov (United States)

    Parrell, Benjamin; Agnew, Zarinah; Nagarajan, Srikantan; Houde, John; Ivry, Richard B

    2017-09-20

    The cerebellum has been hypothesized to form a crucial part of the speech motor control network. Evidence for this comes from patients with cerebellar damage, who exhibit a variety of speech deficits, as well as imaging studies showing cerebellar activation during speech production in healthy individuals. To date, the precise role of the cerebellum in speech motor control remains unclear, as it has been implicated in both anticipatory (feedforward) and reactive (feedback) control. Here, we assess both anticipatory and reactive aspects of speech motor control, comparing the performance of patients with cerebellar degeneration and matched controls. Experiment 1 tested feedforward control by examining speech adaptation across trials in response to a consistent perturbation of auditory feedback. Experiment 2 tested feedback control, examining online corrections in response to inconsistent perturbations of auditory feedback. Both male and female patients and controls were tested. The patients were impaired in adapting their feedforward control system relative to controls, exhibiting an attenuated anticipatory response to the perturbation. In contrast, the patients produced even larger compensatory responses than controls, suggesting an increased reliance on sensory feedback to guide speech articulation in this population. Together, these results suggest that the cerebellum is crucial for maintaining accurate feedforward control of speech, but relatively uninvolved in feedback control. SIGNIFICANCE STATEMENT Speech motor control is a complex activity that is thought to rely on both predictive, feedforward control as well as reactive, feedback control. While the cerebellum has been shown to be part of the speech motor control network, its functional contribution to feedback and feedforward control remains controversial. Here, we use real-time auditory perturbations of speech to show that patients with cerebellar degeneration are impaired in adapting feedforward control of

  11. Dynamic Optimization of Feedforward Automatic Gauge Control Based on Extended Kalman Filter

    Institute of Scientific and Technical Information of China (English)

    YANG Bin-hu; YANG Wei-dong; CHEN Lian-gui; QU Lei

    2008-01-01

    Automatic gauge control is an essentially nonlinear process varying with time delay, and stochastically varying input and process noise always influence the target gauge control accuracy. To improve the control capability of feedforward automatic gauge control, Kalman filter was employed to filter the noise signal transferred from one stand to another. The linearized matrix that the Kalman filter algorithm needed was concluded; thus, the feedforward automatic gauge control architecture was dynamically optimized. The theoretical analyses and simulation show that the proposed algorithm is reasonable and effective.

  12. Linkages between motivation, self-efficacy, self-regulated learning and preferences for traditional learning environments or those with an online component

    Directory of Open Access Journals (Sweden)

    Daniel Auld

    2010-10-01

    Full Text Available This study assessed 96 law school students’ preferences for online, hybrid, or traditional learning environments, and their reasons for these preferences, learning strategies, and motivational orientations. A discriminant analysis revealed that non-traditional learning environment familiarity, self-efficacy, and employment status were the strongest predictors of preferences for non-traditional learning environments. Preferences for traditional environments were attributed to students’ familiarity and ability to engage in and foster personal interaction. Preferences for hybrid and online environments were attributed to opportunities for enhanced learning given the convenience and flexible manner in which students with time and familial constraints could access these environments.

  13. Cell-type specific short-term plasticity at auditory nerve synapses controls feed-forward inhibition in the dorsal cochlear nucleus.

    Science.gov (United States)

    Sedlacek, Miloslav; Brenowitz, Stephan D

    2014-01-01

    Feed-forward inhibition (FFI) represents a powerful mechanism by which control of the timing and fidelity of action potentials in local synaptic circuits of various brain regions is achieved. In the cochlear nucleus, the auditory nerve provides excitation to both principal neurons and inhibitory interneurons. Here, we investigated the synaptic circuit associated with fusiform cells (FCs), principal neurons of the dorsal cochlear nucleus (DCN) that receive excitation from auditory nerve fibers and inhibition from tuberculoventral cells (TVCs) on their basal dendrites in the deep layer of DCN. Despite the importance of these inputs in regulating fusiform cell firing behavior, the mechanisms determining the balance of excitation and FFI in this circuit are not well understood. Therefore, we examined the timing and plasticity of auditory nerve driven FFI onto FCs. We find that in some FCs, excitatory and inhibitory components of FFI had the same stimulation thresholds indicating they could be triggered by activation of the same fibers. In other FCs, excitation and inhibition exhibit different stimulus thresholds, suggesting FCs and TVCs might be activated by different sets of fibers. In addition, we find that during repetitive activation, synapses formed by the auditory nerve onto TVCs and FCs exhibit distinct modes of short-term plasticity. Feed-forward inhibitory post-synaptic currents (IPSCs) in FCs exhibit short-term depression because of prominent synaptic depression at the auditory nerve-TVC synapse. Depression of this feedforward inhibitory input causes a shift in the balance of fusiform cell synaptic input towards greater excitation and suggests that fusiform cell spike output will be enhanced by physiological patterns of auditory nerve activity.

  14. Reflexions on feedforward control strategies for a class of sailing vehicles

    DEFF Research Database (Denmark)

    Xiao, Lin; Jouffroy, Jerome

    2010-01-01

    Sailing vehicles, whether they are sea or land-based, share the unique property of exhibiting totally different trajectories depending on where their direction of travel is with respect to the wind. Following our previous work, this paper discusses a few points related to feedforward control...

  15. Subtractive, divisive and non-monotonic gain control in feedforward nets linearized by noise and delays.

    Science.gov (United States)

    Mejias, Jorge F; Payeur, Alexandre; Selin, Erik; Maler, Leonard; Longtin, André

    2014-01-01

    The control of input-to-output mappings, or gain control, is one of the main strategies used by neural networks for the processing and gating of information. Using a spiking neural network model, we studied the gain control induced by a form of inhibitory feedforward circuitry-also known as "open-loop feedback"-, which has been experimentally observed in a cerebellum-like structure in weakly electric fish. We found, both analytically and numerically, that this network displays three different regimes of gain control: subtractive, divisive, and non-monotonic. Subtractive gain control was obtained when noise is very low in the network. Also, it was possible to change from divisive to non-monotonic gain control by simply modulating the strength of the feedforward inhibition, which may be achieved via long-term synaptic plasticity. The particular case of divisive gain control has been previously observed in vivo in weakly electric fish. These gain control regimes were robust to the presence of temporal delays in the inhibitory feedforward pathway, which were found to linearize the input-to-output mappings (or f-I curves) via a novel variability-increasing mechanism. Our findings highlight the feedforward-induced gain control analyzed here as a highly versatile mechanism of information gating in the brain.

  16. Feedforward and Feedback Control in Apraxia of Speech: Effects of Noise Masking on Vowel Production

    Science.gov (United States)

    Maas, Edwin; Mailend, Marja-Liisa; Guenther, Frank H.

    2015-01-01

    Purpose: This study was designed to test two hypotheses about apraxia of speech (AOS) derived from the Directions Into Velocities of Articulators (DIVA) model (Guenther et al., 2006): the feedforward system deficit hypothesis and the feedback system deficit hypothesis. Method: The authors used noise masking to minimize auditory feedback during…

  17. Sliding-mode control combined with improved adaptive feedforward for wafer scanner

    Science.gov (United States)

    Li, Xiaojie; Wang, Yiguang

    2018-03-01

    In this paper, a sliding-mode control method combined with improved adaptive feedforward is proposed for wafer scanner to improve the tracking performance of the closed-loop system. Particularly, In addition to the inverse model, the nonlinear force ripple effect which may degrade the tracking accuracy of permanent magnet linear motor (PMLM) is considered in the proposed method. The dominant position periodicity of force ripple is determined by using the Fast Fourier Transform (FFT) analysis for experimental data and the improved feedforward control is achieved by the online recursive least-squares (RLS) estimation of the inverse model and the force ripple. The improved adaptive feedforward is given in a general form of nth-order model with force ripple effect. This proposed method is motivated by the motion controller design of the long-stroke PMLM and short-stroke voice coil motor for wafer scanner. The stability of the closed-loop control system and the convergence of the motion tracking are guaranteed by the proposed sliding-mode feedback and adaptive feedforward methods theoretically. Comparative experiments on a precision linear motion platform can verify the correctness and effectiveness of the proposed method. The experimental results show that comparing to traditional method the proposed one has better performance of rapidity and robustness, especially for high speed motion trajectory. And, the improvements on both tracking accuracy and settling time can be achieved.

  18. A novel controller for bipedal locomotion integrating feed-forward and feedback mechanisms

    NARCIS (Netherlands)

    Xiong, Xiaofeng; Sartori, Massimo; Dosen, Strahinja; González-Vargas, José; Wörgötter, Florentin; Farina, Dario; Ibanez, J.; González-Vargas, J.; Azorin, J.M.; Akay, M.; Pons, J.L.

    2017-01-01

    It has been recognized that bipedal locomotion is controlled using feed-forward (e.g., patterned) and feedback (e.g., reflex) control schemes. However, most current controllers fail to integrate the two schemes to simplify speed control of bipedal locomotion. To solve this problem, we here propose a

  19. Control of a local neural network by feedforward and feedback inhibition

    NARCIS (Netherlands)

    Remme, M.W.H.; Wadman, W.J.

    2004-01-01

    The signal transfer of a neuronal network is shaped by the local interactions between the excitatory principal cells and the inhibitory interneurons. We investigated with a simple lumped model how feedforward and feedback inhibition in.uence the steady-state network signal transfer. We analyze how

  20. Performance trade-offs in disturbance feedforward compensation of active hard-mounted vibration isolators

    NARCIS (Netherlands)

    Beijen, M.A.; Heertjes, M.F.; Butler, H.; Steinbuch, M.

    2015-01-01

    With disturbance feedforward compensation (DFC), input disturbances are measured and compensated to cancel the effect of the disturbance. Perfect cancellation is not possible in practice due to the causal nature of DFC, in which the compensation generally comes too late. Therefore, non-perfect plant

  1. Subtractive, divisive and non-monotonic gain control in feedforward nets linearized by noise and delays

    Directory of Open Access Journals (Sweden)

    Jorge F Mejias

    2014-02-01

    Full Text Available The control of input-to-output mappings, or gain control, is one of the main strategies used by neural networks for the processing and gating of information. Using a spiking neural network model, we studied the gain control induced by a form of inhibitory feedforward circuitry — also known as ’open-loop feedback’ —, which has been experimentally observed in a cerebellum-like structure in weakly electric fish. We found, both analytically and numerically, that this network displays three different regimes of gain control: subtractive, divisive, and non-monotonic. Subtractive gain control was obtained when noise is very low in the network. Also, it was possible to change from divisive to non-monotonic gain control by simply modulating the strength of the feedforward inhibition, which may be achieved via long-term synaptic plasticity. The particular case of divisive gain control has been previously observed in vivo in weakly electric fish. These gain control regimes were robust to the presence of temporal delays in the inhibitory feedforward pathway, which were found to linearize the input-to-output mappings (or f-I curves via a novel variability-increasing mechanism. Our findings highlight the feedforward-induced gain control analyzed here as a highly versatile mechanism of information gating in the brain.

  2. Global output feedback stabilisation of stochastic high-order feedforward nonlinear systems with time-delay

    Science.gov (United States)

    Zhang, Kemei; Zhao, Cong-Ran; Xie, Xue-Jun

    2015-12-01

    This paper considers the problem of output feedback stabilisation for stochastic high-order feedforward nonlinear systems with time-varying delay. By using the homogeneous domination theory and solving several troublesome obstacles in the design and analysis, an output feedback controller is constructed to drive the closed-loop system globally asymptotically stable in probability.

  3. A low-complexity feed-forward I/Q imbalance compensation algorithm

    NARCIS (Netherlands)

    Moseley, N.A.; Slump, Cornelis H.

    2006-01-01

    This paper presents a low-complexity adaptive feed- forward I/Q imbalance compensation algorithm. The feed-forward so- lution has guaranteed stability. Due to its blind nature the algorithm is easily incorporated into an existing receiver design. The algorithm uses three estimators to obtain the

  4. Noise destroys feedback enhanced figure-ground segmentation but not feedforward figure-ground segmentation

    Science.gov (United States)

    Romeo, August; Arall, Marina; Supèr, Hans

    2012-01-01

    Figure-ground (FG) segmentation is the separation of visual information into background and foreground objects. In the visual cortex, FG responses are observed in the late stimulus response period, when neurons fire in tonic mode, and are accompanied by a switch in cortical state. When such a switch does not occur, FG segmentation fails. Currently, it is not known what happens in the brain on such occasions. A biologically plausible feedforward spiking neuron model was previously devised that performed FG segmentation successfully. After incorporating feedback the FG signal was enhanced, which was accompanied by a change in spiking regime. In a feedforward model neurons respond in a bursting mode whereas in the feedback model neurons fired in tonic mode. It is known that bursts can overcome noise, while tonic firing appears to be much more sensitive to noise. In the present study, we try to elucidate how the presence of noise can impair FG segmentation, and to what extent the feedforward and feedback pathways can overcome noise. We show that noise specifically destroys the feedback enhanced FG segmentation and leaves the feedforward FG segmentation largely intact. Our results predict that noise produces failure in FG perception. PMID:22934028

  5. Different glutamate receptors convey feedforward and recurrent processing in macaque V1

    NARCIS (Netherlands)

    Self, M.W.; Kooijmans, R.N.; Super, H.; Lamme, V.A.F.; Roelfsema, P.R.

    2012-01-01

    Neurons in the primary visual cortex (V1) receive feedforward input from the thalamus, which shapes receptive-field properties. They additionally receive recurrent inputs via horizontal connections within V1 and feedback from higher visual areas that are thought to be important for conscious visual

  6. Cortical feedback signals generalise across different spatial frequencies of feedforward inputs.

    Science.gov (United States)

    Revina, Yulia; Petro, Lucy S; Muckli, Lars

    2017-09-22

    Visual processing in cortex relies on feedback projections contextualising feedforward information flow. Primary visual cortex (V1) has small receptive fields and processes feedforward information at a fine-grained spatial scale, whereas higher visual areas have larger, spatially invariant receptive fields. Therefore, feedback could provide coarse information about the global scene structure or alternatively recover fine-grained structure by targeting small receptive fields in V1. We tested if feedback signals generalise across different spatial frequencies of feedforward inputs, or if they are tuned to the spatial scale of the visual scene. Using a partial occlusion paradigm, functional magnetic resonance imaging (fMRI) and multivoxel pattern analysis (MVPA) we investigated whether feedback to V1 contains coarse or fine-grained information by manipulating the spatial frequency of the scene surround outside an occluded image portion. We show that feedback transmits both coarse and fine-grained information as it carries information about both low (LSF) and high spatial frequencies (HSF). Further, feedback signals containing LSF information are similar to feedback signals containing HSF information, even without a large overlap in spatial frequency bands of the HSF and LSF scenes. Lastly, we found that feedback carries similar information about the spatial frequency band across different scenes. We conclude that cortical feedback signals contain information which generalises across different spatial frequencies of feedforward inputs. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

  7. Investigating transfer gate potential barrier by feed-forward effect measurement

    NARCIS (Netherlands)

    Xu, Y.; Ge, X.; Theuwissen, A.J.P.

    2015-01-01

    In a 4T pixel, the transfer gate (TG) “OFF” surface potential is one of the important parameters, which determines the pinned photodiode (PPD) full well capacity. The feed-forward effect measurement is a powerful tool to characterize the relationship of the PPD injection potential and the

  8. Active gust load alleviation system for flexible aircraft: Mixed feedforward/feedback approach

    DEFF Research Database (Denmark)

    Alam, Mushfiqul; Hromcik, Martin; Hanis, Tomas

    2015-01-01

    Lightweight flexible blended-wing-body (BWB) aircraft concept seems as a highly promising configuration for future high capacity airliners which suffers from reduced stiffness for disturbance loads such as gusts. A robust feedforward gust load alleviation system (GLAS) was developed to alleviate ...

  9. Causal feedforward control of a stochastically excited fuselage structure with active sidewall panel.

    Science.gov (United States)

    Misol, Malte; Haase, Thomas; Monner, Hans Peter; Sinapius, Michael

    2014-10-01

    This paper provides experimental results of an aircraft-relevant double panel structure mounted in a sound transmission loss facility. The primary structure of the double panel system is excited either by a stochastic point force or by a diffuse sound field synthesized in the reverberation room of the transmission loss facility. The secondary structure, which is connected to the frames of the primary structure, is augmented by actuators and sensors implementing an active feedforward control system. Special emphasis is placed on the causality of the active feedforward control system and its implications on the disturbance rejection at the error sensors. The coherence of the sensor signals is analyzed for the two different disturbance excitations. Experimental results are presented regarding the causality, coherence, and disturbance rejection of the active feedforward control system. Furthermore, the sound transmission loss of the double panel system is evaluated for different configurations of the active system. A principal result of this work is the evidence that it is possible to strongly influence the transmission of stochastic disturbance sources through double panel configurations by means of an active feedforward control system.

  10. Comparative experiments regarding approaches to feedforward hysteresis compensation for piezoceramic actuators

    International Nuclear Information System (INIS)

    Gu, Guo-Ying; Zhu, Li-Min

    2014-01-01

    Piezoceramic actuators (PCAs) are desired devices in many micro/nano-positioning applications. The performance of PCA-based applications is severely limited by the presence of hysteresis nonlinearity. To remedy the hysteresis nonlinearity in such systems, feedforward hysteresis compensation is the most common technique. In the literature, many different feedforward hysteresis compensation approaches have been developed, but there are no comparative studies of these approaches. Focusing on the modified Prandtl-Ishlinskii model (MPIM) for asymmetric hysteresis description of piezoceramic actuators, three feedforward hysteresis compensation approaches—inverse hysteresis compensation (IHC), without inverse hysteresis compensation (WIHC), and direct inverse hysteresis compensation (DIHC)—are developed and compared in this paper. Extensive comparative experiments were conducted on a PCA-actuated stage to verify the effectiveness of the three different feedforward control approaches to hysteresis compensation. The experimental results show that the performances among the three approaches are rather similar, and the main differences among them are due to the specific implementation of each approach. (paper)

  11. Proinflammatory Cytokine Infusion Attenuates LH's Feedforward on Testosterone Secretion: Modulation by Age.

    Science.gov (United States)

    Veldhuis, Johannes; Yang, Rebecca; Roelfsema, Ferdinand; Takahashi, Paul

    2016-02-01

    In the experimental animal, inflammatory signals quench LH's feedforward drive of testosterone (T) secretion and appear to impair GnRH-LH output. The degree to which such suppressive effects operate in the human is not known. To test the hypothesis that IL-2 impairs LH's feedforward drive on T and T's feedback inhibition of LH secretion in healthy men. Mayo Center for Translational Science Activities. A total of 35 healthy men, 17 young and 18 older. Randomized prospective double-blind saline-controlled study of IL-2 infusion in 2 doses with concurrent 10-minute blood sampling for 24 hours. Deconvolution analysis of LH and T secretion. After saline injection, older compared with young men exhibited reduced LH feedforward drive on T secretion (P enforces biochemical hypogonadism, viz, combined feedforward block and feedback amplification; and 2) unequal absolute inhibition of T and LH secretion by IL-2 in young and older men. These outcomes establish that the male gonadal axis is susceptible to dual-site suppression by a prototypic inflammatory mediator. Thus, we postulate that selected ILs might also enforce male hypogonadism in chronic systemic inflammation.

  12. Implementation of an Automated Grading System with an Adaptive Learning Component to Affect Student Feedback and Response Time

    Science.gov (United States)

    Matthews, Kevin; Janicki, Thomas; He, Ling; Patterson, Laurie

    2012-01-01

    This research focuses on the development and implementation of an adaptive learning and grading system with a goal to increase the effectiveness and quality of feedback to students. By utilizing various concepts from established learning theories, the goal of this research is to improve the quantity, quality, and speed of feedback as it pertains…

  13. Computer Simulation Tests of Feedback Error Learning Controller with IDM and ISM for Functional Electrical Stimulation in Wrist Joint Control

    OpenAIRE

    Watanabe, Takashi; Sugi, Yoshihiro

    2010-01-01

    Feedforward controller would be useful for hybrid Functional Electrical Stimulation (FES) system using powered orthotic devices. In this paper, Feedback Error Learning (FEL) controller for FES (FEL-FES controller) was examined using an inverse statics model (ISM) with an inverse dynamics model (IDM) to realize a feedforward FES controller. For FES application, the ISM was tested in learning off line using training data obtained by PID control of very slow movements. Computer simulation tests ...

  14. A combined feedforward and feedback control scheme for low-ripple fast-response switchmode magnet power supplies

    International Nuclear Information System (INIS)

    Jin, H.; Dewan, S.B.

    1994-01-01

    In this paper, a new feedforward technique is introduced, and a combined feedforward/feedback control scheme is applied to switchmode magnet power supplies for low-ripple fast-response performance. The purposes of the feedforward technique are two-fold: to reduce the effect of source variations and low-order harmonics, and to improve the reference tracking ability of the system. The algorithm of the proposed control scheme is presented in the paper, and results of a two-quadrant system are provided to verify the concept

  15. AUTOMOTIVE DIESEL MAINTENANCE 1. UNIT XXVI, I--CATERPILLAR LUBRICATION SYSTEMS AND COMPONENTS, II--LEARNING ABOUT BRAKES (PART I).

    Science.gov (United States)

    Minnesota State Dept. of Education, St. Paul. Div. of Vocational and Technical Education.

    THIS MODULE OF A 30-MODULE COURSE IS DESIGNED TO DEVELOP AN UNDERSTANDING OF THE FUNCTIONS OF DIESEL ENGINE LUBRICATION SYSTEMS AND COMPONENTS AND THE PRINCIPLES OF OPERATION OF BRAKE SYSTEMS USED ON DIESEL POWERED VEHICLES. TOPICS ARE (1) THE NEED FOR OIL, (2) SERVICE CLASSIFICATION OF OILS, (3) CATERPILLAR LUBRICATION SYSTEM COMPONENTS (4)…

  16. Wind Speed Preview Measurement and Estimation for Feedforward Control of Wind Turbines

    Science.gov (United States)

    Simley, Eric J.

    Wind turbines typically rely on feedback controllers to maximize power capture in below-rated conditions and regulate rotor speed during above-rated operation. However, measurements of the approaching wind provided by Light Detection and Ranging (lidar) can be used as part of a preview-based, or feedforward, control system in order to improve rotor speed regulation and reduce structural loads. But the effectiveness of preview-based control depends on how accurately lidar can measure the wind that will interact with the turbine. In this thesis, lidar measurement error is determined using a statistical frequency-domain wind field model including wind evolution, or the change in turbulent wind speeds between the time they are measured and when they reach the turbine. Parameters of the National Renewable Energy Laboratory (NREL) 5-MW reference turbine model are used to determine measurement error for a hub-mounted circularly-scanning lidar scenario, based on commercially-available technology, designed to estimate rotor effective uniform and shear wind speed components. By combining the wind field model, lidar model, and turbine parameters, the optimal lidar scan radius and preview distance that yield the minimum mean square measurement error, as well as the resulting minimum achievable error, are found for a variety of wind conditions. With optimized scan scenarios, it is found that relatively low measurement error can be achieved, but the attainable measurement error largely depends on the wind conditions. In addition, the impact of the induction zone, the region upstream of the turbine where the approaching wind speeds are reduced, as well as turbine yaw error on measurement quality is analyzed. In order to minimize the mean square measurement error, an optimal measurement prefilter is employed, which depends on statistics of the correlation between the preview measurements and the wind that interacts with the turbine. However, because the wind speeds encountered by

  17. Feedforward Control of Gear Mesh Vibration Using Piezoelectric Actuators

    Directory of Open Access Journals (Sweden)

    Gerald T. Montague

    1994-01-01

    Full Text Available This article presents a novel means for suppressing gear mesh related vibrations. The key components in this approach are piezoelectric actuators and a high-frequency, analog feed forward controller. Test results are presented and show up to a 70% reduction in gear mesh acceleration and vibration control up to 4500 Hz. The principle of the approach is explained by an analysis of a harmonically excited, general linear vibratory system.

  18. Are All Program Elements Created Equal? Relations Between Specific Social and Emotional Learning Components and Teacher-Student Classroom Interaction Quality.

    Science.gov (United States)

    Abry, Tashia; Rimm-Kaufman, Sara E; Curby, Timothy W

    2017-02-01

    School-based social and emotional learning (SEL) programs are presented to educators with little understanding of the program components that have the greatest leverage for improving targeted outcomes. Conducted in the context of a randomized controlled trial, the present study used variation in treatment teachers' (N = 143) implementation of four core components of the Responsive Classroom approach to examine relations between each component and the quality of teachers' emotional, organizational, and instructional interactions in third, fourth, and fifth grade classrooms (controlling for pre-intervention interaction quality and other covariates). We also examined the extent to which these relations varied as a function of teachers' baseline levels of interaction quality. Indices of teachers' implementation of Morning Meeting, Rule Creation, Interactive Modeling, and Academic Choice were derived from a combination of teacher-reported surveys and classroom observations. Ratings of teacher-student classroom interactions were aggregated across five observations conducted throughout the school year. Structural path models indicated that teachers' use of Morning Meeting and Academic Choice related to higher levels of emotionally supportive interactions; Academic Choice also related to higher levels of instructional interactions. In addition, teachers' baseline interaction quality moderated several associations such that the strongest relations between RC component use and interaction quality emerged for teachers with the lowest baseline interaction quality. Results highlight the value of examining individual program components toward the identification of program active ingredients that can inform intervention optimization and teacher professional development.

  19. Time-optimal control of nuclear reactor power with adaptive proportional- integral-feedforward gains

    International Nuclear Information System (INIS)

    Park, Moon Ghu; Cho, Nam Zin

    1993-01-01

    A time-optimal control method which consists of coarse and fine control stages is described here. During the coarse control stage, the maximum control effort (time-optimal) is used to direct the system toward the switching boundary which is set near the desired power level. At this boundary, the controller is switched to the fine control stage in which an adaptive proportional-integral-feedforward (PIF) controller is used to compensate for any unmodeled reactivity feedback effects. This fine control is also introduced to obtain a constructive method for determining the (adaptive) feedback gains against the sampling effect. The feedforward control term is included to suppress the over-or undershoot. The estimation and feedback of the temperature-induced reactivity is also discussed

  20. Feedback enhances feedforward figure-ground segmentation by changing firing mode.

    Science.gov (United States)

    Supèr, Hans; Romeo, August

    2011-01-01

    In the visual cortex, feedback projections are conjectured to be crucial in figure-ground segregation. However, the precise function of feedback herein is unclear. Here we tested a hypothetical model of reentrant feedback. We used a previous developed 2-layered feedforward spiking network that is able to segregate figure from ground and included feedback connections. Our computer model data show that without feedback, neurons respond with regular low-frequency (∼9 Hz) bursting to a figure-ground stimulus. After including feedback the firing pattern changed into a regular (tonic) spiking pattern. In this state, we found an extra enhancement of figure responses and a further suppression of background responses resulting in a stronger figure-ground signal. Such push-pull effect was confirmed by comparing the figure-ground responses with the responses to a homogenous texture. We propose that feedback controls figure-ground segregation by influencing the neural firing patterns of feedforward projecting neurons.

  1. Feedback enhances feedforward figure-ground segmentation by changing firing mode.

    Directory of Open Access Journals (Sweden)

    Hans Supèr

    Full Text Available In the visual cortex, feedback projections are conjectured to be crucial in figure-ground segregation. However, the precise function of feedback herein is unclear. Here we tested a hypothetical model of reentrant feedback. We used a previous developed 2-layered feedforward spiking network that is able to segregate figure from ground and included feedback connections. Our computer model data show that without feedback, neurons respond with regular low-frequency (∼9 Hz bursting to a figure-ground stimulus. After including feedback the firing pattern changed into a regular (tonic spiking pattern. In this state, we found an extra enhancement of figure responses and a further suppression of background responses resulting in a stronger figure-ground signal. Such push-pull effect was confirmed by comparing the figure-ground responses with the responses to a homogenous texture. We propose that feedback controls figure-ground segregation by influencing the neural firing patterns of feedforward projecting neurons.

  2. A mixed incoherent feed-forward loop contributes to the regulation of bacterial photosynthesis genes.

    Science.gov (United States)

    Mank, Nils N; Berghoff, Bork A; Klug, Gabriele

    2013-03-01

    Living cells use a variety of regulatory network motifs for accurate gene expression in response to changes in their environment or during differentiation processes. In Rhodobacter sphaeroides, a complex regulatory network controls expression of photosynthesis genes to guarantee optimal energy supply on one hand and to avoid photooxidative stress on the other hand. Recently, we identified a mixed incoherent feed-forward loop comprising the transcription factor PrrA, the sRNA PcrZ and photosynthesis target genes as part of this regulatory network. This point-of-view provides a comparison to other described feed-forward loops and discusses the physiological relevance of PcrZ in more detail.

  3. Prior-knowledge-based feedforward network simulation of true boiling point curve of crude oil.

    Science.gov (United States)

    Chen, C W; Chen, D Z

    2001-11-01

    Theoretical results and practical experience indicate that feedforward networks can approximate a wide class of functional relationships very well. This property is exploited in modeling chemical processes. Given finite and noisy training data, it is important to encode the prior knowledge in neural networks to improve the fit precision and the prediction ability of the model. In this paper, as to the three-layer feedforward networks and the monotonic constraint, the unconstrained method, Joerding's penalty function method, the interpolation method, and the constrained optimization method are analyzed first. Then two novel methods, the exponential weight method and the adaptive method, are proposed. These methods are applied in simulating the true boiling point curve of a crude oil with the condition of increasing monotonicity. The simulation experimental results show that the network models trained by the novel methods are good at approximating the actual process. Finally, all these methods are discussed and compared with each other.

  4. A novel approach to error function minimization for feedforward neural networks

    International Nuclear Information System (INIS)

    Sinkus, R.

    1995-01-01

    Feedforward neural networks with error backpropagation are widely applied to pattern recognition. One general problem encountered with this type of neural networks is the uncertainty, whether the minimization procedure has converged to a global minimum of the cost function. To overcome this problem a novel approach to minimize the error function is presented. It allows to monitor the approach to the global minimum and as an outcome several ambiguities related to the choice of free parameters of the minimization procedure are removed. (orig.)

  5. Quantifying feedforward control: a linear scaling model for fingertip forces and object weight.

    Science.gov (United States)

    Lu, Ying; Bilaloglu, Seda; Aluru, Viswanath; Raghavan, Preeti

    2015-07-01

    The ability to predict the optimal fingertip forces according to object properties before the object is lifted is known as feedforward control, and it is thought to occur due to the formation of internal representations of the object's properties. The control of fingertip forces to objects of different weights has been studied extensively by using a custom-made grip device instrumented with force sensors. Feedforward control is measured by the rate of change of the vertical (load) force before the object is lifted. However, the precise relationship between the rate of change of load force and object weight and how it varies across healthy individuals in a population is not clearly understood. Using sets of 10 different weights, we have shown that there is a log-linear relationship between the fingertip load force rates and weight among neurologically intact individuals. We found that after one practice lift, as the weight increased, the peak load force rate (PLFR) increased by a fixed percentage, and this proportionality was common among the healthy subjects. However, at any given weight, the level of PLFR varied across individuals and was related to the efficiency of the muscles involved in lifting the object, in this case the wrist and finger extensor muscles. These results quantify feedforward control during grasp and lift among healthy individuals and provide new benchmarks to interpret data from neurologically impaired populations as well as a means to assess the effect of interventions on restoration of feedforward control and its relationship to muscular control. Copyright © 2015 the American Physiological Society.

  6. Further results on global state feedback stabilization of nonlinear high-order feedforward systems.

    Science.gov (United States)

    Xie, Xue-Jun; Zhang, Xing-Hui

    2014-03-01

    In this paper, by introducing a combined method of sign function, homogeneous domination and adding a power integrator, and overcoming several troublesome obstacles in the design and analysis, the problem of state feedback control for a class of nonlinear high-order feedforward systems with the nonlinearity's order being relaxed to an interval rather than a fixed point is solved. Copyright © 2013 ISA. Published by Elsevier Ltd. All rights reserved.

  7. Evaluation of the Performance of Feedforward and Recurrent Neural Networks in Active Cancellation of Sound Noise

    OpenAIRE

    Mehrshad Salmasi; Homayoun Mahdavi-Nasab

    2012-01-01

    Active noise control is based on the destructive interference between the primary noise and generated noise from the secondary source. An antinoise of equal amplitude and opposite phase is generated and combined with the primary noise. In this paper, performance of the neural networks is evaluated in active cancellation of sound noise. For this reason, feedforward and recurrent neural networks are designed and trained. After training, performance of the feedforwrad and recurrent networks in n...

  8. Neural dynamics of feedforward and feedback processing in figure-ground segregation.

    Science.gov (United States)

    Layton, Oliver W; Mingolla, Ennio; Yazdanbakhsh, Arash

    2014-01-01

    Determining whether a region belongs to the interior or exterior of a shape (figure-ground segregation) is a core competency of the primate brain, yet the underlying mechanisms are not well understood. Many models assume that figure-ground segregation occurs by assembling progressively more complex representations through feedforward connections, with feedback playing only a modulatory role. We present a dynamical model of figure-ground segregation in the primate ventral stream wherein feedback plays a crucial role in disambiguating a figure's interior and exterior. We introduce a processing strategy whereby jitter in RF center locations and variation in RF sizes is exploited to enhance and suppress neural activity inside and outside of figures, respectively. Feedforward projections emanate from units that model cells in V4 known to respond to the curvature of boundary contours (curved contour cells), and feedback projections from units predicted to exist in IT that strategically group neurons with different RF sizes and RF center locations (teardrop cells). Neurons (convex cells) that preferentially respond when centered on a figure dynamically balance feedforward (bottom-up) information and feedback from higher visual areas. The activation is enhanced when an interior portion of a figure is in the RF via feedback from units that detect closure in the boundary contours of a figure. Our model produces maximal activity along the medial axis of well-known figures with and without concavities, and inside algorithmically generated shapes. Our results suggest that the dynamic balancing of feedforward signals with the specific feedback mechanisms proposed by the model is crucial for figure-ground segregation.

  9. A Feedforward Control Approach to the Local Navigation Problem for Autonomous Vehicles

    Science.gov (United States)

    1994-05-02

    AD-A282 787 " A Feedforward Control Approach to the Local Navigation Problem for Autonomous Vehicles Alonzo Kelly CMU-RI-TR-94-17 The Robotics...follow, or a direction to prefer, it cannot generate its own strategic goals. Therefore, it solves the local planning problem for autonomous vehicles . The... autonomous vehicles . It is intelligent because it uses range images that are generated from either a laser rangefinder or a stereo triangulation

  10. Neural Dynamics of Feedforward and Feedback Processing in Figure-Ground Segregation

    Directory of Open Access Journals (Sweden)

    Oliver W. Layton

    2014-09-01

    Full Text Available Determining whether a region belongs to the interior or exterior of a shape (figure-ground segregation is a core competency of the primate brain, yet the underlying mechanisms are not well understood. Many models assume that figure-ground segregation occurs by assembling progressively more complex representations through feedforward connections, with feedback playing only a modulatory role. We present a dynamical model of figure-ground segregation in the primate ventral stream wherein feedback plays a crucial role in disambiguating a figure’s interior and exterior. We introduce a processing strategy whereby jitter in RF center locations and variation in RF sizes is exploited to enhance and suppress neural activity inside and outside of figures, respectively. Feedforward projections emanate from units that model cells in V4 known to respond to the curvature of boundary contours (curved contour cells, and feedback projections from units predicted to exist in IT that strategically group neurons with different RF sizes and RF center locations (teardrop cells. Neurons (convex cells that preferentially respond when centered on a figure dynamically balance feedforward (bottom-up information and feedback from higher visual areas. The activation is enhanced when an interior portion of a figure is in the RF via feedback from units that detect closure in the boundary contours of a figure. Our model produces maximal activity along the medial axis of well-known figures with and without concavities, and inside algorithmically generated shapes. Our results suggest that the dynamic balancing of feedforward signals with the specific feedback mechanisms proposed by the model is crucial for figure-ground segregation.

  11. Neural Dynamics of Feedforward and Feedback Processing in Figure-Ground Segregation

    OpenAIRE

    Oliver W. Layton; Ennio eMingolla; Arash eYazdanbakhsh

    2014-01-01

    Determining whether a region belongs to the interior or exterior of a shape (figure-ground segregation) is a core competency of the primate brain, yet the underlying mechanisms are not well understood. Many models assume that figure-ground segregation occurs by assembling progressively more complex representations through feedforward connections, with feedback playing only a modulatory role. We present a dynamical model of figure-ground segregation in the primate ventral stream wherein feedba...

  12. Neural dynamics of feedforward and feedback processing in figure-ground segregation

    Science.gov (United States)

    Layton, Oliver W.; Mingolla, Ennio; Yazdanbakhsh, Arash

    2014-01-01

    Determining whether a region belongs to the interior or exterior of a shape (figure-ground segregation) is a core competency of the primate brain, yet the underlying mechanisms are not well understood. Many models assume that figure-ground segregation occurs by assembling progressively more complex representations through feedforward connections, with feedback playing only a modulatory role. We present a dynamical model of figure-ground segregation in the primate ventral stream wherein feedback plays a crucial role in disambiguating a figure's interior and exterior. We introduce a processing strategy whereby jitter in RF center locations and variation in RF sizes is exploited to enhance and suppress neural activity inside and outside of figures, respectively. Feedforward projections emanate from units that model cells in V4 known to respond to the curvature of boundary contours (curved contour cells), and feedback projections from units predicted to exist in IT that strategically group neurons with different RF sizes and RF center locations (teardrop cells). Neurons (convex cells) that preferentially respond when centered on a figure dynamically balance feedforward (bottom-up) information and feedback from higher visual areas. The activation is enhanced when an interior portion of a figure is in the RF via feedback from units that detect closure in the boundary contours of a figure. Our model produces maximal activity along the medial axis of well-known figures with and without concavities, and inside algorithmically generated shapes. Our results suggest that the dynamic balancing of feedforward signals with the specific feedback mechanisms proposed by the model is crucial for figure-ground segregation. PMID:25346703

  13. Breast cancer detection via Hu moment invariant and feedforward neural network

    Science.gov (United States)

    Zhang, Xiaowei; Yang, Jiquan; Nguyen, Elijah

    2018-04-01

    One of eight women can get breast cancer during all her life. This study used Hu moment invariant and feedforward neural network to diagnose breast cancer. With the help of K-fold cross validation, we can test the out-of-sample accuracy of our method. Finally, we found that our methods can improve the accuracy of detecting breast cancer and reduce the difficulty of judging.

  14. Selection of W-pair-production in DELPHI with feed-forward neural networks

    International Nuclear Information System (INIS)

    Becks, K.-H.; Buschmann, P.; Drees, J.; Mueller, U.; Wahlen, H.

    2001-01-01

    Since 1998 feed-forward networks have been applied for the separation of hadronic WW-decays from background processes measured by the DELPHI collaboration at different center-of-mass energies of the Large Electron Positron collider at CERN. Prior to the publication of the 189 GeV results intensive studies of systematic effects and uncertainties were performed. The methods and results will be discussed and compared to standard selection procedures

  15. Mixed signal learning by spike correlation propagation in feedback inhibitory circuits.

    Directory of Open Access Journals (Sweden)

    Naoki Hiratani

    2015-04-01

    Full Text Available The brain can learn and detect mixed input signals masked by various types of noise, and spike-timing-dependent plasticity (STDP is the candidate synaptic level mechanism. Because sensory inputs typically have spike correlation, and local circuits have dense feedback connections, input spikes cause the propagation of spike correlation in lateral circuits; however, it is largely unknown how this secondary correlation generated by lateral circuits influences learning processes through STDP, or whether it is beneficial to achieve efficient spike-based learning from uncertain stimuli. To explore the answers to these questions, we construct models of feedforward networks with lateral inhibitory circuits and study how propagated correlation influences STDP learning, and what kind of learning algorithm such circuits achieve. We derive analytical conditions at which neurons detect minor signals with STDP, and show that depending on the origin of the noise, different correlation timescales are useful for learning. In particular, we show that non-precise spike correlation is beneficial for learning in the presence of cross-talk noise. We also show that by considering excitatory and inhibitory STDP at lateral connections, the circuit can acquire a lateral structure optimal for signal detection. In addition, we demonstrate that the model performs blind source separation in a manner similar to the sequential sampling approximation of the Bayesian independent component analysis algorithm. Our results provide a basic understanding of STDP learning in feedback circuits by integrating analyses from both dynamical systems and information theory.

  16. On the use of the autocorrelation and covariance methods for feedforward control of transverse angle and position jitter in linear particle beam accelerators

    International Nuclear Information System (INIS)

    Barr, D.S.

    1994-01-01

    It is desired to design a predictive feedforward transverse jitter control system to control both angle and position jitter in pulsed linear accelerators. Such a system will increase the accuracy and bandwidth of correction over that of currently available feedback correction systems. Intrapulse correction is performed. An offline process actually ''learns'' the properties of the jitter, and uses these properties to apply correction to the beam. The correction weights calculated offline are downloaded to a real-time analog correction system between macropulses. Jitter data were taken at the Los Alamos National Laboratory (LANL) Ground Test Accelerator (GTA) telescope experiment at Argonne National Laboratory (ANL). The experiment consisted of the LANL telescope connected to the ANL ZGS proton source and linac. A simulation of the correction system using this data was shown to decrease the average rms jitter by a factor of two over that of a comparable standard feedback correction system. The system also improved the correction bandwidth

  17. Feedforward neural network model estimating pollutant removal process within mesophilic upflow anaerobic sludge blanket bioreactor treating industrial starch processing wastewater.

    Science.gov (United States)

    Antwi, Philip; Li, Jianzheng; Meng, Jia; Deng, Kaiwen; Koblah Quashie, Frank; Li, Jiuling; Opoku Boadi, Portia

    2018-06-01

    In this a, three-layered feedforward-backpropagation artificial neural network (BPANN) model was developed and employed to evaluate COD removal an upflow anaerobic sludge blanket (UASB) reactor treating industrial starch processing wastewater. At the end of UASB operation, microbial community characterization revealed satisfactory composition of microbes whereas morphology depicted rod-shaped archaea. pH, COD, NH 4 + , VFA, OLR and biogas yield were selected by principal component analysis and used as input variables. Whilst tangent sigmoid function (tansig) and linear function (purelin) were assigned as activation functions at the hidden-layer and output-layer, respectively, optimum BPANN architecture was achieved with Levenberg-Marquardt algorithm (trainlm) after eleven training algorithms had been tested. Based on performance indicators such the mean squared errors, fractional variance, index of agreement and coefficient of determination (R 2 ), the BPANN model demonstrated significant performance with R 2 reaching 87%. The study revealed that, control and optimization of an anaerobic digestion process with BPANN model was feasible. Copyright © 2018 Elsevier Ltd. All rights reserved.

  18. Diagnosis of Alzheimer’s Disease Using Dual-Tree Complex Wavelet Transform, PCA, and Feed-Forward Neural Network

    Directory of Open Access Journals (Sweden)

    Debesh Jha

    2017-01-01

    Full Text Available Background. Error-free diagnosis of Alzheimer’s disease (AD from healthy control (HC patients at an early stage of the disease is a major concern, because information about the condition’s severity and developmental risks present allows AD sufferer to take precautionary measures before irreversible brain damage occurs. Recently, there has been great interest in computer-aided diagnosis in magnetic resonance image (MRI classification. However, distinguishing between Alzheimer’s brain data and healthy brain data in older adults (age > 60 is challenging because of their highly similar brain patterns and image intensities. Recently, cutting-edge feature extraction technologies have found extensive application in numerous fields, including medical image analysis. Here, we propose a dual-tree complex wavelet transform (DTCWT for extracting features from an image. The dimensionality of feature vector is reduced by using principal component analysis (PCA. The reduced feature vector is sent to feed-forward neural network (FNN to distinguish AD and HC from the input MR images. These proposed and implemented pipelines, which demonstrate improvements in classification output when compared to that of recent studies, resulted in high and reproducible accuracy rates of 90.06 ± 0.01% with a sensitivity of 92.00 ± 0.04%, a specificity of 87.78 ± 0.04%, and a precision of 89.6 ± 0.03% with 10-fold cross-validation.

  19. Sandwich masking eliminates both visual awareness of faces and face-specific brain activity through a feedforward mechanism.

    Science.gov (United States)

    Harris, Joseph A; Wu, Chien-Te; Woldorff, Marty G

    2011-06-07

    It is generally agreed that considerable amounts of low-level sensory processing of visual stimuli can occur without conscious awareness. On the other hand, the degree of higher level visual processing that occurs in the absence of awareness is as yet unclear. Here, event-related potential (ERP) measures of brain activity were recorded during a sandwich-masking paradigm, a commonly used approach for attenuating conscious awareness of visual stimulus content. In particular, the present study used a combination of ERP activation contrasts to track both early sensory-processing ERP components and face-specific N170 ERP activations, in trials with versus without awareness. The electrophysiological measures revealed that the sandwich masking abolished the early face-specific N170 neural response (peaking at ~170 ms post-stimulus), an effect that paralleled the abolition of awareness of face versus non-face image content. Furthermore, however, the masking appeared to render a strong attenuation of earlier feedforward visual sensory-processing signals. This early attenuation presumably resulted in insufficient information being fed into the higher level visual system pathways specific to object category processing, thus leading to unawareness of the visual object content. These results support a coupling of visual awareness and neural indices of face processing, while also demonstrating an early low-level mechanism of interference in sandwich masking.

  20. A Newton-type neural network learning algorithm

    International Nuclear Information System (INIS)

    Ivanov, V.V.; Puzynin, I.V.; Purehvdorzh, B.

    1993-01-01

    First- and second-order learning methods for feed-forward multilayer networks are considered. A Newton-type algorithm is proposed and compared with the common back-propagation algorithm. It is shown that the proposed algorithm provides better learning quality. Some recommendations for their usage are given. 11 refs.; 1 fig.; 1 tab

  1. Synaptic convergence regulates synchronization-dependent spike transfer in feedforward neural networks.

    Science.gov (United States)

    Sailamul, Pachaya; Jang, Jaeson; Paik, Se-Bum

    2017-12-01

    Correlated neural activities such as synchronizations can significantly alter the characteristics of spike transfer between neural layers. However, it is not clear how this synchronization-dependent spike transfer can be affected by the structure of convergent feedforward wiring. To address this question, we implemented computer simulations of model neural networks: a source and a target layer connected with different types of convergent wiring rules. In the Gaussian-Gaussian (GG) model, both the connection probability and the strength are given as Gaussian distribution as a function of spatial distance. In the Uniform-Constant (UC) and Uniform-Exponential (UE) models, the connection probability density is a uniform constant within a certain range, but the connection strength is set as a constant value or an exponentially decaying function, respectively. Then we examined how the spike transfer function is modulated under these conditions, while static or synchronized input patterns were introduced to simulate different levels of feedforward spike synchronization. We observed that the synchronization-dependent modulation of the transfer function appeared noticeably different for each convergence condition. The modulation of the spike transfer function was largest in the UC model, and smallest in the UE model. Our analysis showed that this difference was induced by the different spike weight distributions that was generated from convergent synapses in each model. Our results suggest that, the structure of the feedforward convergence is a crucial factor for correlation-dependent spike control, thus must be considered important to understand the mechanism of information transfer in the brain.

  2. Estimating feedforward vs. feedback control of speech production through kinematic analyses of unperturbed articulatory movements.

    Science.gov (United States)

    Kim, Kwang S; Max, Ludo

    2014-01-01

    To estimate the contributions of feedforward vs. feedback control systems in speech articulation, we analyzed the correspondence between initial and final kinematics in unperturbed tongue and jaw movements for consonant-vowel (CV) and vowel-consonant (VC) syllables. If movement extents and endpoints are highly predictable from early kinematic information, then the movements were most likely completed without substantial online corrections (feedforward control); if the correspondence between early kinematics and final amplitude or position is low, online adjustments may have altered the planned trajectory (feedback control) (Messier and Kalaska, 1999). Five adult speakers produced CV and VC syllables with high, mid, or low vowels while movements of the tongue and jaw were tracked electromagnetically. The correspondence between the kinematic parameters peak acceleration or peak velocity and movement extent as well as between the articulators' spatial coordinates at those kinematic landmarks and movement endpoint was examined both for movements across different target distances (i.e., across vowel height) and within target distances (i.e., within vowel height). Taken together, results suggest that jaw and tongue movements for these CV and VC syllables are mostly under feedforward control but with feedback-based contributions. One type of feedback-driven compensatory adjustment appears to regulate movement duration based on variation in peak acceleration. Results from a statistical model based on multiple regression are presented to illustrate how the relative strength of these feedback contributions can be estimated.

  3. [Feedforward control strategy and its application in quality improvement of ethanol precipitation process of danhong injection].

    Science.gov (United States)

    Yan, Bin-Jun; Guo, Zheng-Tai; Qu, Hai-Bin; Zhao, Bu-Chang; Zhao, Tao

    2013-06-01

    In this work, a feedforward control strategy basing on the concept of quality by design was established for the manufacturing process of traditional Chinese medicine to reduce the impact of the quality variation of raw materials on drug. In the research, the ethanol precipitation process of Danhong injection was taken as an application case of the method established. Box-Behnken design of experiments was conducted. Mathematical models relating the attributes of the concentrate, the process parameters and the quality of the supernatants produced were established. Then an optimization model for calculating the best process parameters basing on the attributes of the concentrate was built. The quality of the supernatants produced by ethanol precipitation with optimized and non-optimized process parameters were compared. The results showed that using the feedforward control strategy for process parameters optimization can control the quality of the supernatants effectively. The feedforward control strategy proposed can enhance the batch-to-batch consistency of the supernatants produced by ethanol precipitation.

  4. Feedforward and feedback motor control abnormalities implicate cerebellar dysfunctions in autism spectrum disorder.

    Science.gov (United States)

    Mosconi, Matthew W; Mohanty, Suman; Greene, Rachel K; Cook, Edwin H; Vaillancourt, David E; Sweeney, John A

    2015-02-04

    Sensorimotor abnormalities are common in autism spectrum disorder (ASD) and among the earliest manifestations of the disorder. They have been studied far less than the social-communication and cognitive deficits that define ASD, but a mechanistic understanding of sensorimotor abnormalities in ASD may provide key insights into the neural underpinnings of the disorder. In this human study, we examined rapid, precision grip force contractions to determine whether feedforward mechanisms supporting initial motor output before sensory feedback can be processed are disrupted in ASD. Sustained force contractions also were examined to determine whether reactive adjustments to ongoing motor behavior based on visual feedback are altered. Sustained force was studied across multiple force levels and visual gains to assess motor and visuomotor mechanisms, respectively. Primary force contractions of individuals with ASD showed greater peak rate of force increases and large transient overshoots. Individuals with ASD also showed increased sustained force variability that scaled with force level and was more severe when visual gain was highly amplified or highly degraded. When sustaining a constant force level, their reactive adjustments were more periodic than controls, and they showed increased reliance on slower feedback mechanisms. Feedforward and feedback mechanism alterations each were associated with more severe social-communication impairments in ASD. These findings implicate anterior cerebellar circuits involved in feedforward motor control and posterior cerebellar circuits involved in transforming visual feedback into precise motor adjustments in ASD. Copyright © 2015 the authors 0270-6474/15/352015-11$15.00/0.

  5. Differential contributions of the superior and inferior parietal cortex to feedback versus feedforward control of tools.

    Science.gov (United States)

    Macuga, Kristen L; Frey, Scott H

    2014-05-15

    Damage to the superior and/or inferior parietal lobules (SPL, IPL) (Sirigu et al., 1996) or cerebellum (Grealy and Lee, 2011) can selectively disrupt motor imagery, motivating the hypothesis that these regions participate in predictive (i.e., feedforward) control. If so, then the SPL, IPL, and cerebellum should show greater activity as the demands on feedforward control increase from visually-guided execution (closed-loop) to execution without visual feedback (open-loop) to motor imagery. Using fMRI and a Fitts' reciprocal aiming task with tools directed at targets in far space, we found that the SPL and cerebellum exhibited greater activity during closed-loop control. Conversely, open-loop and imagery conditions were associated with increased activity within the IPL and prefrontal areas. These results are consistent with a superior-to-inferior gradient in the representation of feedback-to-feedforward control within the posterior parietal cortex. Additionally, the anterior SPL displayed greater activity when aiming movements were performed with a stick vs. laser pointer. This may suggest that it is involved in the remapping of far into near (reachable) space (Maravita and Iriki, 2004), or in distalization of the end-effector from hand to stick (Arbib et al., 2009). Copyright © 2014 Elsevier Inc. All rights reserved.

  6. Top-down knowledge modulates onset capture in a feedforward manner.

    Science.gov (United States)

    Becker, Stefanie I; Lewis, Amanda J; Axtens, Jenna E

    2017-04-01

    How do we select behaviourally important information from cluttered visual environments? Previous research has shown that both top-down, goal-driven factors and bottom-up, stimulus-driven factors determine which stimuli are selected. However, it is still debated when top-down processes modulate visual selection. According to a feedforward account, top-down processes modulate visual processing even before the appearance of any stimuli, whereas others claim that top-down processes modulate visual selection only at a late stage, via feedback processing. In line with such a dual stage account, some studies found that eye movements to an irrelevant onset distractor are not modulated by its similarity to the target stimulus, especially when eye movements are launched early (within 150-ms post stimulus onset). However, in these studies the target transiently changed colour due to a colour after-effect that occurred during premasking, and the time course analyses were incomplete. The present study tested the feedforward account against the dual stage account in two eye tracking experiments, with and without colour after-effects (Exp. 1), as well when the target colour varied randomly and observers were informed of the target colour with a word cue (Exp. 2). The results showed that top-down processes modulated the earliest eye movements to the onset distractors (feedforward account of top-down modulation.

  7. Ammonia-based feedforward and feedback aeration control in activated sludge processes.

    Science.gov (United States)

    Rieger, Leiv; Jones, Richard M; Dold, Peter L; Bott, Charles B

    2014-01-01

    Aeration control at wastewater treatment plants based on ammonia as the controlled variable is applied for one of two reasons: (1) to reduce aeration costs, or (2) to reduce peaks in effluent ammonia. Aeration limitation has proven to result in significant energy savings, may reduce external carbon addition, and can improve denitrification and biological phosphorus (bio-P) performance. Ammonia control for limiting aeration has been based mainly on feedback control to constrain complete nitrification by maintaining approximately one to two milligrams of nitrogen per liter of ammonia in the effluent. Increased attention has been given to feedforward ammonia control, where aeration control is based on monitoring influent ammonia load. Typically, the intent is to anticipate the impact of sudden load changes, and thereby reduce effluent ammonia peaks. This paper evaluates the fundamentals of ammonia control with a primary focus on feedforward control concepts. A case study discussion is presented that reviews different ammonia-based control approaches. In most instances, feedback control meets the objectives for both aeration limitation and containment of effluent ammonia peaks. Feedforward control, applied specifically for switching aeration on or off in swing zones, can be beneficial when the plant encounters particularly unusual influent disturbances.

  8. Variable synaptic strengths controls the firing rate distribution in feedforward neural networks.

    Science.gov (United States)

    Ly, Cheng; Marsat, Gary

    2018-02-01

    Heterogeneity of firing rate statistics is known to have severe consequences on neural coding. Recent experimental recordings in weakly electric fish indicate that the distribution-width of superficial pyramidal cell firing rates (trial- and time-averaged) in the electrosensory lateral line lobe (ELL) depends on the stimulus, and also that network inputs can mediate changes in the firing rate distribution across the population. We previously developed theoretical methods to understand how two attributes (synaptic and intrinsic heterogeneity) interact and alter the firing rate distribution in a population of integrate-and-fire neurons with random recurrent coupling. Inspired by our experimental data, we extend these theoretical results to a delayed feedforward spiking network that qualitatively capture the changes of firing rate heterogeneity observed in in-vivo recordings. We demonstrate how heterogeneous neural attributes alter firing rate heterogeneity, accounting for the effect with various sensory stimuli. The model predicts how the strength of the effective network connectivity is related to intrinsic heterogeneity in such delayed feedforward networks: the strength of the feedforward input is positively correlated with excitability (threshold value for spiking) when firing rate heterogeneity is low and is negatively correlated with excitability with high firing rate heterogeneity. We also show how our theory can be used to predict effective neural architecture. We demonstrate that neural attributes do not interact in a simple manner but rather in a complex stimulus-dependent fashion to control neural heterogeneity and discuss how it can ultimately shape population codes.

  9. Feedback and Feedforward Control During Walking in Individuals With Chronic Ankle Instability.

    Science.gov (United States)

    Yen, Sheng-Che; Corkery, Marie B; Donohoe, Amy; Grogan, Maddison; Wu, Yi-Ning

    2016-09-01

    Study Design Controlled laboratory study. Background Recurrent ankle sprains associated with chronic ankle instability (CAI) occur not only in challenging sports but also in daily walking. Understanding whether and how CAI alters feedback and feedforward controls during walking may be important for developing interventions for CAI prevention or treatment. Objective To understand whether CAI is associated with changes in feedback and feedforward control when individuals with CAI are subjected to experimental perturbation during walking. Methods Twelve subjects with CAI and 12 control subjects walked on a treadmill while adapting to external loading that generated inversion perturbation at the ankle joint. Ankle kinematics around heel contact during and after the adaptation were compared between the 2 groups. Results Both healthy and CAI groups showed an increase in eversion around heel contact in early adaptation to the external loading. However, the CAI group adapted back toward the baseline, while the healthy controls showed further increase in eversion in late adaptation. When the external loading was removed in the postadaptation period, healthy controls showed an aftereffect consisting of an increase in eversion around heel contact, but the CAI group showed no aftereffect. Conclusion The results provide preliminary evidence that CAI may alter individuals' feedback and feedforward control during walking. J Orthop Sports Phys Ther 2016;46(9):775-783. Epub 5 Aug 2016. doi:10.2519/jospt.2016.6403.

  10. Feed-forward and feedback projections of midbrain reticular formation neurons in the cat

    Directory of Open Access Journals (Sweden)

    Eddie ePerkins

    2014-01-01

    Full Text Available Gaze changes involving the eyes and head are orchestrated by brainstem gaze centers found within the superior colliculus (SC, paramedian pontine reticular formation (PPRF, and medullary reticular formation (MdRF. The mesencephalic reticular formation (MRF also plays a role in gaze. It receives a major input from the ipsilateral SC and contains cells that fire in relation to gaze changes. Moreover, it provides a feedback projection to the SC and feed-forward projections to the PPRF and MdRF. We sought to determine whether these MRF feedback and feed-forward projections originate from the same or different neuronal populations by utilizing paired fluorescent retrograde tracers in cats. Specifically, we tested: 1. whether MRF neurons that control eye movements form a single population by injecting the SC and PPRF with different tracers, and 2. whether MRF neurons that control head movements form a single population by injecting the SC and MdRF with different tracers. In neither case were double labeled neurons observed, indicating that feedback and feed-forward projections originate from separate MRF populations. In both cases, the labeled reticulotectal and reticuloreticular neurons were distributed bilaterally in the MRF. However, neurons projecting to the MdRF were generally constrained to the medial half of the MRF, while those projecting to the PPRF, like MRF reticulotectal neurons, were spread throughout the mediolateral axis. Thus, the medial MRF may be specialized for control of head movements, with control of eye movements being more widespread in this structure.

  11. Measurable Disturbances Compensation: Analysis and Tuning of Feedforward Techniques for Dead-Time Processes

    Directory of Open Access Journals (Sweden)

    Andrzej Pawlowski

    2016-04-01

    Full Text Available In this paper, measurable disturbance compensation techniques are analyzed, focusing the problem on the input-output and disturbance-output time delays. The feedforward compensation method is evaluated for the common structures that appear between the disturbance and process dynamics. Due to the presence of time delays, the study includes causality and instability phenomena that can arise when a classical approach for disturbance compensation is used. Different feedforward configurations are analyzed for two feedback control techniques, PID (Proportional-Integral-Derivative and MPC (Model Predictive Control that are widely used for industrial process-control applications. The specific tuning methodology for the analyzed process structure is used to obtain improved disturbance rejection performance regarding classical approaches. The evaluation of the introduced disturbance rejection schemes is performed through simulation, considering process constraints in order to highlight the advantages and drawbacks in common scenarios. The performance of the analyzed structure is expressed with different indexes that allow us direct comparisons. The obtained results show that the proper design and tuning of the feedforward action helps to significantly improve the overall control performance in process control tasks.

  12. Probing feedforward and feedback contributions to awareness with visual masking and transcranial magnetic stimulation.

    Science.gov (United States)

    Tapia, Evelina; Beck, Diane M

    2014-01-01

    A number of influential theories posit that visual awareness relies not only on the initial, stimulus-driven (i.e., feedforward) sweep of activation but also on recurrent feedback activity within and between brain regions. These theories of awareness draw heavily on data from masking paradigms in which visibility of one stimulus is reduced due to the presence of another stimulus. More recently transcranial magnetic stimulation (TMS) has been used to study the temporal dynamics of visual awareness. TMS over occipital cortex affects performance on visual tasks at distinct time points and in a manner that is comparable to visual masking. We draw parallels between these two methods and examine evidence for the neural mechanisms by which visual masking and TMS suppress stimulus visibility. Specifically, both methods have been proposed to affect feedforward as well as feedback signals when applied at distinct time windows relative to stimulus onset and as a result modify visual awareness. Most recent empirical evidence, moreover, suggests that while visual masking and TMS impact stimulus visibility comparably, the processes these methods affect may not be as similar as previously thought. In addition to reviewing both masking and TMS studies that examine feedforward and feedback processes in vision, we raise questions to guide future studies and further probe the necessary conditions for visual awareness.

  13. Distinct Feedforward and Feedback Effects of Microstimulation in Visual Cortex Reveal Neural Mechanisms of Texture Segregation.

    Science.gov (United States)

    Klink, P Christiaan; Dagnino, Bruno; Gariel-Mathis, Marie-Alice; Roelfsema, Pieter R

    2017-07-05

    The visual cortex is hierarchically organized, with low-level areas coding for simple features and higher areas for complex ones. Feedforward and feedback connections propagate information between areas in opposite directions, but their functional roles are only partially understood. We used electrical microstimulation to perturb the propagation of neuronal activity between areas V1 and V4 in monkeys performing a texture-segregation task. In both areas, microstimulation locally caused a brief phase of excitation, followed by inhibition. Both these effects propagated faithfully in the feedforward direction from V1 to V4. Stimulation of V4, however, caused little V1 excitation, but it did yield a delayed suppression during the late phase of visually driven activity. This suppression was pronounced for the V1 figure representation and weaker for background representations. Our results reveal functional differences between feedforward and feedback processing in texture segregation and suggest a specific modulating role for feedback connections in perceptual organization. Copyright © 2017 Elsevier Inc. All rights reserved.

  14. Feedforward Delay Estimators in Adverse Multipath Propagation for Galileo and Modernized GPS Signals

    Directory of Open Access Journals (Sweden)

    Lohan Elena Simona

    2006-01-01

    Full Text Available The estimation with high accuracy of the line-of-sight delay is a prerequisite for all global navigation satellite systems. The delay locked loops and their enhanced variants are the structures of choice for the commercial GNSS receivers, but their performance in severe multipath scenarios is still rather limited. The new satellite positioning system proposals specify higher code-epoch lengths compared to the traditional GPS signal and the use of a new modulation, the binary offset carrier (BOC modulation, which triggers new challenges in the delay tracking stage. We propose and analyze here the use of feedforward delay estimation techniques in order to improve the accuracy of the delay estimation in severe multipath scenarios. First, we give an extensive review of feedforward delay estimation techniques for CDMA signals in fading channels, by taking into account the impact of BOC modulation. Second, we extend the techniques previously proposed by the authors in the context of wideband CDMA delay estimation (e.g., Teager-Kaiser and the projection onto convex sets to the BOC-modulated signals. These techniques are presented as possible alternatives to the feedback tracking loops. A particular attention is on the scenarios with closely spaced paths. We also discuss how these feedforward techniques can be implemented via DSPs.

  15. Feedforward responses of transversus abdominis are directionally specific and act asymmetrically: implications for core stability theories.

    Science.gov (United States)

    Allison, Garry T; Morris, Sue L; Lay, Brendan

    2008-05-01

    Experimental laboratory study supplemented with a repeated case study. To examine bilateral muscle activity of the deep abdominals in response to rapid arm raising, specifically to examine the laterality and directional specificity of feedforward responses of the transversus abdominis (TrA). Based on the feedforward responses of trunk muscles during rapid arm movements, authors have concluded that the deep trunk muscles have different control mechanisms compared to the more superficial muscles. It has been proposed that deep trunk muscles such as TrA contribute substantially to the stability of the lumbar spine and that this is achieved through simultaneous bilateral feedforward activation. These inferences are based on unilateral fine-wire electromyographic (EMG) data and there are limited investigations of bilateral responses of the TrA during unilateral arm raising. Bilateral fine-wire and surface EMG data from the anterior deltoid, TrA, obliquus internus (OI), obliquus externus, biceps femoris, erector spinae, and rectus abdominis during repeated arm raises were recorded at 2 kHz. EMG signal linear envelopes were synchronized to the onset of the anterior deltoid. A feedforward window was defined as the period up to 50 ms after the onset of the anterior deltoid, and paired onsets for bilateral muscles were plotted for both left and right arm movements. Trunk muscles from the group data demonstrated differences between sides (laterality), which were systematically altered when alternate arms were raised (directional specificity). This was clearly evident for the TrA but less obvious for the erector spinae. The ipsilateral biceps femoris and obliquus externus, and contralateral OI and TrA, were activated earlier than the alternate side for both right and left arm movements. This was a consistent pattern over a 7-year period for the case study. Data for the rectus abdominis derived from the case study demonstrated little laterality or directionally specific

  16. PSYCHOLOGICAL STRATEGY OF COOPERATION, MOTIVATIONAL, INFORMATION AND TECHNOLOGICAL COMPONENTS OF FUTURE HUMANITARIAN TEACHER READINESS FOR PROFESSIONAL ACTIVITY IN POLYSUBJECTIVE LEARNING ENVIRONMENT

    Directory of Open Access Journals (Sweden)

    Y. Spivakovska

    2014-04-01

    Full Text Available Redefining of modern information and communication technologies (ICT from teaching aids to teaching process subjects, continuous growth of their subjectivity necessary demands appropriate knowledge, skills, appropriate attitude to didactic capabilities of ICT, ability to cooperate with them and to build pupils learning activity aimed at formation and development of self organization, self development skills, promoting their subjective position in getting education that will be readiness of modern teacher to organize effective professional activities in polysubjective learning environment (PLE. The new tasks of humanitarian teacher related to self selection and design of educational content as well as the modeling of the learning process in conditions of PLE virtualized alternatives choice, impose special requirements to professionally important teacher’s personality qualities, rather to his readiness to implement effective professional work in such conditions. In this article the essence of future humanitarian teacher readiness concept to professional activity in polysubjective educational environment is proved. The structure of the readiness is analyzed. Psychological strategy of cooperation, reflective, motivational and informational partials are substantiated and characterized as components of the future humanitarian teacher readiness to professional activities in polysubjective educational environment.

  17. Feedback and feedforward control of frequency tuning to naturalistic stimuli.

    Science.gov (United States)

    Chacron, Maurice J; Maler, Leonard; Bastian, Joseph

    2005-06-08

    Sensory neurons must respond to a wide variety of natural stimuli that can have very different spatiotemporal characteristics. Optimal responsiveness to subsets of these stimuli can be achieved by devoting specialized neural circuitry to different stimulus categories, or, alternatively, this circuitry can be modulated or tuned to optimize responsiveness to current stimulus conditions. This study explores the mechanisms that enable neurons within the initial processing station of the electrosensory system of weakly electric fish to shift their tuning properties based on the spatial extent of the stimulus. These neurons are tuned to low frequencies when the stimulus is restricted to a small region within the receptive field center but are tuned to higher frequencies when the stimulus impinges on large regions of the sensory epithelium. Through a combination of modeling and in vivo electrophysiology, we reveal the respective contributions of the filtering characteristics of extended dendritic structures and feedback circuitry to this shift in tuning. Our results show that low-frequency tuning can result from the cable properties of an extended dendrite that conveys receptor-afferent information to the cell body. The shift from low- to high-frequency tuning, seen in response to spatially extensive stimuli, results from increased wide-band input attributable to activation of larger populations of receptor afferents, as well as the activation of parallel fiber feedback from the cerebellum. This feedback provides a cancellation signal with low-pass characteristics that selectively attenuates low-frequency responsiveness. Thus, with spatially extensive stimuli, these cells preferentially respond to the higher-frequency components of the receptor-afferent input.

  18. Using Deep Learning to Predict Complex Systems: A Case Study in Wind Farm Generation

    Directory of Open Access Journals (Sweden)

    J. M. Torres

    2018-01-01

    Full Text Available Making every component of an electrical system work in unison is being made more challenging by the increasing number of renewable energies used, the electrical output of which is difficult to determine beforehand. In Spain, the daily electricity market opens with a 12-hour lead time, where the supply and demand expected for the following 24 hours are presented. When estimating the generation, energy sources like nuclear are highly stable, while peaking power plants can be run as necessary. Renewable energies, however, which should eventually replace peakers insofar as possible, are reliant on meteorological conditions. In this paper we propose using different deep-learning techniques and architectures to solve the problem of predicting wind generation in order to participate in the daily market, by making predictions 12 and 36 hours in advance. We develop and compare various estimators based on feedforward, convolutional, and recurrent neural networks. These estimators were trained and validated with data from a wind farm located on the island of Tenerife. We show that the best candidates for each type are more precise than the reference estimator and the polynomial regression currently used at the wind farm. We also conduct a sensitivity analysis to determine which estimator type is most robust to perturbations. An analysis of our findings shows that the most accurate and robust estimators are those based on feedforward neural networks with a SELU activation function and convolutional neural networks.

  19. Analysis of Maths Learning Activities Developed By Pre-service Teachers in Terms of the Components of Content, Purpose, Application Methods

    Directory of Open Access Journals (Sweden)

    Çağla Toprak

    2014-04-01

    Full Text Available Today- when the influence of the alteration movement done in order to keep up with the age of the educational system is still continuing- the importance of teachers in students’ learning and achieving what is expected from the education system has been stated by the studies conducted (Hazır & Bıkmaz, 2006. Teachers own a critical role in the stage of both preparing teaching materials and using them (Stein & Smith, 1998b; Swan, 2007. When the existing curriculums –in particular, maths and geometry cirriculums- are analyzed, it can be observed that activities are the most significant teaching materials (Bozkurt, 2012. In fact, it is possible to characterize the existing curriculums as activity-based ones (Report of Workshop Examining Content of Primary School Curriculums According to Branches, 2010; Epö, 2005. Therefore, what sort of learning activities there are, what qualities they need to have, how to design and apply them are topics that must be elaborated (Uğurel et al., 2010.  At this point, our study to increase the skills of pre-service teachers during the process of developing activities was conducted with 27 pre-service teachers -19 girls 8 boys- studying in the 4th year in Mathematics Education Department at a state university in the Aegean Region. The activity designs the pre-service teachers developed considering the patterns given after a series of practice were analyzed in documents in terms of the aim of design and the form of practice. As a result of the studies, it is observed that pre-service teachers deal with the topics from the maths curriculum and these topics are of different grade levels. The result of the examination named as target component suggests that activities developed aim firstly at providing learning and this is followed by reinforcing the concepts already learned. It is stated that pre-service teachers prefer mostly small group (cooperative studies in the activities they develop.Key Words:

  20. Very Fast Estimation of Epicentral Distance and Magnitude from a Single Three Component Seismic Station Using Machine Learning Techniques

    Science.gov (United States)

    Ochoa Gutierrez, L. H.; Niño Vasquez, L. F.; Vargas-Jimenez, C. A.

    2012-12-01

    To minimize adverse effects originated by high magnitude earthquakes, early warning has become a powerful tool to anticipate a seismic wave arrival to an specific location and lets to bring people and government agencies opportune information to initiate a fast response. To do this, a very fast and accurate characterization of the event must be done but this process is often made using seismograms recorded in at least 4 stations where processing time is usually greater than the wave travel time to the interest area, mainly in coarse networks. A faster process can be done if only one three component seismic station is used that is the closest unsaturated station respect to the epicenter. Here we present a Support Vector Regression algorithm which calculates Magnitude and Epicentral Distance using only 5 seconds of signal since P wave onset. This algorithm was trained with 36 records of historical earthquakes where the input were regression parameters of an exponential function estimated by least squares, corresponding to the waveform envelope and the maximum value of the observed waveform for each component in one single station. A 10 fold Cross Validation was applied for a Normalized Polynomial Kernel obtaining the mean absolute error for different exponents and complexity parameters. Magnitude could be estimated with 0.16 of mean absolute error and the distance with an error of 7.5 km for distances within 60 to 120 km. This kind of algorithm is easy to implement in hardware and can be used directly in the field station to make possible the broadcast of estimations of this values to generate fast decisions at seismological control centers, increasing the possibility to have an effective reactiontribute and Descriptors calculator for SVR model training and test

  1. Fast Estimation of Epicentral Distance and Magnitude from a Single Three Component Seismic Station Using Machine Learning Techniques

    Science.gov (United States)

    Ochoa Gutierrez, L. H.; Niño, L. F.; Vargas-Jimenez, C. A.

    2013-05-01

    To minimize adverse effects originated by high magnitude earthquakes, early warning has become a powerful tool to anticipate a seismic wave arrival to an specific location, bringing opportune information to people and government agencies to initiate a fast response. To do this, a very fast and accurate characterization of the event must be done but this process is often made using seismograms recorded in at least four stations where processing time is usually greater than the wave arrival time to the interest area, mainly in seismological coarse networks. A faster process can be done if only one three component seismic station, the closest unsaturated station with respect to the epicenter, is used. Here, we present a Support Vector Regression algorithm which calculates Magnitude and Epicentral Distance using only five seconds of signal since P wave onset. This algorithm was trained with 36 records of historical earthquakes, where the input included regression parameters of an exponential function estimated by least squares, of the waveform envelope and the maximum value of the observed waveform for each component in a single station. A ten-fold Cross Validation was applied for a Normalized Polynomial Kernel obtaining the mean absolute error for different exponents and complexity parameters. The Magnitude could be estimated with 0.16 units of mean absolute error and the distance with an error of 7.5 km for distances within 60 to 120 km. This kind of algorithm is easy to implement in hardware and can be used directly in the field seismological sensor to make the broadcast of estimations of these values possible to generate fast decisions at seismological control centers, increasing the possibility of having an effective reaction.

  2. Feedforward correction of mirror misalignment fluctuations for the GEO 600 gravitational wave detector

    International Nuclear Information System (INIS)

    Smith, J R; Grote, H; Hewitson, M; Hild, S; Lueck, H; Parsons, M; Strain, K A; Willke, B

    2005-01-01

    The core instrument of the GEO 600 gravitational wave detector is a Michelson interferometer with folded arms. The five main optics that form this interferometer are suspended in vacuum by triple pendulums with quasi-monolithic lower stages of fused silica. After installation of these pendulums in early 2003, a larger than expected coupling of longitudinal ground motion to tilt misalignment of the suspended optics was observed. Because of this, the uncontrolled misalignment of the optics during average conditions was several μrad Hz -1/2 in the frequency band around the pendulum resonance frequencies (0.5-4 Hz). In addition, it was found that longitudinal control signals applied to the intermediate pendulum stages also resulted in excessive mirror tilt. The resulting misalignment exceeded the level tolerable for stable operation of GEO 600. In order to reduce the level of mirror tilt, a bipartite feedforward system was implemented. One part feeds signals derived from seismic measurements to piezo-electric crystals in the stacks supporting the suspensions, reducing the longitudinal motion of the uppermost suspension points. The other applies tilt correction signals, derived from longitudinal control signals, to the intermediate level of the suspensions. The seismic feedforward correction reduces the root-mean-squared tilt misalignment of each main optic between 0.1 and 5 Hz by about 10 dB, typically. The intermediate-mass feedforward correction reduces the differential tilt misalignment of the Michelson interferometer by about 10 dB between 0.1 and 0.8 Hz, typically

  3. Flatness based feedforward control of a parallel hybrid drivetrain; Flachheitsbasierter Vorsteuerungsentwurf fuer den Antriebsstrang eines Parallelhybriden

    Energy Technology Data Exchange (ETDEWEB)

    Gasper, Rainer; Hesseler, Frank; Abel, Dirk [RWTH Aachen Univ. (Germany). Inst. fuer Regelungstechnik

    2010-10-15

    The advantages of Hybrid Electrical Vehicles (HEV) are fuel consumption reduction and minimization of exhaust emissions. Moreover, the drivability of a HEV is very important for the consumer acceptance. The gear shifts and the start of the internal combustion engine are very important for the drivability of a HEV. Because this two tasks are automated, oscillations in the vehicle would be uncomfortable for the driver. In the paper at hand, feedforward controllers for the drivetrain control of a parallel hybrid with an automated manual transmission and a dry clutch are presented. (orig.)

  4. Adaptive feedforward of estimated ripple improves the closed loop system performance significantly

    International Nuclear Information System (INIS)

    Kwon, S.; Regan, A.; Wang, Y.M.; Rohlev, A.S.

    1998-01-01

    The Low Energy Demonstration Accelerator (LEDA) being constructed at Los Alamos National Laboratory will serve as the prototype for the low energy section of Acceleration Production of Tritium (APT) accelerator. This paper addresses the problem of LLRF control system for LEDA. The authors propose an estimator of the ripple and its time derivative and a control law which is based on PID control and adaptive feedforward of estimated ripple. The control law reduces the effect of the deterministic cathode ripple that is due to high voltage power supply and achieves tracking of desired set points

  5. Online high voltage power supply ripple estimation and feedforward in LEDA

    International Nuclear Information System (INIS)

    Kwon, S.; Regan, A.; Wang, Y.M.; Rohlev, T.

    1999-01-01

    The Low Energy Demonstration Accelerator (LEDA) being constructed at Los Alamos National Laboratory will serve as the prototype for the low energy section of Acceleration Production of Tritium (APT) accelerator. This paper addresses the problem of LLRF control system for LEDA. They propose an estimator of the ripple and its time derivative and a control law which is based on PID control and adaptive feedforward of estimated ripple. The control law reduces the effect of the deterministic cathode ripple that is due to high voltage power supply and achieves tracking of desired set points

  6. Cell cycle regulation by feed-forward loops coupling transcription and phosphorylation

    DEFF Research Database (Denmark)

    Csikász-Nagy, Attila; Kapuy, Orsolya; Tóth, Attila

    2009-01-01

    of these EPs. From genome-scale data sets of budding yeast, we identify 126 EPs that are regulated by Cdk1 both through direct phosphorylation of the EP and through phosphorylation of the transcription factors that control expression of the EP, so that each of these EPs is regulated by a feed-forward loop (FFL......) from Cdk1. By mathematical modelling, we show that such FFLs can activate EPs at different phases of the cell cycle depending of the effective signs (+ or -) of the regulatory steps of the FFL. We provide several case studies of EPs that are controlled by FFLs exactly as our models predict. The signal...

  7. Stability identification for grid-connected inverters with LCL filters considering grid-voltage feedforward regulator

    DEFF Research Database (Denmark)

    Lu, Minghui; Blaabjerg, Frede

    2017-01-01

    This paper identifies stable resonance frequency range for grid-connected inverter with Grid-Voltage Feedforward Regulator (GVFR). Beginning with the current loop stability analysis without GVFR, system poles distribution is analytically studied in z-domain, the critical frequency is therefore...... calculated as well as the control gain limit. Then, this paper reveals the GVFR would change the system stability in the weak power system, two frequency boundaries and three typical resonance frequency ranges are identified and compared. System poles distribution shows that GVFR can offer damping effects...

  8. Feedforward control strategy for the state-decoupling Stand-alone UPS with LC output filter

    DEFF Research Database (Denmark)

    Lu, Jinghang; Savaghebi, Mehdi; Guerrero, Josep M.

    2017-01-01

    . In order to further increase the load current disturbance rejection capability of the state-decoupling in UPS system, a feedforward control strategy is proposed. In addition, the design principle for the current and voltage regulators are discussed. Simulation and experimental results are provided......In this paper, the disturbance rejection performance of the cascaded control strategy for UPS system is investigated. The comparison of closed loop system performance between conventional cascaded control (CCC) strategy and state-decoupling cascaded control (SDCC) strategy are further explored...

  9. Boundedness and convergence of online gradient method with penalty for feedforward neural networks.

    Science.gov (United States)

    Zhang, Huisheng; Wu, Wei; Liu, Fei; Yao, Mingchen

    2009-06-01

    In this brief, we consider an online gradient method with penalty for training feedforward neural networks. Specifically, the penalty is a term proportional to the norm of the weights. Its roles in the method are to control the magnitude of the weights and to improve the generalization performance of the network. By proving that the weights are automatically bounded in the network training with penalty, we simplify the conditions that are required for convergence of online gradient method in literature. A numerical example is given to support the theoretical analysis.

  10. Subtractive, divisive and non-monotonic gain control in feedforward nets linearized by noise and delays

    OpenAIRE

    Mejias, Jorge F.; Payeur, Alexandre; Selin, Erik; Maler, Leonard; Longtin, André

    2014-01-01

    The control of input-to-output mappings, or gain control, is one of the main strategies used by neural networks for the processing and gating of information. Using a spiking neural network model, we studied the gain control induced by a form of inhibitory feedforward circuitry—also known as “open-loop feedback”—, which has been experimentally observed in a cerebellum-like structure in weakly electric fish. We found, both analytically and numerically, that this network displays three different...

  11. On path generation and feedforward control for a class of surface sailing vessels

    DEFF Research Database (Denmark)

    Xiao, Lin; Jouffroy, Jerome

    2010-01-01

    Sailing vessels with wind as their main means of propulsion possess a unique property that the paths they take depend on the wind direction, which, in the literature, has attracted less attention than normal vehicles propelled by propellers or thrusters. This paper considers the problem of motion...... planning and controllability for sailing vehicles representing the no-sailing zone effect in sailing. Following our previous work, we present an extended algorithm for automatic path generation with a prescribed initial heading for a simple model of sailing vehicles, together with a feedforward controller...

  12. Feed-forward control of a solid oxide fuel cell system with anode offgas recycle

    Science.gov (United States)

    Carré, Maxime; Brandenburger, Ralf; Friede, Wolfgang; Lapicque, François; Limbeck, Uwe; da Silva, Pedro

    2015-05-01

    In this work a combined heat and power unit (CHP unit) based on the solid oxide fuel cell (SOFC) technology is analysed. This unit has a special feature: the anode offgas is partially recycled to the anode inlet. Thus it is possible to increase the electrical efficiency and the system can be operated without external water feeding. A feed-forward control concept which allows secure operating conditions of the CHP unit as well as a maximization of its electrical efficiency is introduced and validated experimentally. The control algorithm requires a limited number of measurement values and few deterministic relations for its description.

  13. A high-speed tunable beam splitter for feed-forward photonic quantum information processing.

    Science.gov (United States)

    Ma, Xiao-Song; Zotter, Stefan; Tetik, Nuray; Qarry, Angie; Jennewein, Thomas; Zeilinger, Anton

    2011-11-07

    We realize quantum gates for path qubits with a high-speed, polarization-independent and tunable beam splitter. Two electro-optical modulators act in a Mach-Zehnder interferometer as high-speed phase shifters and rapidly tune its splitting ratio. We test its performance with heralded single photons, observing a polarization-independent interference contrast above 95%. The switching time is about 5.6 ns, and a maximal repetition rate is 2.5 MHz. We demonstrate tunable feed-forward operations of a single-qubit gate of path-encoded qubits and a two-qubit gate via measurement-induced interaction between two photons.

  14. Application of a feedforward neural network in the search for kuroko deposits in the hokuroku district, Japan

    Science.gov (United States)

    Singer, D.A.; Kouda, R.

    1996-01-01

    A feedforward neural network with one hidden layer and five neurons was trained to recognize the distance to kuroko mineral deposits. Average amounts per hole of pyrite, sericite, and gypsum plus anhydrite as measured by X-rays in 69 drillholes were used in train the net. Drillholes near and between the Fukazawa, Furutobe, and Shakanai mines were used. The training data were selected carefully to represent well-explored areas where some confidence of the distance to ore was assured. A logarithmic transform was applied to remove the skewness of distance and each variable was scaled and centered by subtracting the median and dividing by the interquartile range. The learning algorithm of annealing plus conjugate gradients was used to minimise the mean squared error of the sealed distance to ore. The trained network then was applied to all of the 152 drillholes that had measured gypsum, sericite, and pyrite. A contour plot of the neural net predicted distance to ore shows fairly wide areas of 1 km or less to ore; each of the known deposit groups is within the 1 km contour. The high and htw distances on the margins of the contoured distance plot are in part the result of boundary effects of the contouring algorithm. For example, the short distances to ore predicted west of the Shakanai (Hanaoka) deposits are in basement. However, the short distances to ore predicted northeast of Furotobe, just off the figure, coincide with the location of the Nurukawa kuroko deposit and the Omaki deposit, south of the Shakanai-Hanaoka deposits, seems to be on an extension of short distance to ore contour, but is beyond the 3 km limit from drillholes. Also of interest are some areas only a few kilometers from the Fukazawa and Shakanai groups of deposits that are estimated to be many kilometers from ore, apparently reflecting the network's recognition of the extreme local variability of the geology near some deposits. 1996 International Association for Mathematical Geology.

  15. Application of kernel principal component analysis and computational machine learning to exploration of metabolites strongly associated with diet.

    Science.gov (United States)

    Shiokawa, Yuka; Date, Yasuhiro; Kikuchi, Jun

    2018-02-21

    Computer-based technological innovation provides advancements in sophisticated and diverse analytical instruments, enabling massive amounts of data collection with relative ease. This is accompanied by a fast-growing demand for technological progress in data mining methods for analysis of big data derived from chemical and biological systems. From this perspective, use of a general "linear" multivariate analysis alone limits interpretations due to "non-linear" variations in metabolic data from living organisms. Here we describe a kernel principal component analysis (KPCA)-incorporated analytical approach for extracting useful information from metabolic profiling data. To overcome the limitation of important variable (metabolite) determinations, we incorporated a random forest conditional variable importance measure into our KPCA-based analytical approach to demonstrate the relative importance of metabolites. Using a market basket analysis, hippurate, the most important variable detected in the importance measure, was associated with high levels of some vitamins and minerals present in foods eaten the previous day, suggesting a relationship between increased hippurate and intake of a wide variety of vegetables and fruits. Therefore, the KPCA-incorporated analytical approach described herein enabled us to capture input-output responses, and should be useful not only for metabolic profiling but also for profiling in other areas of biological and environmental systems.

  16. Gaze stabilization in chronic vestibular-loss and in cerebellar ataxia: interactions of feedforward and sensory feedback mechanisms.

    Science.gov (United States)

    Sağlam, M; Lehnen, N

    2014-01-01

    During gaze shifts, humans can use visual, vestibular, and proprioceptive feedback, as well as feedforward mechanisms, for stabilization against active and passive head movements. The contributions of feedforward and sensory feedback control, and the role of the cerebellum, are still under debate. To quantify these contributions, we increased the head moment of inertia in three groups (ten healthy, five chronic vestibular-loss and nine cerebellar-ataxia patients) while they performed large gaze shifts to flashed targets in darkness. This induces undesired head oscillations. Consequently, both active (desired) and passive (undesired) head movements had to be compensated for to stabilize gaze. All groups compensated for active and passive head movements, vestibular-loss patients less than the other groups (P feedforward mechanisms substantially contribute to gaze stabilization. Proprioception alone is not sufficient (gain 0.2). Stabilization against active and passive head movements was not impaired in our cerebellar ataxia patients.

  17. A Feed-Forward Control Realizing Fast Response for Three-Branch Interleaved DC-DC Converter in DC Microgrid

    Directory of Open Access Journals (Sweden)

    Haojie Wang

    2016-07-01

    Full Text Available It is a common practice for storage batteries to be connected to DC microgrid buses through DC-DC converters for voltage support on islanded operation mode. A feed-forward control based dual-loop constant voltage PI control for three-branch interleaved DC-DC converters (TIDC is proposed for storage batteries in DC microgrids. The working principle of TIDC is analyzed, and the factors influencing the response rate based on the dual-loop constant voltage control for TIDC are discussed, and then the method of feed-forward control for TIDC is studied to improve the response rate for load changing. A prototype of the TIDC is developed and an experimental platform is built. The experiment results show that DC bus voltage sags or swells caused by load changing can be reduced and the time for voltage recovery can be decreased significantly with the proposed feed-forward control.

  18. A Feed-Forward Control Realizing Fast Response for Three-Branch Interleaved DC-DC Converter in DC Microgrid

    DEFF Research Database (Denmark)

    Wang, Haojie; Han, Minxiao; Yan, Wenli

    2016-01-01

    It is a common practice for storage batteries to be connected to DC microgrid buses through DC-DC converters for voltage support on islanded operation mode. A feed-forward control based dual-loop constant voltage PI control for three-branch interleaved DC-DC converters (TIDC) is proposed...... for storage batteries in DC microgrids. The working principle of TIDC is analyzed, and the factors influencing the response rate based on the dual-loop constant voltage control for TIDC are discussed, and then the method of feed-forward control for TIDC is studied to improve the response rate for load...... changing. A prototype of the TIDC is developed and an experimental platform is built. The experiment results show that DC bus voltage sags or swells caused by load changing can be reduced and the time for voltage recovery can be decreased significantly with the proposed feed-forward control....

  19. Developing and Incorporating Instructional Videos and Quizzes as a Blended and Online Learning Component in an Undergraduate Optical Microscopy Curriculum.

    Science.gov (United States)

    Tramontano, S.; Gualda, G. A. R.; Claiborne, L. L.; Brame, C.

    2015-12-01

    Optical mineralogy is not an easy skill to master as an undergraduate, but it is crucial for understanding what the Earth is made out of. It is a supplementary and specific skillset typically taught in a microscope lab supporting lessons on crystallography, chemistry and mineral analysis in the classroom. Mastering the basic skills is required for advancement in courses that utilize thin sections in teaching igneous, metamorphic, and sedimentary rocks. This project asks: Will exposing undergraduate Earth and environmental studies students to optical microscopy figures in videos prior to lab assist in the acquisition of skills required to describe and distinguish Earth materials? This project is conducted in conjunction with the Blended and Online Learning Design (BOLD) Fellowship offered through the Center for Teaching (CFT) at Vanderbilt University. Eight videos and accompanying pre-lab questions were hosted online weekly in a semester-long, undergraduate Earth materials course. The focus of the design of the videos and supporting questions is specifically on microscopy skills rather than on optics concepts, which is taught post-video. The videos were made available prior to a weekly lab with the intent of familiarizing the student with the types of images and information he/she should obtain with the microscope. Multiple choice, formative-style questions accompany the videos in an online-hosted assignment. These questions are graded on basis of completion and are intended to aid in student metacognition. Subjects include students in the Vanderbilt University Earth Materials course and students from the Hanover College Mineralogy course. The effectiveness of the videos is assessed in two parts: (1) Comparing the homework and lab final grades of the students this year with those of the students last year (2) Analysis of a weekly questionnaire. The answers after each week will be compiled and compared. Collecting data from Vanderbilt University students and Hanover

  20. Radar HRRP Target Recognition Based on Stacked Autoencoder and Extreme Learning Machine.

    Science.gov (United States)

    Zhao, Feixiang; Liu, Yongxiang; Huo, Kai; Zhang, Shuanghui; Zhang, Zhongshuai

    2018-01-10

    A novel radar high-resolution range profile (HRRP) target recognition method based on a stacked autoencoder (SAE) and extreme learning machine (ELM) is presented in this paper. As a key component of deep structure, the SAE does not only learn features by making use of data, it also obtains feature expressions at different levels of data. However, with the deep structure, it is hard to achieve good generalization performance with a fast learning speed. ELM, as a new learning algorithm for single hidden layer feedforward neural networks (SLFNs), has attracted great interest from various fields for its fast learning speed and good generalization performance. However, ELM needs more hidden nodes than conventional tuning-based learning algorithms due to the random set of input weights and hidden biases. In addition, the existing ELM methods cannot utilize the class information of targets well. To solve this problem, a regularized ELM method based on the class information of the target is proposed. In this paper, SAE and the regularized ELM are combined to make full use of their advantages and make up for each of their shortcomings. The effectiveness of the proposed method is demonstrated by experiments with measured radar HRRP data. The experimental results show that the proposed method can achieve good performance in the two aspects of real-time and accuracy, especially when only a few training samples are available.

  1. Feedback and feedforward locomotor adaptations to ankle-foot load in people with incomplete spinal cord injury.

    Science.gov (United States)

    Gordon, Keith E; Wu, Ming; Kahn, Jennifer H; Schmit, Brian D

    2010-09-01

    Humans with spinal cord injury (SCI) modulate locomotor output in response to limb load. Understanding the neural control mechanisms responsible for locomotor adaptation could provide a framework for selecting effective interventions. We quantified feedback and feedforward locomotor adaptations to limb load modulations in people with incomplete SCI. While subjects airstepped (stepping performed with kinematic assistance and 100% bodyweight support), a powered-orthosis created a dorisflexor torque during the "stance phase" of select steps producing highly controlled ankle-load perturbations. When given repetitive, stance phase ankle-load, the increase in hip extension work, 0.27 J/kg above baseline (no ankle-load airstepping), was greater than the response to ankle-load applied during a single step, 0.14 J/kg (P = 0.029). This finding suggests that, at the hip, subjects produced both feedforward and feedback locomotor modulations. We estimate that, at the hip, the locomotor response to repetitive ankle-load was modulated almost equally by ongoing feedback and feedforward adaptations. The majority of subjects also showed after-effects in hip kinetic patterns that lasted 3 min in response to repetitive loading, providing additional evidence of feedforward locomotor adaptations. The magnitude of the after-effect was proportional to the response to repetitive ankle-foot load (R(2) = 0.92). In contrast, increases in soleus EMG amplitude were not different during repetitive and single-step ankle-load exposure, suggesting that ankle locomotor modulations were predominately feedback-based. Although subjects made both feedback and feedforward locomotor adaptations to changes in ankle-load, between-subject variations suggest that walking function may be related to the ability to make feedforward adaptations.

  2. A case study of translating ACGME practice-based learning and improvement requirements into reality: systems quality improvement projects as the key component to a comprehensive curriculum.

    Science.gov (United States)

    Tomolo, A M; Lawrence, R H; Aron, D C

    2009-10-01

    In 2002, the Accreditation Council for Graduate Medical Education (ACGME) introduced a new requirement: residents must demonstrate competency in Practice-Based Learning and Improvement (PBLI). Training in this domain is still not consistently integrated into programmes, with few, if any, adequately going beyond knowledge of basic content and addressing all components of the requirement. To summarise the implementation of a PBLI curriculum designed to address all components of the requirement and to evaluate the impact on the practice system. A case-study approach was used for identifying and evaluating the steps for delivering the curriculum, along with the Model for Improvement's successive Plan-Do-Study-Act (PDSA) cycles (July 2004-May 2006). Notes from curriculum development meetings, notes and presentation slides made by teams about their projects, resident curriculum exit evaluations curriculum and interviews. Residents reported high levels of comfort by applying PBLI-related knowledge and skills and that the curriculum improved their ability to do various PBLI tasks. The involvement of multiple stakeholders increased. Twelve of the 15 teams' suggestions with practical systems-relevant outcomes were implemented and sustained beyond residents' project periods. While using the traditional PDSA cycles was helpful, there were limitations. A PBLI curriculum that is centred around practice-based quality improvement projects can fulfil the objectives of this ACGME competency while accomplishing sustained outcomes in quality improvement. A comprehensive curriculum is an investment but offers organisational rewards. We propose a more realistic and informative representation of rapid PDSA cycle changes.

  3. Extended Stable Boundary of LCL-Filtered Grid-Connected Inverter Based on An Improved Grid-Voltage Feedforward Control

    DEFF Research Database (Denmark)

    Lu, Minghui; Xin, Zhen; Wang, Xiongfei

    2016-01-01

    should be designed under one-sixth of sampling frequency. However, the low resonance frequency leads to a comparatively large filter inductance or/and capacitance. To extend the stable boundary to the region above fs/6, this paper proposes a novel voltage feedforward scheme for the LCL-filtered inverter....... Theoretical analysis is then provided to validate its feasibility and stability. Compared to other widely used active damping strategies, no extra sensors are needed because the filter capacitor voltage, which is used for voltage feedforward control, is also sampled for phase-locked loop in this paper...

  4. Regulation of Cortical Dynamic Range by Background Synaptic Noise and Feedforward Inhibition.

    Science.gov (United States)

    Khubieh, Ayah; Ratté, Stéphanie; Lankarany, Milad; Prescott, Steven A

    2016-08-01

    The cortex encodes a broad range of inputs. This breadth of operation requires sensitivity to weak inputs yet non-saturating responses to strong inputs. If individual pyramidal neurons were to have a narrow dynamic range, as previously claimed, then staggered all-or-none recruitment of those neurons would be necessary for the population to achieve a broad dynamic range. Contrary to this explanation, we show here through dynamic clamp experiments in vitro and computer simulations that pyramidal neurons have a broad dynamic range under the noisy conditions that exist in the intact brain due to background synaptic input. Feedforward inhibition capitalizes on those noise effects to control neuronal gain and thereby regulates the population dynamic range. Importantly, noise allows neurons to be recruited gradually and occludes the staggered recruitment previously attributed to heterogeneous excitation. Feedforward inhibition protects spike timing against the disruptive effects of noise, meaning noise can enable the gain control required for rate coding without compromising the precise spike timing required for temporal coding. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  5. A technique for improved stability of adaptive feedforward controllers without detailed uncertainty measurements

    International Nuclear Information System (INIS)

    Berkhoff, A P

    2012-01-01

    Model errors in adaptive controllers for the reduction of broadband noise and vibrations may lead to unstable systems or increased error signals. Previous research on active structures with small damping has shown that the addition of a low-authority controller which increases damping in the system may lead to improved performance of an adaptive, high-authority controller. Other researchers have suggested the use of frequency dependent regularization based on measured uncertainties. In this paper an alternative method is presented that avoids the disadvantages of these methods, namely the additional complex hardware and the need to obtain detailed information on the uncertainties. An analysis is made of an adaptive feedforward controller in which a difference exists between the secondary path and the model as used in the controller. The real parts of the eigenvalues that determine the stability of the system are expressed in terms of the amount of uncertainty and the singular values of the secondary path. Modifications of the feedforward control scheme are suggested that aim to improve performance without requiring detailed uncertainty measurements. (paper)

  6. System Dynamics and Feedforward Control for Tether-Net Space Robot System

    Directory of Open Access Journals (Sweden)

    Guang Zhai

    2009-06-01

    Full Text Available A new concept using flexible tether-net system to capture space debris is presented in this paper. With a mass point assumption the tether-net system dynamic model is established in orbital frame by applying Lagrange Equations. In order to investigate the net in-plane trajectories during after cast, the non-control R-bar and V-bar captures are simulated with ignoring the out-of-plane libration, the effect of in-plane libration on the trajectories of the capture net is demonstrated by simulation results. With an effort to damp the in-plane libration, the control scheme based on tether tension is investigated firstly, after that an integrated control scheme is proposed by introduced the thrusters into the system, the nonlinear close-loop dynamics is linearised by feedforward strategy, the simulation results show that feedforward controllor is effective for in-plane libration damping and enable the capture net to track an expected trajectory.

  7. Combined feedforward and model-assisted active disturbance rejection control for non-minimum phase system.

    Science.gov (United States)

    Sun, Li; Li, Donghai; Gao, Zhiqiang; Yang, Zhao; Zhao, Shen

    2016-09-01

    Control of the non-minimum phase (NMP) system is challenging, especially in the presence of modelling uncertainties and external disturbances. To this end, this paper presents a combined feedforward and model-assisted Active Disturbance Rejection Control (MADRC) strategy. Based on the nominal model, the feedforward controller is used to produce a tracking performance that has minimum settling time subject to a prescribed undershoot constraint. On the other hand, the unknown disturbances and uncertain dynamics beyond the nominal model are compensated by MADRC. Since the conventional Extended State Observer (ESO) is not suitable for the NMP system, a model-assisted ESO (MESO) is proposed based on the nominal observable canonical form. The convergence of MESO is proved in time domain. The stability, steady-state characteristics and robustness of the closed-loop system are analyzed in frequency domain. The proposed strategy has only one tuning parameter, i.e., the bandwidth of MESO, which can be readily determined with a prescribed robustness level. Some comparative examples are given to show the efficacy of the proposed method. This paper depicts a promising prospect of the model-assisted ADRC in dealing with complex systems. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

  8. Intelligence rules of hysteresis in the feedforward trajectory control of piezoelectrically-driven nanostagers

    Science.gov (United States)

    Bashash, Saeid; Jalili, Nader

    2007-02-01

    Piezoelectrically-driven nanostagers have limited performance in a variety of feedforward and feedback positioning applications because of their nonlinear hysteretic response to input voltage. The hysteresis phenomenon is well known for its complex and multi-path behavior. To realize the underlying physics of this phenomenon and to develop an efficient compensation strategy, the intelligence properties of hysteresis with the effects of non-local memories are discussed here. Through performing a set of experiments on a piezoelectrically-driven nanostager with a high resolution capacitive position sensor, it is shown that for the precise prediction of the hysteresis path, certain memory units are required to store the previous hysteresis trajectory data. Based on the experimental observations, a constitutive memory-based mathematical modeling framework is developed and trained for the precise prediction of the hysteresis path for arbitrarily assigned input profiles. Using the inverse hysteresis model, a feedforward control strategy is then developed and implemented on the nanostager to compensate for the ever-present nonlinearity. Experimental results demonstrate that the controller remarkably eliminates the nonlinear effect, if memory units are sufficiently chosen for the inverse model.

  9. Simultaneous feedforward recruitment of the vasti in untrained postural tasks can be restored by physical therapy.

    Science.gov (United States)

    Cowan, Sallie M; Bennell, Kim L; Hodges, Paul W; Crossley, Kay M; McConnell, Jenny

    2003-05-01

    Physical therapy rehabilitation strategies are commonly directed at the alteration of muscle recruitment in functional movements. The aim of this study was to investigate whether feedforward strategies of the vasti in people with patellofemoral pain syndrome can be changed by a physical therapy treatment program in a randomised, double blind, placebo controlled trial. Forty (25 female, 15 male) subjects aged 40 yrs or less (27.2+/-7.8 yrs). Subjects were allocated to either a placebo treatment or a physical therapy intervention program. The postural challenge used as the outcome measure was not included in the training program. Electromyography (EMG) onsets of vastus medialis obliquus (VMO), vastus lateralis (VL), tibialis anterior and soleus were assessed before and after the six week standardised treatment programs. At baseline the EMG onset of VL occurred prior to that of VMO in both subject groups. Following physical therapy intervention there was a significant change in the time of onset of EMG of VMO compared to VL with the onsets occurring simultaneously. This change was associated with a reduction in symptoms. In contrast, following placebo intervention the EMG onset of VL still occurred prior to that of VMO. The results indicate that the feedforward strategy used by the central nervous system to control the patella can be restored. Importantly, the data suggest that this intervention produced a change that was transferred to a task that was not specifically included in the training program. Furthermore, the change in motor control was associated with clinical improvement in symptoms.

  10. Automated optimal coordination of multiple-DOF neuromuscular actions in feedforward neuroprostheses.

    Science.gov (United States)

    Lujan, J Luis; Crago, Patrick E

    2009-01-01

    This paper describes a new method for designing feedforward controllers for multiple-muscle, multiple-DOF, motor system neural prostheses. The design process is based on experimental measurement of the forward input/output properties of the neuromechanical system and numerical optimization of stimulation patterns to meet muscle coactivation criteria, thus resolving the muscle redundancy (i.e., overcontrol) and the coupled DOF problems inherent in neuromechanical systems. We designed feedforward controllers to control the isometric forces at the tip of the thumb in two directions during stimulation of three thumb muscles as a model system. We tested the method experimentally in ten able-bodied individuals and one patient with spinal cord injury. Good control of isometric force in both DOFs was observed, with rms errors less than 10% of the force range in seven experiments and statistically significant correlations between the actual and target forces in all ten experiments. Systematic bias and slope errors were observed in a few experiments, likely due to the neuromuscular fatigue. Overall, the tests demonstrated the ability of a general design approach to satisfy both control and coactivation criteria in multiple-muscle, multiple-axis neuromechanical systems, which is applicable to a wide range of neuromechanical systems and stimulation electrodes.

  11. Feedforward Control of a 3-D Physiological Articulatory Model for Vowel Production

    Institute of Scientific and Technical Information of China (English)

    FANG Qiang; Akikazu Nishikido; Jianwu Dang

    2009-01-01

    A three-dimensional (3-D) physiological articulatory model was developed to account for the bio-mechanical properties of the speech organs in speech production. Control of the model to investigate the mechanism of speech production requires an efficient control module to estimate muscle activation patterns, which is used to manipulate the 3-D physiological arUculatory model, according to the desired articulatory posture. For this purpose, a feedforward control strategy was developed by mapping the articulatory target to the corresponding muscle activation pattern via the intrinsic representation of vowel articulation. In this process, the articulatory postures are first mapped to the corresponding intrinsic representations; then, the articulatory postures are clustered in the intrinsic representations space and a nonlinear function is ap-proximated for each cluster to map the intrinsic representation of vowel articulation to the muscle activation pattern by using general regression neural networks (GRNN). The results show that the feedforward control module is able to manipulate the 3-D physiological articulatory model for vowel production with high accu-racy both acoustically and articulatodly.

  12. Perceptual decision-making difficulty modulates feedforward effective connectivity to the dorsolateral prefrontal cortex

    Directory of Open Access Journals (Sweden)

    Bidhan eLamichhane

    2015-09-01

    Full Text Available Diverse cortical structures are known to coordinate activity as a network in relaying and processing of visual information to discriminate visual objects. However, how this discrimination is achieved is still largely unknown. To contribute to answering this question, we used face-house categorization tasks with three levels of noise in face and house images in functional magnetic resonance imaging (fMRI experiments involving thirty-three participants. The behavioral performance error and response time (RT were correlated with noise in face-house images. We then built dynamical causal models (DCM of fMRI blood-oxygenation level dependent (BOLD signals from the face and house category-specific regions in ventral temporal cortex, the fusiform face area (FFA and parahippocampal place area (PPA, and the dorsolateral prefrontal cortex (dlPFC. We found a strong feed-forward intrinsic connectivity pattern from FFA and PPA to dlPFC. Importantly, the feed-forward connectivity to dlPFC was significantly modulated by the perception of both faces and houses. The dlPFC-BOLD activity, the connectivity from FFA and PPA to the dlPFC all increased with noise level. These results suggest that the FFA-PPA-dlPFC network plays an important role for relaying and integrating competing sensory information to arrive at perceptual decisions.

  13. Visual language recognition with a feed-forward network of spiking neurons

    Energy Technology Data Exchange (ETDEWEB)

    Rasmussen, Craig E [Los Alamos National Laboratory; Garrett, Kenyan [Los Alamos National Laboratory; Sottile, Matthew [GALOIS; Shreyas, Ns [INDIANA UNIV.

    2010-01-01

    An analogy is made and exploited between the recognition of visual objects and language parsing. A subset of regular languages is used to define a one-dimensional 'visual' language, in which the words are translational and scale invariant. This allows an exploration of the viewpoint invariant languages that can be solved by a network of concurrent, hierarchically connected processors. A language family is defined that is hierarchically tiling system recognizable (HREC). As inspired by nature, an algorithm is presented that constructs a cellular automaton that recognizes strings from a language in the HREC family. It is demonstrated how a language recognizer can be implemented from the cellular automaton using a feed-forward network of spiking neurons. This parser recognizes fixed-length strings from the language in parallel and as the computation is pipelined, a new string can be parsed in each new interval of time. The analogy with formal language theory allows inferences to be drawn regarding what class of objects can be recognized by visual cortex operating in purely feed-forward fashion and what class of objects requires a more complicated network architecture.

  14. Counteracting Rotor Imbalance in a Bearingless Motor System with Feedforward Control

    Science.gov (United States)

    Kascak, Peter Eugene; Jansen, Ralph H.; Dever, Timothy; Nagorny, Aleksandr; Loparo, Kenneth

    2012-01-01

    In standard motor applications, traditional mechanical bearings represent the most economical approach to rotor suspension. However, in certain high performance applications, rotor suspension without bearing contact is either required or highly beneficial. Such applications include very high speed, extreme environment, or limited maintenance access applications. This paper extends upon a novel bearingless motor concept, in which full five-axis levitation and rotation of the rotor is achieved using two motors with opposing conical air-gaps. By leaving the motors' pole-pairs unconnected, different d-axis flux in each pole-pair is created, generating a flux imbalance which creates lateral force. Note this is approach is different than that used in previous bearingless motors, which use separate windings for levitation and rotation. This paper will examine the use of feedforward control to counteract synchronous whirl caused by rotor imbalance. Experimental results will be presented showing the performance of a prototype bearingless system, which was sized for a high speed flywheel energy storage application, with and without feedforward control.

  15. Advances in coherent optical modems and 16-QAM transmission with feedforward carrier recovery

    Science.gov (United States)

    Noé, Reinhold; Hoffmann, Sebastian; Wördehoff, Christian; Al-Bermani, Ali; El-Darawy, Mohamed

    2011-01-01

    Polarization multiplexing and quadrature phase shift keying (QPSK) both double spectral efficiency. Combined with synchronous coherent polarization diverse intradyne receivers this modulation format is ultra-robust and cost-efficient. A feedforward carrier recovery is required in order to tolerate phase noise of normal DFB lasers. Signal processing in the digital domain permits compensation of at least chromatic and polarization mode dispersion. Some companies have products on the market, others are working on them. For 100 GbE transmission, 50 GHz channel spacing is sufficient. 16ary quadrature amplitude modulation (16-QAM) is attractive to double capacity once more, possibly in a modulation format flexible transponder which is switched down to QPSK only if system margin is too low. For 16-QAM the phase noise problem is sharply increased. However, also here a feedforward carrier recovery has been implemented. A number of carrier phase angles is tested in parallel, and the recovered data is selected for that phase angle where squared distance of recovered data to the nearest constellation point, averaged over a number of symbols, is minimum. An intradyne/selfhomodyne synchronous coherent 16-QAM experiment (2.5 Gb/s, 81 km) is presented.

  16. Local excitation-inhibition ratio for synfire chain propagation in feed-forward neuronal networks

    Science.gov (United States)

    Guo, Xinmeng; Yu, Haitao; Wang, Jiang; Liu, Jing; Cao, Yibin; Deng, Bin

    2017-09-01

    A leading hypothesis holds that spiking activity propagates along neuronal sub-populations which are connected in a feed-forward manner, and the propagation efficiency would be affected by the dynamics of sub-populations. In this paper, how the interaction between local excitation and inhibition effects on synfire chain propagation in feed-forward network (FFN) is investigated. The simulation results show that there is an appropriate excitation-inhibition (EI) ratio maximizing the performance of synfire chain propagation. The optimal EI ratio can significantly enhance the selectivity of FFN to synchronous signals, which thereby increases the stability to background noise. Moreover, the effect of network topology on synfire chain propagation is also investigated. It is found that synfire chain propagation can be maximized by an optimal interlayer linking probability. We also find that external noise is detrimental to synchrony propagation by inducing spiking jitter. The results presented in this paper may provide insights into the effects of network dynamics on neuronal computations.

  17. Performance of active feedforward control systems in non-ideal, synthesized diffuse sound fields.

    Science.gov (United States)

    Misol, Malte; Bloch, Christian; Monner, Hans Peter; Sinapius, Michael

    2014-04-01

    The acoustic performance of passive or active panel structures is usually tested in sound transmission loss facilities. A reverberant sending room, equipped with one or a number of independent sound sources, is used to generate a diffuse sound field excitation which acts as a disturbance source on the structure under investigation. The spatial correlation and coherence of such a synthesized non-ideal diffuse-sound-field excitation, however, might deviate significantly from the ideal case. This has consequences for the operation of an active feedforward control system which heavily relies on the acquisition of coherent disturbance source information. This work, therefore, evaluates the spatial correlation and coherence of ideal and non-ideal diffuse sound fields and considers the implications on the performance of a feedforward control system. The system under consideration is an aircraft-typical double panel system, equipped with an active sidewall panel (lining), which is realized in a transmission loss facility. Experimental results for different numbers of sound sources in the reverberation room are compared to simulation results of a comparable generic double panel system excited by an ideal diffuse sound field. It is shown that the number of statistically independent noise sources acting on the primary structure of the double panel system depends not only on the type of diffuse sound field but also on the sample lengths of the processed signals. The experimental results show that the number of reference sensors required for a defined control performance exhibits an inverse relationship to control filter length.

  18. Adaptive feedforward control for improving output power response of CO2 laser; Tekiogata feedforward ni yoru laser shutsuryoku oto no kaizen

    Energy Technology Data Exchange (ETDEWEB)

    Imai, Y.; Takahashi, t.; Morita, A. [Mitsubishi Electric Corp., Tokyo (Japan)

    1998-03-31

    Feedback control has been used to stabilize the steady-state output power of a CO2 laser to overcome the problems caused by the change in the temperature/deterioration of CO2 gas. The transient response, however, is as slow as a few hundred milliseconds because of the slow dynamics of a thermopile power sensor. When machining conditions of a CO2 laser are changed, this rather slow response requires an extra dwell time, resulting in low productivity of the machining. To cope with this problem, the authors have developed adaptive feedforward control for a CO2 laser in addition to conventional feedback control. The model of a CO2 laser is described as a gain, which is varied by the setting parameters; laser power, pulse frequency and duty factor, as well as gas conditions. In this paper, two new variables, effective discharge power and threshold discharge power, are introduced to obtain a compact and adjustable model. With the proposed control system, the step response time of a laser power is reduced to less than ten milliseconds without overshoot, and can be set to desired constant time. The effects of such a fast and stable response on the machining speed and machining quality are examined. The experimental results show that for thin metal line-cutting, neither the melt-off area nor dross is observed even in the no-dwell time case. For thin metal hole-cutting, the machining speed is improved by 30%. 11 refs., 14 figs., 3 tabs.

  19. Evaluation as a powerful practice in digital learning processes

    DEFF Research Database (Denmark)

    Sørensen, Birgitte Holm; Levinsen, Karin

    2014-01-01

    The present paper is based on two empirical research studies. The Netbook 1:1 project (2009–2012), funded by the municipality of Gentofte and Microsoft Denmark, is complete, while Students’ digital production and students as learning designers (2013–2015), funded by the Danish Ministry of Educati...... as a learning practice in a digitalised learning context focuses on students as actors, adressing their self‐reflections, responses to feedback from peers and feedforward processes....

  20. Fastest learning in small-world neural networks

    International Nuclear Information System (INIS)

    Simard, D.; Nadeau, L.; Kroeger, H.

    2005-01-01

    We investigate supervised learning in neural networks. We consider a multi-layered feed-forward network with back propagation. We find that the network of small-world connectivity reduces the learning error and learning time when compared to the networks of regular or random connectivity. Our study has potential applications in the domain of data-mining, image processing, speech recognition, and pattern recognition

  1. Computer Simulation Tests of Feedback Error Learning Controller with IDM and ISM for Functional Electrical Stimulation in Wrist Joint Control

    Directory of Open Access Journals (Sweden)

    Takashi Watanabe

    2010-01-01

    Full Text Available Feedforward controller would be useful for hybrid Functional Electrical Stimulation (FES system using powered orthotic devices. In this paper, Feedback Error Learning (FEL controller for FES (FEL-FES controller was examined using an inverse statics model (ISM with an inverse dynamics model (IDM to realize a feedforward FES controller. For FES application, the ISM was tested in learning off line using training data obtained by PID control of very slow movements. Computer simulation tests in controlling wrist joint movements showed that the ISM performed properly in positioning task and that IDM learning was improved by using the ISM showing increase of output power ratio of the feedforward controller. The simple ISM learning method and the FEL-FES controller using the ISM would be useful in controlling the musculoskeletal system that has nonlinear characteristics to electrical stimulation and therefore is expected to be useful in applying to hybrid FES system using powered orthotic device.

  2. Second-Order Learning Methods for a Multilayer Perceptron

    International Nuclear Information System (INIS)

    Ivanov, V.V.; Purehvdorzh, B.; Puzynin, I.V.

    1994-01-01

    First- and second-order learning methods for feed-forward multilayer neural networks are studied. Newton-type and quasi-Newton algorithms are considered and compared with commonly used back-propagation algorithm. It is shown that, although second-order algorithms require enhanced computer facilities, they provide better convergence and simplicity in usage. 13 refs., 2 figs., 2 tabs

  3. Advances in data-driven optimization of parametric and non-parametric feedforward control designs with industrial applications

    NARCIS (Netherlands)

    Tousain, R.L.; Meulen, van der S.H.; Hof, van den P.M.J.; Scherer, C.; Heuberger, P.S.C.

    2009-01-01

    The performance of many industrial control systems is determined to a large extent by the quality of both setpoint and disturbance feedforward signals. The quality that is required for a high tracking performance is generally not achieved when the controller parameters are determined on the basis of

  4. Toward heterogeneity in feedforward network with synaptic delays based on FitzHugh-Nagumo model

    Science.gov (United States)

    Qin, Ying-Mei; Men, Cong; Zhao, Jia; Han, Chun-Xiao; Che, Yan-Qiu

    2018-01-01

    We focus on the role of heterogeneity on the propagation of firing patterns in feedforward network (FFN). Effects of heterogeneities both in parameters of neuronal excitability and synaptic delays are investigated systematically. Neuronal heterogeneity is found to modulate firing rates and spiking regularity by changing the excitability of the network. Synaptic delays are strongly related with desynchronized and synchronized firing patterns of the FFN, which indicate that synaptic delays may play a significant role in bridging rate coding and temporal coding. Furthermore, quasi-coherence resonance (quasi-CR) phenomenon is observed in the parameter domain of connection probability and delay-heterogeneity. All these phenomena above enable a detailed characterization of neuronal heterogeneity in FFN, which may play an indispensable role in reproducing the important properties of in vivo experiments.

  5. Modeling of quasistatic magnetic hysteresis with feed-forward neural networks

    International Nuclear Information System (INIS)

    Makaveev, Dimitre; Dupre, Luc; De Wulf, Marc; Melkebeek, Jan

    2001-01-01

    A modeling technique for rate-independent (quasistatic) scalar magnetic hysteresis is presented, using neural networks. Based on the theory of dynamic systems and the wiping-out and congruency properties of the classical scalar Preisach hysteresis model, the choice of a feed-forward neural network model is motivated. The neural network input parameters at each time step are the corresponding magnetic field strength and memory state, thereby assuring accurate prediction of the change of magnetic induction. For rate-independent hysteresis, the current memory state can be determined by the last extreme magnetic field strength and induction values, kept in memory. The choice of a network training set is motivated and the performance of the network is illustrated for a test set not used during training. Very accurate prediction of both major and minor hysteresis loops is observed, proving that the neural network technique is suitable for hysteresis modeling. [copyright] 2001 American Institute of Physics

  6. A Novel Memristive Multilayer Feedforward Small-World Neural Network with Its Applications in PID Control

    Directory of Open Access Journals (Sweden)

    Zhekang Dong

    2014-01-01

    Full Text Available In this paper, we present an implementation scheme of memristor-based multilayer feedforward small-world neural network (MFSNN inspirited by the lack of the hardware realization of the MFSNN on account of the need of a large number of electronic neurons and synapses. More specially, a mathematical closed-form charge-governed memristor model is presented with derivation procedures and the corresponding Simulink model is presented, which is an essential block for realizing the memristive synapse and the activation function in electronic neurons. Furthermore, we investigate a more intelligent memristive PID controller by incorporating the proposed MFSNN into intelligent PID control based on the advantages of the memristive MFSNN on computation speed and accuracy. Finally, numerical simulations have demonstrated the effectiveness of the proposed scheme.

  7. Effects of secondary loudspeaker properties on broadband feedforward active duct noise control.

    Science.gov (United States)

    Chan, Yum-Ji; Huang, Lixi; Lam, James

    2013-07-01

    Dependence of the performance of feedforward active duct noise control on secondary loudspeaker parameters is investigated. Noise reduction performance can be improved if the force factor of the secondary loudspeaker is higher. For example, broadband noise reduction improvement up to 1.6 dB is predicted by increasing the force factor by 50%. In addition, a secondary loudspeaker with a larger force factor was found to have quicker convergence in the adaptive algorithm in experiment. In simulations, noise reduction is improved in using an adaptive algorithm by using a secondary loudspeaker with a heavier moving mass. It is predicted that an extra broadband noise reduction of more than 7 dB can be gained using an adaptive filter if the force factor, moving mass and coil inductance of a commercially available loudspeaker are doubled. Methods to increase the force factor beyond those of commercially available loudspeakers are proposed.

  8. Finite-time stabilization of uncertain nonholonomic systems in feedforward-like form by output feedback.

    Science.gov (United States)

    Gao, Fangzheng; Wu, Yuqiang; Zhang, Zhongcai

    2015-11-01

    This paper investigates the problem of finite-time stabilization by output feedback for a class of nonholonomic systems in chained form with uncertainties. Comparing with the existing relevant literature, a distinguishing feature of the systems under investigation is that the x-subsystem is a feedforward-like rather than feedback-like system. This renders the existing control methods inapplicable to the control problems of the systems. A constructive design procedure for output feedback control is given. The designed controller renders that the states of closed-loop system are regulated to zero in a finite time. Two simulation examples are provided to illustrate the effectiveness of the proposed approach. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

  9. Increasing LIGO sensitivity by feedforward subtraction of auxiliary length control noise

    International Nuclear Information System (INIS)

    Meadors, Grant David; Riles, Keith; Kawabe, Keita

    2014-01-01

    LIGO, the Laser Interferometer Gravitational-wave Observatory, has been designed and constructed to measure gravitational wave strain via differential arm length. The LIGO 4 km Michelson arms with Fabry–Perot cavities have auxiliary length control servos for suppressing Michelson motion of the beam-splitter and arm cavity input mirrors, which degrades interferometer sensitivity. We demonstrate how a post facto pipeline improves a data sample from LIGO Science Run 6 with feedforward subtraction. Dividing data into 1024 s windows, we numerically fit filter functions representing the frequency-domain transfer functions from Michelson length channels into the gravitational-wave strain data channel for each window, then subtract the filtered Michelson channel noise (witness) from the strain channel (target). In this paper we describe the algorithm, assess achievable improvements in sensitivity to astrophysical sources, and consider relevance to future interferometry. (paper)

  10. A novel memristive multilayer feedforward small-world neural network with its applications in PID control.

    Science.gov (United States)

    Dong, Zhekang; Duan, Shukai; Hu, Xiaofang; Wang, Lidan; Li, Hai

    2014-01-01

    In this paper, we present an implementation scheme of memristor-based multilayer feedforward small-world neural network (MFSNN) inspirited by the lack of the hardware realization of the MFSNN on account of the need of a large number of electronic neurons and synapses. More specially, a mathematical closed-form charge-governed memristor model is presented with derivation procedures and the corresponding Simulink model is presented, which is an essential block for realizing the memristive synapse and the activation function in electronic neurons. Furthermore, we investigate a more intelligent memristive PID controller by incorporating the proposed MFSNN into intelligent PID control based on the advantages of the memristive MFSNN on computation speed and accuracy. Finally, numerical simulations have demonstrated the effectiveness of the proposed scheme.

  11. GA-optimized feedforward-PID tracking control for a rugged electrohydraulic system design.

    Science.gov (United States)

    Sarkar, B K; Mandal, P; Saha, R; Mookherjee, S; Sanyal, D

    2013-11-01

    Rugged electrohydraulic systems are preferred for remote and harsh applications. Despite the low bandwidth, large deadband and flow nonlinearities in proportional valves valve and highly nonlinear friction in industry-grade cylinders that comprise rugged systems, their maintenance are much easier than very sophisticated and delicate servocontrol and servocylinder systems. With the target of making the easily maintainable system to perform comparably to a servosystem, a feedforward control has been designed here for compensating the nonlinearities. A PID feedback of the piston displacement has been employed in tandem for absorbing the unmodeled effects. All the controller parameters have been optimized by a real-coded genetic algorithm. The agreement between the achieved real-time responses for step and sinusoidal demands with those achieved by modern servosystems clearly establishes the acceptability of the controller design. Copyright © 2013 ISA. Published by Elsevier Ltd. All rights reserved.

  12. Multiple-Input Subject-Specific Modeling of Plasma Glucose Concentration for Feedforward Control.

    Science.gov (United States)

    Kotz, Kaylee; Cinar, Ali; Mei, Yong; Roggendorf, Amy; Littlejohn, Elizabeth; Quinn, Laurie; Rollins, Derrick K

    2014-11-26

    The ability to accurately develop subject-specific, input causation models, for blood glucose concentration (BGC) for large input sets can have a significant impact on tightening control for insulin dependent diabetes. More specifically, for Type 1 diabetics (T1Ds), it can lead to an effective artificial pancreas (i.e., an automatic control system that delivers exogenous insulin) under extreme changes in critical disturbances. These disturbances include food consumption, activity variations, and physiological stress changes. Thus, this paper presents a free-living, outpatient, multiple-input, modeling method for BGC with strong causation attributes that is stable and guards against overfitting to provide an effective modeling approach for feedforward control (FFC). This approach is a Wiener block-oriented methodology, which has unique attributes for meeting critical requirements for effective, long-term, FFC.

  13. Design of an embedded inverse-feedforward biomolecular tracking controller for enzymatic reaction processes.

    Science.gov (United States)

    Foo, Mathias; Kim, Jongrae; Sawlekar, Rucha; Bates, Declan G

    2017-04-06

    Feedback control is widely used in chemical engineering to improve the performance and robustness of chemical processes. Feedback controllers require a 'subtractor' that is able to compute the error between the process output and the reference signal. In the case of embedded biomolecular control circuits, subtractors designed using standard chemical reaction network theory can only realise one-sided subtraction, rendering standard controller design approaches inadequate. Here, we show how a biomolecular controller that allows tracking of required changes in the outputs of enzymatic reaction processes can be designed and implemented within the framework of chemical reaction network theory. The controller architecture employs an inversion-based feedforward controller that compensates for the limitations of the one-sided subtractor that generates the error signals for a feedback controller. The proposed approach requires significantly fewer chemical reactions to implement than alternative designs, and should have wide applicability throughout the fields of synthetic biology and biological engineering.

  14. Finite-time stabilization for a class of nonholonomic feedforward systems subject to inputs saturation.

    Science.gov (United States)

    Gao, Fangzheng; Yuan, Ye; Wu, Yuqiang

    2016-09-01

    This paper studies the problem of finite-time stabilization by state feedback for a class of uncertain nonholonomic systems in feedforward-like form subject to inputs saturation. Under the weaker homogeneous condition on systems growth, a saturated finite-time control scheme is developed by exploiting the adding a power integrator method, the homogeneous domination approach and the nested saturation technique. Together with a novel switching control strategy, the designed saturated controller guarantees that the states of closed-loop system are regulated to zero in a finite time without violation of the constraint. As an application of the proposed theoretical results, the problem of saturated finite-time control for vertical wheel on rotating table is solved. Simulation results are given to demonstrate the effectiveness of the proposed method. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

  15. Force control of a magnetorheological damper using an elementary hysteresis model-based feedforward neural network

    International Nuclear Information System (INIS)

    Ekkachai, Kittipong; Nilkhamhang, Itthisek; Tungpimolrut, Kanokvate

    2013-01-01

    An inverse controller is proposed for a magnetorheological (MR) damper that consists of a hysteresis model and a voltage controller. The force characteristics of the MR damper caused by excitation signals are represented by a feedforward neural network (FNN) with an elementary hysteresis model (EHM). The voltage controller is constructed using another FNN to calculate a suitable input signal that will allow the MR damper to produce the desired damping force. The performance of the proposed EHM-based FNN controller is experimentally compared to existing control methodologies, such as clipped-optimal control, signum function control, conventional FNN, and recurrent neural network with displacement or velocity inputs. The results show that the proposed controller, which does not require force feedback to implement, provides excellent accuracy, fast response time, and lower energy consumption. (paper)

  16. Propagation of spiking regularity and double coherence resonance in feedforward networks.

    Science.gov (United States)

    Men, Cong; Wang, Jiang; Qin, Ying-Mei; Deng, Bin; Tsang, Kai-Ming; Chan, Wai-Lok

    2012-03-01

    We investigate the propagation of spiking regularity in noisy feedforward networks (FFNs) based on FitzHugh-Nagumo neuron model systematically. It is found that noise could modulate the transmission of firing rate and spiking regularity. Noise-induced synchronization and synfire-enhanced coherence resonance are also observed when signals propagate in noisy multilayer networks. It is interesting that double coherence resonance (DCR) with the combination of synaptic input correlation and noise intensity is finally attained after the processing layer by layer in FFNs. Furthermore, inhibitory connections also play essential roles in shaping DCR phenomena. Several properties of the neuronal network such as noise intensity, correlation of synaptic inputs, and inhibitory connections can serve as control parameters in modulating both rate coding and the order of temporal coding.

  17. Operating wind turbines in strong wind conditions by using feedforward-feedback control

    International Nuclear Information System (INIS)

    Feng, Ju; Sheng, Wen Zhong

    2014-01-01

    Due to the increasing penetration of wind energy into power systems, it becomes critical to reduce the impact of wind energy on the stability and reliability of the overall power system. In precedent works, Shen and his co-workers developed a re-designed operation schema to run wind turbines in strong wind conditions based on optimization method and standard PI feedback control, which can prevent the typical shutdowns of wind turbines when reaching the cut-out wind speed. In this paper, a new control strategy combing the standard PI feedback control with feedforward controls using the optimization results is investigated for the operation of variable-speed pitch-regulated wind turbines in strong wind conditions. It is shown that the developed control strategy is capable of smoothening the power output of wind turbine and avoiding its sudden showdown at high wind speeds without worsening the loads on rotor and blades

  18. Development of Sorting System for Fishes by Feed-forward Neural Networks Using Rotation Invariant Features

    Science.gov (United States)

    Shiraishi, Yuhki; Takeda, Fumiaki

    In this research, we have developed a sorting system for fishes, which is comprised of a conveyance part, a capturing image part, and a sorting part. In the conveyance part, we have developed an independent conveyance system in order to separate one fish from an intertwined group of fishes. After the image of the separated fish is captured in the capturing part, a rotation invariant feature is extracted using two-dimensional fast Fourier transform, which is the mean value of the power spectrum with the same distance from the origin in the spectrum field. After that, the fishes are classified by three-layered feed-forward neural networks. The experimental results show that the developed system classifies three kinds of fishes captured in various angles with the classification ratio of 98.95% for 1044 captured images of five fishes. The other experimental results show the classification ratio of 90.7% for 300 fishes by 10-fold cross validation method.

  19. Simulation of Feedforward-Feedback Control of Dissolved Oxygen of Microbial Repeated Fed-batch Culture

    Directory of Open Access Journals (Sweden)

    Ling Gao

    2016-09-01

    Full Text Available Fed-batch culture is often used in industry, and dissolved oxygen (DO concentration control is important in fermentation process control. DO control is often applied by using feedback (FB control strategy. But, feedforward-feedback (FF-FB control has the advantage in dealing with the time-varying characteristics resulted from the cell growth during the fermentation process. Mathematical modeling and computer simulation is a useful tool in analysis of the control system.  In this research, the FF-FB DO control and FB substrate control of repeated fed-batch culture process is modeled and simulated. The results showed the feasibility of the control strategy. These results are useful for control system development and process analyses and optimization.

  20. Modeling of an industrial process of pleuromutilin fermentation using feed-forward neural networks

    Directory of Open Access Journals (Sweden)

    L. Khaouane

    2013-03-01

    Full Text Available This work investigates the use of artificial neural networks in modeling an industrial fermentation process of Pleuromutilin produced by Pleurotus mutilus in a fed-batch mode. Three feed-forward neural network models characterized by a similar structure (five neurons in the input layer, one hidden layer and one neuron in the output layer are constructed and optimized with the aim to predict the evolution of three main bioprocess variables: biomass, substrate and product. Results show a good fit between the predicted and experimental values for each model (the root mean squared errors were 0.4624% - 0.1234 g/L and 0.0016 mg/g respectively. Furthermore, the comparison between the optimized models and the unstructured kinetic models in terms of simulation results shows that neural network models gave more significant results. These results encourage further studies to integrate the mathematical formulae extracted from these models into an industrial control loop of the process.

  1. Structural vibration control of micro/macro-manipulator using feedforward and feedback approaches

    International Nuclear Information System (INIS)

    Lew, J.Y.; Cannon, D.W.; Magee, D.P.; Book, W.J.

    1995-09-01

    Pacific Northwest Laboratory (PDL) researchers investigated the combined use of two control approaches to minimize micro/macro-manipulator structural vibration: (1) modified input shaping and (2) inertial force active damping control. Modified input shaping (MIS) is used as a feedforward controller to modify reference input by canceling the vibratory motion. Inertial force active damping (IFAD) is applied as a feedback controller to increase the system damping and robustness to unexpected disturbances. Researchers implemented both control schemes in the PNL micro/macro flexible-link manipulator testbed collaborating with Georgia Institute of Technology. The experiments successfully demonstrated the effectiveness of two control approaches in reducing structural vibration. Based on the results of the experiments, the combined use of two controllers is recommended for a micro/macro manipulator to achieve the fastest response to commands while canceling disturbances from unexpected forces

  2. Hippocampus-driven feed-forward inhibition of the prefrontal cortex mediates relapse of extinguished fear

    DEFF Research Database (Denmark)

    Marek, Roger; Jin, Jingji; Goode, Travis D.

    2018-01-01

    The medial prefrontal cortex (mPFC) has been implicated in the extinction of emotional memories, including conditioned fear. We found that ventral hippocampal (vHPC) projections to the infralimbic (IL) cortex recruited parvalbumin-expressing interneurons to counter the expression of extinguished...... fear and promote fear relapse. Whole-cell recordings ex vivo revealed that optogenetic activation of vHPC input to amygdala-projecting pyramidal neurons in the IL was dominated by feed-forward inhibition. Selectively silencing parvalbumin-expressing, but not somatostatin-expressing, interneurons...... in the IL eliminated vHPC-mediated inhibition. In behaving rats, pharmacogenetic activation of vHPC→IL projections impaired extinction recall, whereas silencing IL projectors diminished fear renewal. Intra-IL infusion of GABA receptor agonists or antagonists, respectively, reproduced these effects. Together...

  3. A Novel Feed-Forward Modeling System Leads to Sustained Improvements in Attention and Academic Performance.

    Science.gov (United States)

    McDermott, Ashley F; Rose, Maya; Norris, Troy; Gordon, Eric

    2016-01-28

    This study tested a novel feed-forward modeling (FFM) system as a nonpharmacological intervention for the treatment of ADHD children and the training of cognitive skills that improve academic performance. This study implemented a randomized, controlled, parallel design comparing this FFM with a nonpharmacological community care intervention. Improvements were measured on parent- and clinician-rated scales of ADHD symptomatology and on academic performance tests completed by the participant. Participants were followed for 3 months after training. Participants in the FFM training group showed significant improvements in ADHD symptomatology and academic performance, while the control group did not. Improvements from FFM were sustained 3 months later. The FFM appeared to be an effective intervention for the treatment of ADHD and improving academic performance. This FFM training intervention shows promise as a first-line treatment for ADHD while improving academic performance. © The Author(s) 2016.

  4. Feedback Enhances Feedforward Figure-Ground Segmentation by Changing Firing Mode

    Science.gov (United States)

    Supèr, Hans; Romeo, August

    2011-01-01

    In the visual cortex, feedback projections are conjectured to be crucial in figure-ground segregation. However, the precise function of feedback herein is unclear. Here we tested a hypothetical model of reentrant feedback. We used a previous developed 2-layered feedforwardspiking network that is able to segregate figure from ground and included feedback connections. Our computer model data show that without feedback, neurons respond with regular low-frequency (∼9 Hz) bursting to a figure-ground stimulus. After including feedback the firing pattern changed into a regular (tonic) spiking pattern. In this state, we found an extra enhancement of figure responses and a further suppression of background responses resulting in a stronger figure-ground signal. Such push-pull effect was confirmed by comparing the figure-ground responses withthe responses to a homogenous texture. We propose that feedback controlsfigure-ground segregation by influencing the neural firing patterns of feedforward projecting neurons. PMID:21738747

  5. CUDA-accelerated genetic feedforward-ANN training for data mining

    International Nuclear Information System (INIS)

    Patulea, Catalin; Peace, Robert; Green, James

    2010-01-01

    We present an implementation of genetic algorithm (GA) training of feedforward artificial neural networks (ANNs) targeting commodity graphics cards (GPUs). By carefully mapping the problem onto the unique GPU architecture, we achieve order-of-magnitude speedup over a conventional CPU implementation. Furthermore, we show that the speedup is consistent across a wide range of data set sizes, making this implementation ideal for large data sets. This performance boost enables the genetic algorithm to search a larger subset of the solution space, which results in more accurate pattern classification. Finally, we demonstrate this method in the context of the 2009 UC San Diego Data Mining Contest, achieving a world-class lift on a data set of 94682 e-commerce transactions.

  6. Increasing Fuel Efficiency of Direct Methanol Fuel Cell Systems with Feedforward Control of the Operating Concentration

    Directory of Open Access Journals (Sweden)

    Youngseung Na

    2015-09-01

    Full Text Available Most of the R&D on fuel cells for portable applications concentrates on increasing efficiencies and energy densities to compete with other energy storage devices, especially batteries. To improve the efficiency of direct methanol fuel cell (DMFC systems, several modifications to system layouts and operating strategies are considered in this paper, rather than modifications to the fuel cell itself. Two modified DMFC systems are presented, one with an additional inline mixer and a further modification of it with a separate tank to recover condensed water. The set point for methanol concentration control in the solution is determined by fuel efficiency and varies with the current and other process variables. Feedforward concentration control enables variable concentration for dynamic loads. Simulation results were validated experimentally with fuel cell systems.

  7. CUDA-accelerated genetic feedforward-ANN training for data mining

    Energy Technology Data Exchange (ETDEWEB)

    Patulea, Catalin; Peace, Robert; Green, James, E-mail: cpatulea@sce.carleton.ca, E-mail: rpeace@sce.carleton.ca, E-mail: jrgreen@sce.carleton.ca [School of Systems and Computer Engineering, Carleton University, Ottawa, K1S 5B6 (Canada)

    2010-11-01

    We present an implementation of genetic algorithm (GA) training of feedforward artificial neural networks (ANNs) targeting commodity graphics cards (GPUs). By carefully mapping the problem onto the unique GPU architecture, we achieve order-of-magnitude speedup over a conventional CPU implementation. Furthermore, we show that the speedup is consistent across a wide range of data set sizes, making this implementation ideal for large data sets. This performance boost enables the genetic algorithm to search a larger subset of the solution space, which results in more accurate pattern classification. Finally, we demonstrate this method in the context of the 2009 UC San Diego Data Mining Contest, achieving a world-class lift on a data set of 94682 e-commerce transactions.

  8. Linearizing of Low Noise Power Amplifier Using 5.8GHz Double Loop Feedforward Linearization Technique

    Directory of Open Access Journals (Sweden)

    Abdulkareem Mokif Obais

    2017-05-01

    Full Text Available In this paper, a double loop feedforward linearization technique is analyzed and built with a MMIC low noise amplifier “HMC753” as main amplifier and a two-stage class-A power amplifier as error amplifier. The system is operated with 5V DC supply at a center frequency of 5.8GHz and a bandwidth of 500MHz. The proposed technique, increases the linearity of the MMIC amplifier from 18dBm at 1dB compression point to more than 26dBm. In addition, the proposed system is tested with OFDM signal and it reveals good response in maximizing the linearity region and eliminating distortions. The proposed system is designed and simulated onAdvanced Wave Research-Microwave Office (AWR-MWO.

  9. Organization of feed-forward loop motifs reveals architectural principles in natural and engineered networks.

    Science.gov (United States)

    Gorochowski, Thomas E; Grierson, Claire S; di Bernardo, Mario

    2018-03-01

    Network motifs are significantly overrepresented subgraphs that have been proposed as building blocks for natural and engineered networks. Detailed functional analysis has been performed for many types of motif in isolation, but less is known about how motifs work together to perform complex tasks. To address this issue, we measure the aggregation of network motifs via methods that extract precisely how these structures are connected. Applying this approach to a broad spectrum of networked systems and focusing on the widespread feed-forward loop motif, we uncover striking differences in motif organization. The types of connection are often highly constrained, differ between domains, and clearly capture architectural principles. We show how this information can be used to effectively predict functionally important nodes in the metabolic network of Escherichia coli . Our findings have implications for understanding how networked systems are constructed from motif parts and elucidate constraints that guide their evolution.

  10. Mitigation of ground motion effects in linear accelerators via feed-forward control

    Directory of Open Access Journals (Sweden)

    J. Pfingstner

    2014-12-01

    Full Text Available Ground motion is a severe problem for many particle accelerators, since it excites beam oscillations, which decrease the beam quality and create beam-beam offset (at colliders. Orbit feedback systems can only compensate ground motion effects at frequencies significantly smaller than the beam repetition rate. In linear colliders, where the repetition rate is low, additional counter measures have to be put in place. For this reason, a ground motion mitigation method based on feed-forward control is presented in this paper. It has several advantages compared to other techniques (stabilization systems and intratrain feedback systems such as cost reduction and potential performance improvement. An analytical model is presented that allows the derivation of hardware specification and performance estimates for a specific accelerator and ground motion model. At the Accelerator Test Facility (ATF2, ground motion sensors have been installed to verify the feasibility of important parts of the mitigation strategy. In experimental studies, it has been shown that beam excitations due to ground motion can be predicted from ground motion measurements on a pulse-to-pulse basis. Correlations of up to 80% between the estimated and measured orbit jitter have been observed. Additionally, an orbit jitter source was identified and has been removed, which halved the orbit jitter power at ATF2 and shows that the feed-forward scheme is also very useful for the detection of installation issues. We believe that the presented mitigation method has the potential to reduce costs and improve the performance of linear colliders and potentially other linear accelerators.

  11. Arm dominance affects feedforward strategy more than feedback sensitivity during a postural task.

    Science.gov (United States)

    Walker, Elise H E; Perreault, Eric J

    2015-07-01

    Handedness is a feature of human motor control that is still not fully understood. Recent work has demonstrated that the dominant and nondominant arm each excel at different behaviors and has proposed that this behavioral asymmetry arises from lateralization in the cerebral cortex: the dominant side specializes in predictive trajectory control, while the nondominant side is specialized for impedance control. Long-latency stretch reflexes are an automatic mechanism for regulating posture and have been shown to contribute to limb impedance. To determine whether long-latency reflexes also contribute to asymmetric motor behavior in the upper limbs, we investigated the effect of arm dominance on stretch reflexes during a postural task that required varying degrees of impedance control. Our results demonstrated slightly but significantly larger reflex responses in the biarticular muscles of the nondominant arm, as would be consistent with increased impedance control. These differences were attributed solely to higher levels of voluntary background activity in the nondominant biarticular muscles, indicating that feedforward strategies for postural stability may differ between arms. Reflex sensitivity, which was defined as the magnitude of the reflex response for matched levels of background activity, was not significantly different between arms for a broad subject population ranging from 23 to 51 years of age. These results indicate that inter-arm differences in feedforward strategies are more influential during posture than differences in feedback sensitivity, in a broad subject population. Interestingly, restricting our analysis to subjects under 40 years of age revealed a small increase in long-latency reflex sensitivity in the nondominant arm relative to the dominant arm. Though our subject numbers were small for this secondary analysis, it suggests that further studies may be required to assess the influence of reflex lateralization throughout development.

  12. Feedback and feedforward adaptation to visuomotor delay during reaching and slicing movements.

    Science.gov (United States)

    Botzer, Lior; Karniel, Amir

    2013-07-01

    It has been suggested that the brain and in particular the cerebellum and motor cortex adapt to represent the environment during reaching movements under various visuomotor perturbations. It is well known that significant delay is present in neural conductance and processing; however, the possible representation of delay and adaptation to delayed visual feedback has been largely overlooked. Here we investigated the control of reaching movements in human subjects during an imposed visuomotor delay in a virtual reality environment. In the first experiment, when visual feedback was unexpectedly delayed, the hand movement overshot the end-point target, indicating a vision-based feedback control. Over the ensuing trials, movements gradually adapted and became accurate. When the delay was removed unexpectedly, movements systematically undershot the target, demonstrating that adaptation occurred within the vision-based feedback control mechanism. In a second experiment designed to broaden our understanding of the underlying mechanisms, we revealed similar after-effects for rhythmic reversal (out-and-back) movements. We present a computational model accounting for these results based on two adapted forward models, each tuned for a specific modality delay (proprioception or vision), and a third feedforward controller. The computational model, along with the experimental results, refutes delay representation in a pure forward vision-based predictor and suggests that adaptation occurred in the forward vision-based predictor, and concurrently in the state-based feedforward controller. Understanding how the brain compensates for conductance and processing delays is essential for understanding certain impairments concerning these neural delays as well as for the development of brain-machine interfaces. © 2013 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

  13. Hebbian learning in a model with dynamic rate-coded neurons: an alternative to the generative model approach for learning receptive fields from natural scenes.

    Science.gov (United States)

    Hamker, Fred H; Wiltschut, Jan

    2007-09-01

    Most computational models of coding are based on a generative model according to which the feedback signal aims to reconstruct the visual scene as close as possible. We here explore an alternative model of feedback. It is derived from studies of attention and thus, probably more flexible with respect to attentive processing in higher brain areas. According to this model, feedback implements a gain increase of the feedforward signal. We use a dynamic model with presynaptic inhibition and Hebbian learning to simultaneously learn feedforward and feedback weights. The weights converge to localized, oriented, and bandpass filters similar as the ones found in V1. Due to presynaptic inhibition the model predicts the organization of receptive fields within the feedforward pathway, whereas feedback primarily serves to tune early visual processing according to the needs of the task.

  14. Other components

    International Nuclear Information System (INIS)

    Anon.

    1993-01-01

    This chapter includes descriptions of electronic and mechanical components which do not merit a chapter to themselves. Other hardware requires mention because of particularly high tolerance or intolerance of exposure to radiation. A more systematic analysis of radiation responses of structures which are definable by material was given in section 3.8. The components discussed here are field effect transistors, transducers, temperature sensors, magnetic components, superconductors, mechanical sensors, and miscellaneous electronic components

  15. Performance comparison of machine learning algorithms and number of independent components used in fMRI decoding of belief vs. disbelief.

    Science.gov (United States)

    Douglas, P K; Harris, Sam; Yuille, Alan; Cohen, Mark S

    2011-05-15

    Machine learning (ML) has become a popular tool for mining functional neuroimaging data, and there are now hopes of performing such analyses efficiently in real-time. Towards this goal, we compared accuracy of six different ML algorithms applied to neuroimaging data of persons engaged in a bivariate task, asserting their belief or disbelief of a variety of propositional statements. We performed unsupervised dimension reduction and automated feature extraction using independent component (IC) analysis and extracted IC time courses. Optimization of classification hyperparameters across each classifier occurred prior to assessment. Maximum accuracy was achieved at 92% for Random Forest, followed by 91% for AdaBoost, 89% for Naïve Bayes, 87% for a J48 decision tree, 86% for K*, and 84% for support vector machine. For real-time decoding applications, finding a parsimonious subset of diagnostic ICs might be useful. We used a forward search technique to sequentially add ranked ICs to the feature subspace. For the current data set, we determined that approximately six ICs represented a meaningful basis set for classification. We then projected these six IC spatial maps forward onto a later scanning session within subject. We then applied the optimized ML algorithms to these new data instances, and found that classification accuracy results were reproducible. Additionally, we compared our classification method to our previously published general linear model results on this same data set. The highest ranked IC spatial maps show similarity to brain regions associated with contrasts for belief > disbelief, and disbelief < belief. Copyright © 2010 Elsevier Inc. All rights reserved.

  16. Euler principal component analysis

    NARCIS (Netherlands)

    Liwicki, Stephan; Tzimiropoulos, Georgios; Zafeiriou, Stefanos; Pantic, Maja

    Principal Component Analysis (PCA) is perhaps the most prominent learning tool for dimensionality reduction in pattern recognition and computer vision. However, the ℓ 2-norm employed by standard PCA is not robust to outliers. In this paper, we propose a kernel PCA method for fast and robust PCA,

  17. Perceptual learning increases the strength of the earliest signals in visual cortex.

    Science.gov (United States)

    Bao, Min; Yang, Lin; Rios, Cristina; He, Bin; Engel, Stephen A

    2010-11-10

    Training improves performance on most visual tasks. Such perceptual learning can modify how information is read out from, and represented in, later visual areas, but effects on early visual cortex are controversial. In particular, it remains unknown whether learning can reshape neural response properties in early visual areas independent from feedback arising in later cortical areas. Here, we tested whether learning can modify feedforward signals in early visual cortex as measured by the human electroencephalogram. Fourteen subjects were trained for >24 d to detect a diagonal grating pattern in one quadrant of the visual field. Training improved performance, reducing the contrast needed for reliable detection, and also reliably increased the amplitude of the earliest component of the visual evoked potential, the C1. Control orientations and locations showed smaller effects of training. Because the C1 arises rapidly and has a source in early visual cortex, our results suggest that learning can increase early visual area response through local receptive field changes without feedback from later areas.

  18. Electronic components

    CERN Document Server

    Colwell, Morris A

    1976-01-01

    Electronic Components provides a basic grounding in the practical aspects of using and selecting electronics components. The book describes the basic requirements needed to start practical work on electronic equipment, resistors and potentiometers, capacitance, and inductors and transformers. The text discusses semiconductor devices such as diodes, thyristors and triacs, transistors and heat sinks, logic and linear integrated circuits (I.C.s) and electromechanical devices. Common abbreviations applied to components are provided. Constructors and electronics engineers will find the book useful

  19. Limitations of Feedback, Feedforward and IMC Controller for a First Order Non-Linear Process with Dead Time

    Directory of Open Access Journals (Sweden)

    Maruthai Suresh

    2010-10-01

    Full Text Available A nonlinear process, the heat exchanger whose parameters vary with respect to the process variable, is considered. The time constant and gain of the chosen process vary as a function of temperature. The limitations of the conventional feedback controller tuned using Ziegler-Nichols settings for the chosen process are brought out. The servo and regulatory responses through simulation and experimentation for various magnitudes of set-point changes and load changes at various operating points with the controller tuned only at a chosen nominal operating point are obtained and analyzed. Regulatory responses for output load changes are studied. The efficiency of feedforward controller and the effects of modeling error have been brought out. An IMC based system is presented to understand clearly how variations of system parameters affect the performance of the controller. The present work illustrates the effectiveness of Feedforward and IMC controller.

  20. A Robust Multivariable Feedforward/Feedback Controller Design for Integrated Power Control of Boiling Water Reactor Power Plants

    International Nuclear Information System (INIS)

    Shyu, S.-S.; Edwards, Robert M.

    2002-01-01

    In this paper, a methodology for synthesizing a robust multivariable feedforward/feedback control (FF/FBC) strategy is proposed for an integrated control of turbine power, throttle pressure, and reactor water level in a nuclear power plant. In the proposed method, the FBC is synthesized by the robust control approach. The feedforward control, which is generated via nonlinear programming, is added to the robust FBC system to further improve the control performance. The plant uncertainties, including unmodeled dynamics, linearization, and model reduction, are characterized and estimated. The comparisons of simulation responses based on a nonlinear reactor model demonstrate the achievement of the proposed controller with specified performance and endurance under uncertainty. It is also important to note that all input variables are manipulated in an orchestrated manner in response to a single output's setpoint change

  1. Field Testing of Feedforward Collective Pitch Control on the CART2 Using a Nacelle-Based Lidar Scanner

    International Nuclear Information System (INIS)

    Schlipf, David; Haizmann, Florian; Hofsäß, Martin; Cheng, Po Wen; Fleming, Paul; Scholbrock, Andrew; Wright, Alan

    2014-01-01

    This work presents the results from a field test of LIDAR assisted collective pitch control using a scanning LIDAR device installed on the nacelle of a mid-scale research turbine. A nonlinear feedforward controller is extended by an adaptive filter to remove all uncorrelated frequencies of the wind speed measurement to avoid unnecessary control action. Positive effects on the rotor speed regulation as well as on tower, blade and shaft loads have been observed in the case that the previous measured correlation and timing between the wind preview and the turbine reaction are accomplish. The feedforward controller had negative impact, when the LIDAR measurement was disturbed by obstacles in front of the turbine. This work proves, that LIDAR is valuable tool for wind turbine control not only in simulations but also under real conditions. Furthermore, the paper shows that further understanding of the relationship between the wind measurement and the turbine reaction is crucial to improve LIDAR assisted control of wind turbines

  2. On the use of iterative techniques for feedforward control of transverse angle and position jitter in linear particle beam accelerators

    International Nuclear Information System (INIS)

    Barr, D.S.

    1995-01-01

    It is possible to use feedforward predictive control for transverse position and trajectory-angle jitter correction. The control procedure is straightforward, but creation of the predictive filter is not as obvious. The two process tested were the least mean squares (LMS) and Kalman filter methods. The controller parameters calculated offline are downloaded to a real-time analog correction system between macropulses. These techniques worked well for both interpulse (pulse-to-pulse) correction and intrapulse (within a pulse) correction with the Kalman filter method being the clear winner. A simulation based on interpulse data taken at the Stanford Linear Collider showed an improvement factor of almost three in the average rms jitter over standard feedback techniques for the Kalman filter. An improvement factor of over three was found for the Kalman filter on intrapulse data taken at the Los Alamos Meson Physics Facility. The feedforward systems also improved the correction bandwidth. copyright 1995 American Institute of Physics

  3. On the use of iterative techniques for feedforward control of transverse angle and position jitter in linear particle beam accelerators

    International Nuclear Information System (INIS)

    Barr, D.S.

    1994-01-01

    It is possible to use feedforward predictive control for transverse position and trajectory-angle jitter correction. The control procedure is straightforward, but creation of the predictive filter is not as obvious. The two processes tested were the least mean squares (LMS) and Kalman inter methods. The controller parameters calculated offline are downloaded to a real-time analog correction system between macropulses. These techniques worked well for both interpulse (pulse-to-pulse) correction and intrapulse (within a pulse) correction with the Kalman filter method being the clear winner. A simulation based on interpulse data taken at the Stanford Linear Collider showed an improvement factor of almost three in the average rms jitter over standard feedback techniques for the Kalman filter. An improvement factor of over three was found for the Kalman filter on intrapulse data taken at the Los Alamos Meson Physics Facility. The feedforward systems also improved the correction bandwidth

  4. Non-predictor control of a class of feedforward nonlinear systems with unknown time-varying delays

    Science.gov (United States)

    Koo, Min-Sung; Choi, Ho-Lim

    2016-08-01

    This paper generalises the several recent results on the control of feedforward time-delay nonlinear systems. First, in view of system formulation, there are unknown time-varying delays in both states and main control input. Also, the considered nonlinear system has extended feedforward nonlinearities. Second, in view of control solution, our proposed controller is a non-predictor feedback controller whereas smith-predictor type controllers are used in the several existing results. Moreover, our controller does not need any information on the unknown delays except their upper bounds. Thus, our result has certain merits in both system formulation and control solution perspective. The analysis and example are given for clear illustration.

  5. Field Testing of Feedforward Collective Pitch Control on the CART2 Using a Nacelle-Based Lidar Scanner

    Science.gov (United States)

    Schlipf, David; Fleming, Paul; Haizmann, Florian; Scholbrock, Andrew; Hofsäß, Martin; Wright, Alan; Cheng, Po Wen

    2014-12-01

    This work presents the results from a field test of LIDAR assisted collective pitch control using a scanning LIDAR device installed on the nacelle of a mid-scale research turbine. A nonlinear feedforward controller is extended by an adaptive filter to remove all uncorrelated frequencies of the wind speed measurement to avoid unnecessary control action. Positive effects on the rotor speed regulation as well as on tower, blade and shaft loads have been observed in the case that the previous measured correlation and timing between the wind preview and the turbine reaction are accomplish. The feedforward controller had negative impact, when the LIDAR measurement was disturbed by obstacles in front of the turbine. This work proves, that LIDAR is valuable tool for wind turbine control not only in simulations but also under real conditions. Furthermore, the paper shows that further understanding of the relationship between the wind measurement and the turbine reaction is crucial to improve LIDAR assisted control of wind turbines.

  6. An Active Seat Controller with Vehicle Suspension Feedforward and Feedback States: An Experimental Study

    Directory of Open Access Journals (Sweden)

    Abdulaziz Alfadhli

    2018-04-01

    Full Text Available Active seat suspensions can be used to reduce the harmful vertical vibration of a vehicle’s seat by applying an external force using a closed loop controller. Many of the controllers found in the literature are difficult to implement practically, because they are based on using unavailable or difficult and costly measurements. This paper presents both simulation and experimental studies of five novel, simple, and cost-effective control strategies to be used for an active seat suspension in order to improve ride comfort at low frequencies below 20 Hz. These strategies use available and measurable feedforward (preview information states from the vehicle secondary suspension, as well as feedback states from the seat suspension, together with gains optimised to minimise the occupant vibration. The gains were optimised using a genetic algorithm (GA, with a fitness function based on the seat effective amplitude transmissibility (SEAT factor. Constraints on the control force and the seat suspension stroke were also included in the optimisation algorithm. Simulation and laboratory experimental tests were carried out to assess the performance of the proposed controllers according to the ISO 2631-1 standard, in both the frequency and time domains with a range of different road profiles. The experimental tests were performed using a multi-axis simulation table (MAST and a physical active seat suspension configured as a hardware-in-loop (HIL simulation with a virtual linear quarter vehicle model (QvM. The results demonstrate that the proposed controllers substantially attenuate the vertical vibration at the driver’s seat compared with both a passive and a proportional-integral-derivative (PID active seat suspension and thus improve ride comfort together with reducing vibration-linked health risks. Moreover, experimental results show that employing both feedforward information and feedback vehicle body and seat acceleration signals in the controller

  7. Loss of Balance between Striatal Feedforward Inhibition and Corticostriatal Excitation Leads to Tremor.

    Science.gov (United States)

    Oran, Yael; Bar-Gad, Izhar

    2018-02-14

    Fast-spiking interneurons (FSIs) exert powerful inhibitory control over the striatum and are hypothesized to balance the massive excitatory cortical and thalamic input to this structure. We recorded neuronal activity in the dorsolateral striatum and globus pallidus (GP) concurrently with the detailed movement kinematics of freely behaving female rats before and after selective inhibition of FSI activity using IEM-1460 microinjections. The inhibition led to the appearance of episodic rest tremor in the body part that depended on the somatotopic location of the injection within the striatum. The tremor was accompanied by coherent oscillations in the local field potential (LFP). Individual neuron activity patterns became oscillatory and coherent in the tremor frequency. Striatal neurons, but not GP neurons, displayed additional temporal, nonoscillatory correlations. The subsequent reduction in the corticostriatal input following muscimol injection to the corresponding somatotopic location in the primary motor cortex led to disruption of the tremor and a reduction of the LFP oscillations and individual neuron's phase-locked activity. The breakdown of the normal balance of excitation and inhibition in the striatum has been shown previously to be related to different motor abnormalities. Our results further indicate that the balance between excitatory corticostriatal input and feedforward FSI inhibition is sufficient to break down the striatal decorrelation process and generate oscillations resulting in rest tremor typical of multiple basal ganglia disorders. SIGNIFICANCE STATEMENT Fast-spiking interneurons (FSIs) play a key role in normal striatal processing by exerting powerful inhibitory control over the network. FSI malfunctions have been associated with abnormal processing of information within the striatum that leads to multiple movement disorders. Here, we study the changes in neuronal activity and movement kinematics following selective inhibition of these

  8. Neural network feedforward control of a closed-circuit wind tunnel

    Science.gov (United States)

    Sutcliffe, Peter

    Accurate control of wind-tunnel test conditions can be dramatically enhanced using feedforward control architectures which allow operating conditions to be maintained at a desired setpoint through the use of mathematical models as the primary source of prediction. However, as the desired accuracy of the feedforward prediction increases, the model complexity also increases, so that an ever increasing computational load is incurred. This drawback can be avoided by employing a neural network that is trained offline using the output of a high fidelity wind-tunnel mathematical model, so that the neural network can rapidly reproduce the predictions of the model with a greatly reduced computational overhead. A novel neural network database generation method, developed through the use of fractional factorial arrays, was employed such that a neural network can accurately predict wind-tunnel parameters across a wide range of operating conditions whilst trained upon a highly efficient database. The subsequent network was incorporated into a Neural Network Model Predictive Control (NNMPC) framework to allow an optimised output schedule capable of providing accurate control of the wind-tunnel operating parameters. Facilitation of an optimised path through the solution space is achieved through the use of a chaos optimisation algorithm such that a more globally optimum solution is likely to be found with less computational expense than the gradient descent method. The parameters associated with the NNMPC such as the control horizon are determined through the use of a Taguchi methodology enabling the minimum number of experiments to be carried out to determine the optimal combination. The resultant NNMPC scheme was employed upon the Hessert Low Speed Wind Tunnel at the University of Notre Dame to control the test-section temperature such that it follows a pre-determined reference trajectory during changes in the test-section velocity. Experimental testing revealed that the

  9. Learning and Generalisation in Neural Networks with Local Preprocessing

    OpenAIRE

    Kutsia, Merab

    2007-01-01

    We study learning and generalisation ability of a specific two-layer feed-forward neural network and compare its properties to that of a simple perceptron. The input patterns are mapped nonlinearly onto a hidden layer, much larger than the input layer, and this mapping is either fixed or may result from an unsupervised learning process. Such preprocessing of initially uncorrelated random patterns results in the correlated patterns in the hidden layer. The hidden-to-output mapping of the net...

  10. Strategic Management Accounting and Feed-forward Management: with Reference to the Unified Management of Profit Opportunity and Risk

    OpenAIRE

    西村, 明

    2015-01-01

    This paper aims toreexamine strategic management accouning in relation to profit opportunity and risk from the viewpoint of feed-forward management , as few studies to date have discuued the relations between management accounting and the unified management of profit opportunity and risk.Many studies have been conducted that emphasize non-fine information and feedback organizational management in an attept to make traditional management accounting relevant to practical strategic needs. As lon...

  11. Control of a flexible beam actuated by macro-fiber composite patches: I. Modeling and feedforward trajectory control

    International Nuclear Information System (INIS)

    Schröck, Johannes; Meurer, Thomas; Kugi, Andreas

    2011-01-01

    This paper considers a systematic approach for motion planning and feedforward control design for a flexible cantilever actuated by piezoelectric macro-fiber composite (MFC) patches. For accurate feedforward tracking control, special attention has to be paid to the inherent nonlinear hysteresis and creep behavior of these actuators. In order to account for these effects an appropriate compensator is applied which allows us to perform the tracking controller design on the basis of a linear infinite-dimensional model. A detailed analysis of the nonlinear actuator behavior as well as the compensator design and the overall experimental validation is presented in the companion paper (Schröck et al 2011 Smart Mater. Struct. 20 015016). The governing equations of motion of the hysteresis and creep compensated cantilever are determined by means of the extended Hamilton's principle. This allows us to consider the influence of the bonded patch actuators on the mechanical properties of the underlying beam structure in a straightforward manner and results in a model with spatially varying system parameters. For the solution of the motion planning and feedforward control problem a flatness-based methodology is proposed. In a first step, the infinite-dimensional system of the MFC-actuated flexible cantilever is approximated by a finite-dimensional model, where all system variables, i.e. the states, input and output, can be parameterized in terms of a so-called flat output. In a second step, it is shown by numerical simulations that these parameterizations converge with increasing system order of the finite-dimensional model such that the feedforward control input can be directly calculated in order to realize prescribed output trajectories

  12. PREDICTIVE CONTROL OF A BATCH POLYMERIZATION SYSTEM USING A FEEDFORWARD NEURAL NETWORK WITH ONLINE ADAPTATION BY GENETIC ALGORITHM

    OpenAIRE

    Cancelier, A.; Claumann, C. A.; Bolzan, A.; Machado, R. A. F.

    2016-01-01

    Abstract This study used a predictive controller based on an empirical nonlinear model comprising a three-layer feedforward neural network for temperature control of the suspension polymerization process. In addition to the offline training technique, an algorithm was also analyzed for online adaptation of its parameters. For the offline training, the network was statically trained and the genetic algorithm technique was used in combination with the least squares method. For online training, ...

  13. Feedforward and feedback projections of caudal belt and parabelt areas of auditory cortex: refining the hierarchical model

    Directory of Open Access Journals (Sweden)

    Troy A Hackett

    2014-04-01

    Full Text Available Our working model of the primate auditory cortex recognizes three major regions (core, belt, parabelt, subdivided into thirteen areas. The connections between areas are topographically ordered in a manner consistent with information flow along two major anatomical axes: core-belt-parabelt and caudal-rostral. Remarkably, most of the connections supporting this model were revealed using retrograde tracing techniques. Little is known about laminar circuitry, as anterograde tracing of axon terminations has rarely been used. The purpose of the present study was to examine the laminar projections of three areas of auditory cortex, pursuant to analysis of all areas. The selected areas were: middle lateral belt (ML; caudomedial belt (CM; and caudal parabelt (CPB. Injections of anterograde tracers yielded data consistent with major features of our model, and also new findings that compel modifications. Results supporting the model were: 1 feedforward projection from ML and CM terminated in CPB; 2 feedforward projections from ML and CPB terminated in rostral areas of the belt and parabelt; and 3 feedback projections typified inputs to the core region from belt and parabelt. At odds with the model was the convergence of feedforward inputs into rostral medial belt from ML and CPB. This was unexpected since CPB is at a higher stage of the processing hierarchy, with mainly feedback projections to all other belt areas. Lastly, extending the model, feedforward projections from CM, ML, and CPB overlapped in the temporal parietal occipital area (TPO in the superior temporal sulcus, indicating significant auditory influence on sensory processing in this region. The combined results refine our working model and highlight the need to complete studies of the laminar inputs to all areas of auditory cortex. Their documentation is essential for developing informed hypotheses about the neurophysiological influences of inputs to each layer and area.

  14. A single hidden layer feedforward network with only one neuron in the hidden layer can approximate any univariate function

    OpenAIRE

    Guliyev , Namig; Ismailov , Vugar

    2016-01-01

    The possibility of approximating a continuous function on a compact subset of the real line by a feedforward single hidden layer neural network with a sigmoidal activation function has been studied in many papers. Such networks can approximate an arbitrary continuous function provided that an unlimited number of neurons in a hidden layer is permitted. In this paper, we consider constructive approximation on any finite interval of $\\mathbb{R}$ by neural networks with only one neuron in the hid...

  15. Students as Learning Designers

    DEFF Research Database (Denmark)

    Levinsen, Karin; Sørensen, Birgitte Holm

    2013-01-01

    This paper focuses on students in the youngest classes at primary school as learning designers of ICT-integrated productions. It is based on the project Netbook 1:1 (2009-2012) funded by the municipality of Gentofte and Microsoft Denmark. The paper presents a model for designing ICT-integrated st......This paper focuses on students in the youngest classes at primary school as learning designers of ICT-integrated productions. It is based on the project Netbook 1:1 (2009-2012) funded by the municipality of Gentofte and Microsoft Denmark. The paper presents a model for designing ICT......-integrated student productions which was developed during the project in relation to different subjects. Ownership, iteration and feedforward are the central concepts in this model. Two exemplary cases are presented illustrating the students’ and teachers’ roles as learning designers in relation to the model...

  16. Independent component analysis: recent advances

    OpenAIRE

    Hyv?rinen, Aapo

    2013-01-01

    Independent component analysis is a probabilistic method for learning a linear transform of a random vector. The goal is to find components that are maximally independent and non-Gaussian (non-normal). Its fundamental difference to classical multi-variate statistical methods is in the assumption of non-Gaussianity, which enables the identification of original, underlying components, in contrast to classical methods. The basic theory of independent component analysis was mainly developed in th...

  17. A new on-chip all-digital three-phase full-bridge dc/ac power inverter with feedforward and frequency control techniques.

    Science.gov (United States)

    Chen, Jiann-Jong; Kung, Che-Min

    2010-09-01

    The communication speed between components is far from satisfactory. To achieve high speed, simple control system configuration, and low cost, a new on-chip all-digital three-phase dc/ac power inverter using feedforward and frequency control techniques is proposed. The controller of the proposed power inverter, called the shift register, consists of six-stage D-latch flip-flops with a goal of achieving low-power consumption and area efficiency. Variable frequency is achieved by controlling the clocks of the shift register. One advantage regarding the data signal (D) and the common clock (CK) is that, regardless of the phase difference between the two, all of the D-latch flip-flops are capable of delaying data by one CK period. To ensure stability, the frequency of CK must be six times higher than that of D. The operation frequency of the proposed power inverter ranges from 10 Hz to 2 MHz, and the maximum output loading current is 0.8 A. The prototype of the proposed circuit has been fabricated with TSMC 0.35 μm 2P4M CMOS processes. The total chip area is 2.333 x 1.698 mm2. The three-phase dc/ac power inverter is applicable in uninterrupted power supplies, cold cathode fluorescent lamps, and motors, because of its ability to convert the dc supply voltage into the three-phase ac power sources.

  18. Wind tunnel tests with combined pitch and free-floating flap control: data-driven iterative feedforward controller tuning

    Directory of Open Access Journals (Sweden)

    S. T. Navalkar

    2016-10-01

    Full Text Available Wind turbine load alleviation has traditionally been addressed in the literature using either full-span pitch control, which has limited bandwidth, or trailing-edge flap control, which typically shows low control authority due to actuation constraints. This paper combines both methods and demonstrates the feasibility and advantages of such a combined control strategy on a scaled prototype in a series of wind tunnel tests. The pitchable blades of the test turbine are instrumented with free-floating flaps close to the tip, designed such that they aerodynamically magnify the low stroke of high-bandwidth actuators. The additional degree of freedom leads to aeroelastic coupling with the blade flexible modes. The inertia of the flaps was tuned such that instability occurs just beyond the operational envelope of the wind turbine; the system can however be stabilised using collocated closed-loop control. A feedforward controller is shown to be capable of significant reduction of the deterministic loads of the turbine. Iterative feedforward tuning, in combination with a stabilising feedback controller, is used to optimise the controller online in an automated manner, to maximise load reduction. Since the system is non-linear, the controller gains vary with wind speed; this paper also shows that iterative feedforward tuning is capable of generating the optimal gain schedule online.

  19. Integrated hybrid vibration isolator with feedforward compensation for fast high-precision positioning X/Y tables

    International Nuclear Information System (INIS)

    Yan, T H; Li, Q; Xu, C; Pu, H Y; Chen, X D

    2010-01-01

    The design, realization and control technologies of a high-performance hybrid microvibration isolator for ultra-high-precision high-speed moving X/Y tables are presented in this paper—the novel isolator with integrated passive–active high level of damping. The passive damping was implemented using air-springs in both vertical and horizontal directions, with parallel linear motors in two directions to realize the active damping and the positioning functions. It is an actual hybrid isolation system because its air-spring can also be controlled through the pneumatic loop. The isolation servo system also has fast positioning capability via the feedforward compensation for the moving tables. Compared with the conventional filtered reference type control algorithms that rely on the assumption for the adaptive filter and the controlled system, in which the disturbance is estimated from the residual signal, the feedforward compensation here shows high effectiveness of vibration isolation and high-precision positioning performance for its platform. The performance of feedforward compensation has been enhanced via an efficient state estimation adaptive algorithm, the fast Kalman filter. Finally, experimental demonstration has been shown for the prototype system and the results have verified the effectiveness of the proposed isolator system design and the adaptive control algorithm for substantially enhanced damping of the platform system with the moving X/Y tables

  20. Control of CA3 output by feedforward inhibition despite developmental changes in the excitation-inhibition balance.

    Science.gov (United States)

    Torborg, Christine L; Nakashiba, Toshiaki; Tonegawa, Susumu; McBain, Chris J

    2010-11-17

    In somatosensory cortex, the relative balance of excitation and inhibition determines how effectively feedforward inhibition enforces the temporal fidelity of action potentials. Within the CA3 region of the hippocampus, glutamatergic mossy fiber (MF) synapses onto CA3 pyramidal cells (PCs) provide strong monosynaptic excitation that exhibit prominent facilitation during repetitive activity. We demonstrate in the juvenile CA3 that MF-driven polysynaptic IPSCs facilitate to maintain a fixed EPSC-IPSC ratio during short-term plasticity. In contrast, in young adult mice this MF-driven polysynaptic inhibitory input can facilitate or depress in response to short trains of activity. Transgenic mice lacking the feedback inhibitory loop continue to exhibit both facilitating and depressing polysynaptic IPSCs, indicating that this robust inhibition is not caused by the secondary engagement of feedback inhibition. Surprisingly, eliminating MF-driven inhibition onto CA3 pyramidal cells by blockade of GABA(A) receptors did not lead to a loss of temporal precision of the first action potential observed after a stimulus but triggered in many cases a long excitatory plateau potential capable of triggering repetitive action potential firing. These observations indicate that, unlike other regions of the brain, the temporal precision of single MF-driven action potentials is dictated primarily by the kinetics of MF EPSPs, not feedforward inhibition. Instead, feedforward inhibition provides a robust regulation of CA3 PC excitability across development to prevent excessive depolarization by the monosynaptic EPSP and multiple action potential firings.

  1. An Evaluation of "Success and Dyslexia"--A Multi Component School-Based Coping Program for Primary School Students with Learning Disabilities: Is It Feasible?

    Science.gov (United States)

    Firth, Nola Virginia; Frydenberg, Erica; Bond, Lyndal

    2012-01-01

    A learning disabilities coping program was implemented in the final year of two primary schools within the context of a whole class coping program and whole school learning disabilities professional development. Using data collected over three years from school surveys, reports, interviews, school documents and a field diary, this paper reports on…

  2. Oncogenic MYC Activates a Feedforward Regulatory Loop Promoting Essential Amino Acid Metabolism and Tumorigenesis.

    Science.gov (United States)

    Yue, Ming; Jiang, Jue; Gao, Peng; Liu, Hudan; Qing, Guoliang

    2017-12-26

    Most tumor cells exhibit obligatory demands for essential amino acids (EAAs), but the regulatory mechanisms whereby tumor cells take up EAAs and EAAs promote malignant transformation remain to be determined. Here, we show that oncogenic MYC, solute carrier family (SLC) 7 member 5 (SLC7A5), and SLC43A1 constitute a feedforward activation loop to promote EAA transport and tumorigenesis. MYC selectively activates Slc7a5 and Slc43a1 transcription through direct binding to specific E box elements within both genes, enabling effective EAA import. Elevated EAAs, in turn, stimulate Myc mRNA translation, in part through attenuation of the GCN2-eIF2α-ATF4 amino acid stress response pathway, leading to MYC-dependent transcriptional amplification. SLC7A5/SLC43A1 depletion inhibits MYC expression, metabolic reprogramming, and tumor cell growth in vitro and in vivo. These findings thus reveal a MYC-SLC7A5/SLC43A1 signaling circuit that underlies EAA metabolism, MYC deregulation, and tumorigenesis. Copyright © 2017 The Author(s). Published by Elsevier Inc. All rights reserved.

  3. Demonstration of feed-forward control for linear optics quantum computation

    International Nuclear Information System (INIS)

    Pittman, T.B.; Jacobs, B.C.; Franson, J.D.

    2002-01-01

    One of the main requirements in linear optics quantum computing is the ability to perform single-qubit operations that are controlled by classical information fed forward from the output of single-photon detectors. These operations correspond to predetermined combinations of phase corrections and bit flips that are applied to the postselected output modes of nondeterministic quantum logic devices. Corrections of this kind are required in order to obtain the correct logical output for certain detection events, and their use can increase the overall success probability of the devices. In this paper, we report on the experimental demonstration of the use of this type of feed-forward system to increase the probability of success of a simple nondeterministic quantum logic operation from approximately (1/4) to (1/2). This logic operation involves the use of one target qubit and one ancilla qubit which, in this experiment, are derived from a parametric down-conversion photon pair. Classical information describing the detection of the ancilla photon is fed forward in real time and used to alter the quantum state of the output photon. A fiber-optic delay line is used to store the output photon until a polarization-dependent phase shift can be applied using a high-speed Pockels cell

  4. Development of a Beam-based Phase Feedforward Demonstration at the CLIC Test Facility (CTF3)

    CERN Document Server

    AUTHOR|(CDS)2083344; Christian, Glenn

    The Compact Linear Collider (CLIC) is a proposal for a future linear electron--positron collider that could achieve collision energies of up to 3~TeV. In the CLIC concept the main high energy beam is accelerated using RF power extracted from a high intensity drive beam, achieving an accelerating gradient of 100~MV/m. This scheme places strict tolerances on the drive beam phase stability, which must be better than $0.2^\\circ$ at 12~GHz. To achieve the required phase stability CLIC proposes a high bandwidth (${>}17.5$~MHz), low latency drive beam ``phase feedforward'' (PFF) system. In this system electromagnetic kickers, powered by 500~kW amplifiers, are installed in a chicane and used to correct the phase by deflecting the beam on to longer or shorter trajectories. A prototype PFF system has been installed at the CLIC Test Facility, CTF3; the design, operation and commissioning of which is the focus of this work. Two kickers have been installed in the pre-existing chicane in the TL2 transfer line at CTF3 for t...

  5. Hippocampus-driven feed-forward inhibition of the prefrontal cortex mediates relapse of extinguished fear.

    Science.gov (United States)

    Marek, Roger; Jin, Jingji; Goode, Travis D; Giustino, Thomas F; Wang, Qian; Acca, Gillian M; Holehonnur, Roopashri; Ploski, Jonathan E; Fitzgerald, Paul J; Lynagh, Timothy; Lynch, Joseph W; Maren, Stephen; Sah, Pankaj

    2018-03-01

    The medial prefrontal cortex (mPFC) has been implicated in the extinction of emotional memories, including conditioned fear. We found that ventral hippocampal (vHPC) projections to the infralimbic (IL) cortex recruited parvalbumin-expressing interneurons to counter the expression of extinguished fear and promote fear relapse. Whole-cell recordings ex vivo revealed that optogenetic activation of vHPC input to amygdala-projecting pyramidal neurons in the IL was dominated by feed-forward inhibition. Selectively silencing parvalbumin-expressing, but not somatostatin-expressing, interneurons in the IL eliminated vHPC-mediated inhibition. In behaving rats, pharmacogenetic activation of vHPC→IL projections impaired extinction recall, whereas silencing IL projectors diminished fear renewal. Intra-IL infusion of GABA receptor agonists or antagonists, respectively, reproduced these effects. Together, our findings describe a previously unknown circuit mechanism for the contextual control of fear, and indicate that vHPC-mediated inhibition of IL is an essential neural substrate for fear relapse.

  6. Periodic spring–mass running over uneven terrain through feedforward control of landing conditions

    International Nuclear Information System (INIS)

    III, Luther R Palmer; Eaton, Caitrin E

    2014-01-01

    This work pursues a feedforward control algorithm for high-speed legged locomotion over uneven terrain. Being able to rapidly negotiate uneven terrain without visual or a priori information about the terrain will allow legged systems to be used in time-critical applications and alongside fast-moving humans or vehicles. The algorithm is shown here implemented on a spring-loaded inverted pendulum model in simulation, and can be configured to approach fixed running height over uneven terrain or self-stable terrain following. Offline search identifies unique landing conditions that achieve a desired apex height with a constant stride period over varying ground levels. Because the time between the apex and touchdown events is directly related to ground height, the landing conditions can be computed in real time as continuous functions of this falling time. Enforcing a constant stride period reduces the need for inertial sensing of the apex event, which is nontrivial for physical systems, and allows for clocked feedfoward control of the swing leg. (paper)

  7. Dead beat filling and feedforward rf control for the spallation neutron source SNQ

    International Nuclear Information System (INIS)

    Schulze, D.

    1982-01-01

    For the 1.1 GeV-100 mA Spallation Neutron Source SNQ operation costs and beam losses ask for the possible potential of rf control improvements. Two novel methods are investigated. First, in order to increase the overall rf efficiency, the cavity field is built up as fast as possible in the open loop state of feedback control and in detuned position of the cavity in such a manner that the cavity with beam is matched to the generator. It is shown that this requires the simulataneous application of a generator amplitude and a generator phase step. Secondly, a feedforward control system is proposed, which reduces the amplitude and phase control error caused by an arbitrary beam transient into the limits of +-0.1% and +-0.1 0 and maintains these error limits also in the presence of parameter drift. This is done by an adaptive parameter adjustment procedure using a digital model of the control system. The system structure and a promising digital simulation are discussed

  8. Load speed regulation in compliant mechanical transmission systems using feedback and feedforward control actions.

    Science.gov (United States)

    Raul, P R; Dwivedula, R V; Pagilla, P R

    2016-07-01

    The problem of controlling the load speed of a mechanical transmission system consisting of a belt-pulley and gear-pair is considered. The system is modeled as two inertia (motor and load) connected by a compliant transmission. If the transmission is assumed to be rigid, then using either the motor or load speed feedback provides the same result. However, with transmission compliance, due to belts or long shafts, the stability characteristics and performance of the closed-loop system are quite different when either motor or load speed feedback is employed. We investigate motor and load speed feedback schemes by utilizing the singular perturbation method. We propose and discuss a control scheme that utilizes both motor and load speed feedback, and design an adaptive feedforward action to reject load torque disturbances. The control algorithms are implemented on an experimental platform that is typically used in roll-to-roll manufacturing and results are shown and discussed. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

  9. Rate of Torque Development and Feedforward Control of the Hip and Knee Extensors: Gender Differences.

    Science.gov (United States)

    Stearns-Reider, Kristen M; Powers, Christopher M

    2017-10-06

    The purpose of this study was to determine whether women demonstrate decreased rate of torque development (RTD) of the hip and knee extensors and altered onset timing of the vastus lateralis and gluteus maximus during a drop-jump task when compared with men. On average, women demonstrated significantly lower normalized RTD of the hip extensors (women: 11.6 ± 1.3 MVT.s -1 , men: 13.1 ± 0.9 MVT.s -1 ; p ≤ .01); however, there was no significant difference in knee extensor RTD. Women also demonstrated significantly earlier activation of their vastus lateralis (women: 206.0 ± 130.6 ms, men: 80.9 ± 69.6 ms; p ≤ .01) and gluteus maximus (women: 85.7 ± 58.6 ms, men: 54.5 ± 35.4 ms; p = .02). In both men and women, there was a significant negative correlation between the hip extensor RTD and the vastus lateralis electromyographic onset time (men: r = -.386, p = .046; women: r = -.531, p = .008). The study findings suggest that women may utilize a feedforward control strategy in which they activate their knee extensors earlier than men to compensate for deficits in hip extensor RTD. The impaired capacity to rapidly stabilize the hip and knee joints during dynamic maneuvers may contribute to the increased risk of anterior cruciate ligament injury observed in women.

  10. Spatial Multiplexing of Atom-Photon Entanglement Sources using Feedforward Control and Switching Networks.

    Science.gov (United States)

    Tian, Long; Xu, Zhongxiao; Chen, Lirong; Ge, Wei; Yuan, Haoxiang; Wen, Yafei; Wang, Shengzhi; Li, Shujing; Wang, Hai

    2017-09-29

    The light-matter quantum interface that can create quantum correlations or entanglement between a photon and one atomic collective excitation is a fundamental building block for a quantum repeater. The intrinsic limit is that the probability of preparing such nonclassical atom-photon correlations has to be kept low in order to suppress multiexcitation. To enhance this probability without introducing multiexcitation errors, a promising scheme is to apply multimode memories to the interface. Significant progress has been made in temporal, spectral, and spatial multiplexing memories, but the enhanced probability for generating the entangled atom-photon pair has not been experimentally realized. Here, by using six spin-wave-photon entanglement sources, a switching network, and feedforward control, we build a multiplexed light-matter interface and then demonstrate a ∼sixfold (∼fourfold) probability increase in generating entangled atom-photon (photon-photon) pairs. The measured compositive Bell parameter for the multiplexed interface is 2.49±0.03 combined with a memory lifetime of up to ∼51  μs.

  11. Periodic spring-mass running over uneven terrain through feedforward control of landing conditions.

    Science.gov (United States)

    Palmer, Luther R; Eaton, Caitrin E

    2014-09-01

    This work pursues a feedforward control algorithm for high-speed legged locomotion over uneven terrain. Being able to rapidly negotiate uneven terrain without visual or a priori information about the terrain will allow legged systems to be used in time-critical applications and alongside fast-moving humans or vehicles. The algorithm is shown here implemented on a spring-loaded inverted pendulum model in simulation, and can be configured to approach fixed running height over uneven terrain or self-stable terrain following. Offline search identifies unique landing conditions that achieve a desired apex height with a constant stride period over varying ground levels. Because the time between the apex and touchdown events is directly related to ground height, the landing conditions can be computed in real time as continuous functions of this falling time. Enforcing a constant stride period reduces the need for inertial sensing of the apex event, which is nontrivial for physical systems, and allows for clocked feedfoward control of the swing leg.

  12. Feedforward hysteresis compensation in trajectory control of piezoelectrically-driven nanostagers

    Science.gov (United States)

    Bashash, Saeid; Jalili, Nader

    2006-03-01

    Complex structural nonlinearities of piezoelectric materials drastically degrade their performance in variety of micro- and nano-positioning applications. From the precision positioning and control perspective, the multi-path time-history dependent hysteresis phenomenon is the most concerned nonlinearity in piezoelectric actuators to be analyzed. To realize the underlying physics of this phenomenon and to develop an efficient compensation strategy, the intelligent properties of hysteresis with the effects of non-local memories are discussed. Through performing a set of experiments on a piezoelectrically-driven nanostager with high resolution capacitive position sensor, it is shown that for the precise prediction of hysteresis path, certain memory units are required to store the previous hysteresis trajectory data. Based on the experimental observations, a constitutive memory-based mathematical modeling framework is developed and trained for the precise prediction of hysteresis path for arbitrarily assigned input profiles. Using the inverse hysteresis model, a feedforward control strategy is then developed and implemented on the nanostager to compensate for the system everpresent nonlinearity. Experimental results demonstrate that the controller remarkably eliminates the nonlinear effect if memory units are sufficiently chosen for the inverse model.

  13. Feedforward inhibitory control of sensory information in higher-order thalamic nuclei.

    Science.gov (United States)

    Lavallée, Philippe; Urbain, Nadia; Dufresne, Caroline; Bokor, Hajnalka; Acsády, László; Deschênes, Martin

    2005-08-17

    Sensory stimuli evoke strong responses in thalamic relay cells, which ensure a faithful relay of information to the neocortex. However, relay cells of the posterior thalamic nuclear group in rodents, despite receiving significant trigeminal input, respond poorly to vibrissa deflection. Here we show that sensory transmission in this nucleus is impeded by fast feedforward inhibition mediated by GABAergic neurons of the zona incerta. Intracellular recordings of posterior group neurons revealed that the first synaptic event after whisker deflection is a prominent inhibition. Whisker-evoked EPSPs with fast rise time and longer onset latency are unveiled only after lesioning the zona incerta. Excitation survives barrel cortex lesion, demonstrating its peripheral origin. Electron microscopic data confirm that trigeminal axons make large synaptic terminals on the proximal dendrites of posterior group cells and on the somata of incertal neurons. Thus, the connectivity of the system allows an unusual situation in which inhibition precedes ascending excitation resulting in efficient shunting of the responses. The dominance of inhibition over excitation strongly suggests that the paralemniscal pathway is not designed to relay inputs triggered by passive whisker deflection. Instead, we propose that this pathway operates through disinhibition, and that the posterior group forwards to the cerebral cortex sensory information that is contingent on motor instructions.

  14. Active vibration control for piezoelectricity cantilever beam: an adaptive feedforward control method

    Science.gov (United States)

    Zhu, Qiao; Yue, Jun-Zhou; Liu, Wei-Qun; Wang, Xu-Dong; Chen, Jun; Hu, Guang-Di

    2017-04-01

    This work is focused on the active vibration control of piezoelectric cantilever beam, where an adaptive feedforward controller (AFC) is utilized to reject the vibration with unknown multiple frequencies. First, the experiment setup and its mathematical model are introduced. Due to that the channel between the disturbance and the vibration output is unknown in practice, a concept of equivalent input disturbance (EID) is employed to put an equivalent disturbance into the input channel. In this situation, the vibration control can be achieved by setting the control input be the identified EID. Then, for the EID with known multiple frequencies, the AFC is introduced to perfectly reject the vibration but is sensitive to the frequencies. In order to accurately identify the unknown frequencies of EID in presence of the random disturbances and un-modeled nonlinear dynamics, the time-frequency-analysis (TFA) method is employed to precisely identify the unknown frequencies. Consequently, a TFA-based AFC algorithm is proposed to the active vibration control with unknown frequencies. Finally, four cases are given to illustrate the efficiency of the proposed TFA-based AFC algorithm by experiment.

  15. Dynamic Feedforward Control of a Diesel Engine Based on Optimal Transient Compensation Maps

    Directory of Open Access Journals (Sweden)

    Giorgio Mancini

    2014-08-01

    Full Text Available To satisfy the increasingly stringent emission regulations and a demand for an ever lower fuel consumption, diesel engines have become complex systems with many interacting actuators. As a consequence, these requirements are pushing control and calibration to their limits. The calibration procedure nowadays is still based mainly on engineering experience, which results in a highly iterative process to derive a complete engine calibration. Moreover, automatic tools are available only for stationary operation, to obtain control maps that are optimal with respect to some predefined objective function. Therefore, the exploitation of any leftover potential during transient operation is crucial. This paper proposes an approach to derive a transient feedforward (FF control system in an automated way. It relies on optimal control theory to solve a dynamic optimization problem for fast transients. A partially physics-based model is thereby used to replace the engine. From the optimal solutions, the relevant information is extracted and stored in maps spanned by the engine speed and the torque gradient. These maps complement the static control maps by accounting for the dynamic behavior of the engine. The procedure is implemented on a real engine and experimental results are presented along with the development of the methodology.

  16. Reduced transposed flicker noise in microwave oscillators using gaas-based feedforward amplifiers.

    Science.gov (United States)

    Everard, Jeremy K A; Broomfield, Carl D

    2007-06-01

    Transposed flicker noise reduction and removal is demonstrated in 7.6 GHz microwave oscillators for offsets greater than 10 kHz. This is achieved by using a GaAs-based feedforward power amplifier as the oscillation-sustaining stage and incorporating a limiter and resonator elsewhere in the loop. 20 dB noise suppression is demonstrated at 12.5 kHz offset when the error correcting amplifier is switched on. Three oscillator pairs have been built. A transmission line feedback oscillator with a Qo of 180 and two sapphire-based, dielectric resonator oscillators (DROs) with a Qo of 44,500. The difference between the two DROs is a change in the limiter threshold power level of 10 dB. The phase noise rolls-off at (1/f)(2) for offsets greater than 10 kHz for the transmission line oscillator and is set by the thermal noise to within 0-1 dB of the theoretical minimum. The noise performance of the DROs is within 6-12 dB of the theory. Possible reasons for this discrepancy are presented.

  17. Mitigating IPMC back relaxation through feedforward and feedback control of patterned electrodes

    International Nuclear Information System (INIS)

    Fleming, Maxwell J; Leang, Kam K; Kim, Kwang J

    2012-01-01

    With low driving voltage ( < 5 V) and the ability to be operated in aqueous environments, ionic polymer–metal composite (IPMC) materials are quickly gaining attention for use in many applications including soft bio-inspired actuators and sensors. There are, however, drawbacks to IPMC actuators, including the ‘back relaxation’ effect. Specifically, when subjected to an excessively slow input, the IPMC actuator will slowly relax back toward its original position. There is debate over the physical mechanism of back relaxation, although one prevalent theory describes an initial current, caused by the electrostatic forces of the charging electrodes, which drives water molecules across the ion exchange membrane and deforms the IPMC. Once the electrodes are fully charged, however, the dominant element of the motion is the osmotic pressure, driving the water molecules back to equilibrium, thus causing back relaxation. A new method to mitigate back relaxation is proposed, taking advantage of controlled activation of patterned (sectored) electrodes on the IPMC. By actuating sectors in opposing directions, back relaxation can be effectively canceled out. An integrated feedforward and feedback controller is employed based on this concept, and is shown to minimize back relaxation, while reducing the input voltage required, as compared to the case of the non-sectored IPMC. Experimental results show nearly an order of magnitude reduction in the tracking error compared to the uncompensated case, and that the IPMC’s position can be maintained over a period of 60 and 1200 s with minimal evidence of back relaxation. (paper)

  18. Multiple Model Predictive Hybrid Feedforward Control of Fuel Cell Power Generation System

    Directory of Open Access Journals (Sweden)

    Long Wu

    2018-02-01

    Full Text Available Solid oxide fuel cell (SOFC is widely considered as an alternative solution among the family of the sustainable distributed generation. Its load flexibility enables it adjusting the power output to meet the requirements from power grid balance. Although promising, its control is challenging when faced with load changes, during which the output voltage is required to be maintained as constant and fuel utilization rate kept within a safe range. Moreover, it makes the control even more intractable because of the multivariable coupling and strong nonlinearity within the wide-range operating conditions. To this end, this paper developed a multiple model predictive control strategy for reliable SOFC operation. The resistance load is regarded as a measurable disturbance, which is an input to the model predictive control as feedforward compensation. The coupling is accommodated by the receding horizon optimization. The nonlinearity is mitigated by the multiple linear models, the weighted sum of which serves as the final control execution. The merits of the proposed control structure are demonstrated by the simulation results.

  19. Anatomy of hierarchy: Feedforward and feedback pathways in macaque visual cortex

    Science.gov (United States)

    Markov, Nikola T; Vezoli, Julien; Chameau, Pascal; Falchier, Arnaud; Quilodran, René; Huissoud, Cyril; Lamy, Camille; Misery, Pierre; Giroud, Pascale; Ullman, Shimon; Barone, Pascal; Dehay, Colette; Knoblauch, Kenneth; Kennedy, Henry

    2013-01-01

    The laminar location of the cell bodies and terminals of interareal connections determines the hierarchical structural organization of the cortex and has been intensively studied. However, we still have only a rudimentary understanding of the connectional principles of feedforward (FF) and feedback (FB) pathways. Quantitative analysis of retrograde tracers was used to extend the notion that the laminar distribution of neurons interconnecting visual areas provides an index of hierarchical distance (percentage of supragranular labeled neurons [SLN]). We show that: 1) SLN values constrain models of cortical hierarchy, revealing previously unsuspected areal relations; 2) SLN reflects the operation of a combinatorial distance rule acting differentially on sets of connections between areas; 3) Supragranular layers contain highly segregated bottom-up and top-down streams, both of which exhibit point-to-point connectivity. This contrasts with the infragranular layers, which contain diffuse bottom-up and top-down streams; 4) Cell filling of the parent neurons of FF and FB pathways provides further evidence of compartmentalization; 5) FF pathways have higher weights, cross fewer hierarchical levels, and are less numerous than FB pathways. Taken together, the present results suggest that cortical hierarchies are built from supra- and infragranular counterstreams. This compartmentalized dual counterstream organization allows point-to-point connectivity in both bottom-up and top-down directions. PMID:23983048

  20. Interpretation of correlated neural variability from models of feed-forward and recurrent circuits

    Science.gov (United States)

    2018-01-01

    Neural populations respond to the repeated presentations of a sensory stimulus with correlated variability. These correlations have been studied in detail, with respect to their mechanistic origin, as well as their influence on stimulus discrimination and on the performance of population codes. A number of theoretical studies have endeavored to link network architecture to the nature of the correlations in neural activity. Here, we contribute to this effort: in models of circuits of stochastic neurons, we elucidate the implications of various network architectures—recurrent connections, shared feed-forward projections, and shared gain fluctuations—on the stimulus dependence in correlations. Specifically, we derive mathematical relations that specify the dependence of population-averaged covariances on firing rates, for different network architectures. In turn, these relations can be used to analyze data on population activity. We examine recordings from neural populations in mouse auditory cortex. We find that a recurrent network model with random effective connections captures the observed statistics. Furthermore, using our circuit model, we investigate the relation between network parameters, correlations, and how well different stimuli can be discriminated from one another based on the population activity. As such, our approach allows us to relate properties of the neural circuit to information processing. PMID:29408930

  1. Limits to the development of feed-forward structures in large recurrent neuronal networks

    Directory of Open Access Journals (Sweden)

    Susanne Kunkel

    2011-02-01

    Full Text Available Spike-timing dependent plasticity (STDP has traditionally been of great interest to theoreticians, as it seems to provide an answer to the question of how the brain can develop functional structure in response to repeated stimuli. However, despite this high level of interest, convincing demonstrations of this capacity in large, initially random networks have not been forthcoming. Such demonstrations as there are typically rely on constraining the problem artificially. Techniques include employing additional pruning mechanisms or STDP rules that enhance symmetry breaking, simulating networks with low connectivity that magnify competition between synapses, or combinations of the above. In this paper we first review modeling choices that carry particularly high risks of producing non-generalizable results in the context of STDP in recurrent networks. We then develop a theory for the development of feed-forward structure in random networks and conclude that an unstable fixed point in the dynamics prevents the stable propagation of structure in recurrent networks with weight-dependent STDP. We demonstrate that the key predictions of the theory hold in large-scale simulations. The theory provides insight into the reasons why such development does not take place in unconstrained systems and enables us to identify candidate biologically motivated adaptations to the balanced random network model that might enable it.

  2. Interpretation of correlated neural variability from models of feed-forward and recurrent circuits.

    Directory of Open Access Journals (Sweden)

    Volker Pernice

    2018-02-01

    Full Text Available Neural populations respond to the repeated presentations of a sensory stimulus with correlated variability. These correlations have been studied in detail, with respect to their mechanistic origin, as well as their influence on stimulus discrimination and on the performance of population codes. A number of theoretical studies have endeavored to link network architecture to the nature of the correlations in neural activity. Here, we contribute to this effort: in models of circuits of stochastic neurons, we elucidate the implications of various network architectures-recurrent connections, shared feed-forward projections, and shared gain fluctuations-on the stimulus dependence in correlations. Specifically, we derive mathematical relations that specify the dependence of population-averaged covariances on firing rates, for different network architectures. In turn, these relations can be used to analyze data on population activity. We examine recordings from neural populations in mouse auditory cortex. We find that a recurrent network model with random effective connections captures the observed statistics. Furthermore, using our circuit model, we investigate the relation between network parameters, correlations, and how well different stimuli can be discriminated from one another based on the population activity. As such, our approach allows us to relate properties of the neural circuit to information processing.

  3. Feedback-linearization and feedback-feedforward decentralized control for multimachine power system

    Energy Technology Data Exchange (ETDEWEB)

    De Tuglie, Enrico [Dipartimento di Ingegneria dell' Ambiente, e per lo Sviluppo Sostenibile - DIASS, Politecnico di Bari, Viale del Turismo 8, 74100 Taranto (Italy); Iannone, Silvio Marcello; Torelli, Francesco [Dipartimento di Elettrotecnica, ed Elettronica - DEE, Politecnico di Bari, Via Re David 200, 70125 Bari (Italy)

    2008-03-15

    In this paper a decentralized nonlinear controller for large-scale power systems is investigated. The proposed controller design is based on the input-output feedback linearization methodology. In order to overcome computational difficulties in adopting such methodology, the overall interconnected nonlinear system, given as n-order, is analyzed as a cascade connection of an n{sub 1}-order nonlinear subsystem and an n{sub 2}-order linear subsystem. The controller design is obtained by applying input-output feedback linearization to the nonlinear subsystem and adopting a tracking control scheme, based on feedback-feedforward technique, for the linear subsystem. In the assumed system model, which is characterised by an interconnected structure between generating units, a decentralised adaptive controller is implemented by decentralizing these constraints. The use of a totally decentralised controller implies a system performance decay with respect to performance when the system is equipped with a centralised controller. Fortunately, the robustness of the proposed controller, based on input-output feedback procedure, guarantees good performance in terms of disturbance even when disturbances are caused by decentralization of interconnection constraints. Test results, provided on the IEEE 30 bus test system, demonstrate the effectiveness and practical applicability of proposed methodology. (author)

  4. Modeling and inverse feedforward control for conducting polymer actuators with hysteresis

    International Nuclear Information System (INIS)

    Wang, Xiangjiang; Alici, Gursel; Tan, Xiaobo

    2014-01-01

    Conducting polymer actuators are biocompatible with a small footprint, and operate in air or liquid media under low actuation voltages. This makes them excellent actuators for macro- and micro-manipulation devices, however, their positioning ability or accuracy is adversely affected by their hysteresis non-linearity under open-loop control strategies. In this paper, we establish a hysteresis model for conducting polymer actuators, based on a rate-independent hysteresis model known as the Duhem model. The hysteresis model is experimentally identified and integrated with the linear dynamics of the actuator. This combined model is inverted to control the displacement of the tri-layer actuators considered in this study, without using any external feedback. The inversion requires an inverse hysteresis model which was experimentally identified using an inverse neural network model. Experimental results show that the position tracking errors are reduced by more than 50% when the hysteresis inverse model is incorporated into an inversion-based feedforward controller, indicating the potential of the proposed method in enabling wider use of such smart actuators. (paper)

  5. Alpha and gamma oscillations characterize feedback and feedforward processing in monkey visual cortex.

    Science.gov (United States)

    van Kerkoerle, Timo; Self, Matthew W; Dagnino, Bruno; Gariel-Mathis, Marie-Alice; Poort, Jasper; van der Togt, Chris; Roelfsema, Pieter R

    2014-10-07

    Cognitive functions rely on the coordinated activity of neurons in many brain regions, but the interactions between cortical areas are not yet well understood. Here we investigated whether low-frequency (α) and high-frequency (γ) oscillations characterize different directions of information flow in monkey visual cortex. We recorded from all layers of the primary visual cortex (V1) and found that γ-waves are initiated in input layer 4 and propagate to the deep and superficial layers of cortex, whereas α-waves propagate in the opposite direction. Simultaneous recordings from V1 and downstream area V4 confirmed that γ- and α-waves propagate in the feedforward and feedback direction, respectively. Microstimulation in V1 elicited γ-oscillations in V4, whereas microstimulation in V4 elicited α-oscillations in V1, thus providing causal evidence for the opposite propagation of these rhythms. Furthermore, blocking NMDA receptors, thought to be involved in feedback processing, suppressed α while boosting γ. These results provide new insights into the relation between brain rhythms and cognition.

  6. Embedding the dynamics of a single delay system into a feed-forward ring.

    Science.gov (United States)

    Klinshov, Vladimir; Shchapin, Dmitry; Yanchuk, Serhiy; Wolfrum, Matthias; D'Huys, Otti; Nekorkin, Vladimir

    2017-10-01

    We investigate the relation between the dynamics of a single oscillator with delayed self-feedback and a feed-forward ring of such oscillators, where each unit is coupled to its next neighbor in the same way as in the self-feedback case. We show that periodic solutions of the delayed oscillator give rise to families of rotating waves with different wave numbers in the corresponding ring. In particular, if for the single oscillator the periodic solution is resonant to the delay, it can be embedded into a ring with instantaneous couplings. We discover several cases where the stability of a periodic solution for the single unit can be related to the stability of the corresponding rotating wave in the ring. As a specific example, we demonstrate how the complex bifurcation scenario of simultaneously emerging multijittering solutions can be transferred from a single oscillator with delayed pulse feedback to multijittering rotating waves in a sufficiently large ring of oscillators with instantaneous pulse coupling. Finally, we present an experimental realization of this dynamical phenomenon in a system of coupled electronic circuits of FitzHugh-Nagumo type.

  7. Hybrid Vibration Control under Broadband Excitation and Variable Temperature Using Viscoelastic Neutralizer and Adaptive Feedforward Approach

    Directory of Open Access Journals (Sweden)

    João C. O. Marra

    2016-01-01

    Full Text Available Vibratory phenomena have always surrounded human life. The need for more knowledge and domain of such phenomena increases more and more, especially in the modern society where the human-machine integration becomes closer day after day. In that context, this work deals with the development and practical implementation of a hybrid (passive-active/adaptive vibration control system over a metallic beam excited by a broadband signal and under variable temperature, between 5 and 35°C. Since temperature variations affect directly and considerably the performance of the passive control system, composed of a viscoelastic dynamic vibration neutralizer (also called a viscoelastic dynamic vibration absorber, the associative strategy of using an active-adaptive vibration control system (based on a feedforward approach with the use of the FXLMS algorithm working together with the passive one has shown to be a good option to compensate the neutralizer loss of performance and generally maintain the extended overall level of vibration control. As an additional gain, the association of both vibration control systems (passive and active-adaptive has improved the attenuation of vibration levels. Some key steps matured over years of research on this experimental setup are presented in this paper.

  8. Learning

    Directory of Open Access Journals (Sweden)

    Mohsen Laabidi

    2014-01-01

    Full Text Available Nowadays learning technologies transformed educational systems with impressive progress of Information and Communication Technologies (ICT. Furthermore, when these technologies are available, affordable and accessible, they represent more than a transformation for people with disabilities. They represent real opportunities with access to an inclusive education and help to overcome the obstacles they met in classical educational systems. In this paper, we will cover basic concepts of e-accessibility, universal design and assistive technologies, with a special focus on accessible e-learning systems. Then, we will present recent research works conducted in our research Laboratory LaTICE toward the development of an accessible online learning environment for persons with disabilities from the design and specification step to the implementation. We will present, in particular, the accessible version “MoodleAcc+” of the well known e-learning platform Moodle as well as new elaborated generic models and a range of tools for authoring and evaluating accessible educational content.

  9. Extreme learning machines 2013 algorithms and applications

    CERN Document Server

    Toh, Kar-Ann; Romay, Manuel; Mao, Kezhi

    2014-01-01

    In recent years, ELM has emerged as a revolutionary technique of computational intelligence, and has attracted considerable attentions. An extreme learning machine (ELM) is a single layer feed-forward neural network alike learning system, whose connections from the input layer to the hidden layer are randomly generated, while the connections from the hidden layer to the output layer are learned through linear learning methods. The outstanding merits of extreme learning machine (ELM) are its fast learning speed, trivial human intervene and high scalability.   This book contains some selected papers from the International Conference on Extreme Learning Machine 2013, which was held in Beijing China, October 15-17, 2013. This conference aims to bring together the researchers and practitioners of extreme learning machine from a variety of fields including artificial intelligence, biomedical engineering and bioinformatics, system modelling and control, and signal and image processing, to promote research and discu...

  10. Phase I to II cross-induction of xenobiotic metabolizing enzymes: A feedforward control mechanism for potential hormetic responses

    International Nuclear Information System (INIS)

    Zhang Qiang; Pi Jingbo; Woods, Courtney G.; Andersen, Melvin E.

    2009-01-01

    Hormetic responses to xenobiotic exposure likely occur as a result of overcompensation by the homeostatic control systems operating in biological organisms. However, the mechanisms underlying overcompensation that leads to hormesis are still unclear. A well-known homeostatic circuit in the cell is the gene induction network comprising phase I, II and III metabolizing enzymes, which are responsible for xenobiotic detoxification, and in many cases, bioactivation. By formulating a differential equation-based computational model, we investigated in this study whether hormesis can arise from the operation of this gene/enzyme network. The model consists of two feedback and one feedforward controls. With the phase I negative feedback control, xenobiotic X activates nuclear receptors to induce cytochrome P450 enzyme, which bioactivates X into a reactive metabolite X'. With the phase II negative feedback control, X' activates transcription factor Nrf2 to induce phase II enzymes such as glutathione S-transferase and glutamate cysteine ligase, etc., which participate in a set of reactions that lead to the metabolism of X' into a less toxic conjugate X''. The feedforward control involves phase I to II cross-induction, in which the parent chemical X can also induce phase II enzymes directly through the nuclear receptor and indirectly through transcriptionally upregulating Nrf2. As a result of the active feedforward control, a steady-state hormetic relationship readily arises between the concentrations of the reactive metabolite X' and the extracellular parent chemical X to which the cell is exposed. The shape of dose-response evolves over time from initially monotonically increasing to J-shaped at the final steady state-a temporal sequence consistent with adaptation-mediated hormesis. The magnitude of the hormetic response is enhanced by increases in the feedforward gain, but attenuated by increases in the bioactivation or phase II feedback loop gains. Our study suggests a

  11. Phase I to II cross-induction of xenobiotic metabolizing enzymes: a feedforward control mechanism for potential hormetic responses.

    Science.gov (United States)

    Zhang, Qiang; Pi, Jingbo; Woods, Courtney G; Andersen, Melvin E

    2009-06-15

    Hormetic responses to xenobiotic exposure likely occur as a result of overcompensation by the homeostatic control systems operating in biological organisms. However, the mechanisms underlying overcompensation that leads to hormesis are still unclear. A well-known homeostatic circuit in the cell is the gene induction network comprising phase I, II and III metabolizing enzymes, which are responsible for xenobiotic detoxification, and in many cases, bioactivation. By formulating a differential equation-based computational model, we investigated in this study whether hormesis can arise from the operation of this gene/enzyme network. The model consists of two feedback and one feedforward controls. With the phase I negative feedback control, xenobiotic X activates nuclear receptors to induce cytochrome P450 enzyme, which bioactivates X into a reactive metabolite X'. With the phase II negative feedback control, X' activates transcription factor Nrf2 to induce phase II enzymes such as glutathione S-transferase and glutamate cysteine ligase, etc., which participate in a set of reactions that lead to the metabolism of X' into a less toxic conjugate X''. The feedforward control involves phase I to II cross-induction, in which the parent chemical X can also induce phase II enzymes directly through the nuclear receptor and indirectly through transcriptionally upregulating Nrf2. As a result of the active feedforward control, a steady-state hormetic relationship readily arises between the concentrations of the reactive metabolite X' and the extracellular parent chemical X to which the cell is exposed. The shape of dose-response evolves over time from initially monotonically increasing to J-shaped at the final steady state-a temporal sequence consistent with adaptation-mediated hormesis. The magnitude of the hormetic response is enhanced by increases in the feedforward gain, but attenuated by increases in the bioactivation or phase II feedback loop gains. Our study suggests a

  12. Improved Extreme Learning Machine and Its Application in Image Quality Assessment

    OpenAIRE

    Mao, Li; Zhang, Lidong; Liu, Xingyang; Li, Chaofeng; Yang, Hong

    2014-01-01

    Extreme learning machine (ELM) is a new class of single-hidden layer feedforward neural network (SLFN), which is simple in theory and fast in implementation. Zong et al. propose a weighted extreme learning machine for learning data with imbalanced class distribution, which maintains the advantages from original ELM. However, the current reported ELM and its improved version are only based on the empirical risk minimization principle, which may suffer from overfitting. To solve the overfitting...

  13. Designing an Adaptive Web-Based Learning System Based on Students' Cognitive Styles Identified Online

    Science.gov (United States)

    Lo, Jia-Jiunn; Chan, Ya-Chen; Yeh, Shiou-Wen

    2012-01-01

    This study developed an adaptive web-based learning system focusing on students' cognitive styles. The system is composed of a student model and an adaptation model. It collected students' browsing behaviors to update the student model for unobtrusively identifying student cognitive styles through a multi-layer feed-forward neural network (MLFF).…

  14. TEKNIK JARINGAN SYARAF TIRUAN FEEDFORWARD UNTUK PREDIKSI HARGA SAHAM PADA PASAR MODAL INDONESIA

    Directory of Open Access Journals (Sweden)

    Budi Bambang DP.

    1999-01-01

    , beberapa model analisa teknik telah dipakai dan dikembangkan, beberapa analisa tersebut seperti : MACD , Fourier Transform, Accumulator Swing Index, Stochastic Oscilator dan lain lain. Sebagai masukannya digunakan beberapa macam kombinasi harga seperti : harga pembukaan, tertinggi, terendah, penutupan kemarin dan penutupan hari ini serta volume perdagangan. Dan sebagai keluaran adalah suatu grafik yang menampilkan suatu keputusan beli atau jual. Suatu cara lain dalam menentukan harga saham adalah dengan menggunakan metoda 'Fundamental Analysis', yaitu suatu analisa dimana penampilan dari suatu kinerja perusahaan didasarkan atas ratio-ratio / laporan keuangan yang ada. Teknologi sistem jaringan syaraf tiruan telah di-implementasikan dalam berbagai aplikasi terutama dalam hal pengenalan pola. Kemampuan inilah yang telah menarik beberapa kalangan dalam menggunakan jaringan syaraf tiruan untuk keperluan kesehatan, keuangan , investasi, marketing dan lain lain. Pada makalah ini akan dibahas penggunaan Jaringan syaraf tiruan Feedforward/Backpropagarion. Data dari harga saham dapat diperlakukan secara 'time series' . Jika kita mempunyai data harian selama perioda tertentu, misal : Xt (t=1,2,......, maka harga saham pada perioda berikutnya (t+h dapat diprediksi (waktu yang digunakan bisa jam, harian, mingguan , bulanan ataupun tahunan . Demikian seterusnya dilakukan suatu iterasi berulang hingan N hari kerja. Untuk mendapatkan hasil prediksi yang baik maka pada jaringan syaraf buatan hasus di-umpankan suatu masukan yang mewakili dari beberapa aspek atau segi penunjang harga suatu saham. Kemudian dilakukan prinsip pembobotan yang diadaptasikan untuk meminimumkan kesalahan prediksi pada satu langkah kedepan. Dengan menggunakan bobot akhir dilakukan suatu tindakan untuk meminimumkan kesalahan total untuk iterasi berikutnya. Saham yang akan dibahas adalah saham Semen Gresik (SMGR dan Gudang Garam (GGRM Kata kunci: prediksi harga saham, jaringan syaraf tiruan, time series feedforward

  15. Predictive zero-dimensional combustion model for DI diesel engine feed-forward control

    International Nuclear Information System (INIS)

    Catania, Andrea Emilio; Finesso, Roberto; Spessa, Ezio

    2011-01-01

    Highlights: → Zero-dimensional low-throughput combustion model for real-time control in diesel engine applications. → Feed-forward control of MFB50, p max and IMEP in both conventional and PCCI combustion modes. → Capability of resolving the contribution to HRR of each injection pulse in multiple injection schedule. → Ignition delay and model parameters estimated through physically consistent and easy-to-tune correlations. - Abstract: An innovative zero-dimensional predictive combustion model has been developed for the estimation of HRR (heat release rate) and in-cylinder pressure traces. This model has been assessed and applied to conventional and PCCI (premixed charge compression ignition) DI diesel engines for model-based feed-forward control purposes. The injection rate profile is calculated on the basis of the injected fuel quantities and on the injection parameters, such as SOI (start of injection), ET (energizing time), and DT (dwell time), taking the injector NOD (nozzle opening delay) and NCD (nozzle closure delay) into account. The injection rate profile in turn allows the released chemical energy Q ch to be estimated. The approach starts from the assumption that, at each time instant, the HRR is proportional to the energy associated with the accumulated fuel mass in the combustion chamber. The main novelties of the proposed approach consist of the method that is adopted to estimate the fuel ignition delay and of injection rate splitting for HRR estimation. The procedure allows an accurate calculation to be made of the different combustion parameters that are important for engine calibration, such as SOC (start of combustion) and MFB50 (50% of fuel mass fraction burned angle). On the basis of an estimation of the fuel released chemical energy, of the heat globally exchanged from the charge with the walls and of the energy associated with the fuel evaporation, the charge net energy is calculated, for a subsequent evaluation of the in

  16. Predictive zero-dimensional combustion model for DI diesel engine feed-forward control

    Energy Technology Data Exchange (ETDEWEB)

    Catania, Andrea Emilio; Finesso, Roberto [IC Engines Advanced Laboratory, Politecnico di Torino, c.so Duca degli Abruzzi 24, 10129 Torino (Italy); Spessa, Ezio, E-mail: ezio.spessa@polito.it [IC Engines Advanced Laboratory, Politecnico di Torino, c.so Duca degli Abruzzi 24, 10129 Torino (Italy)

    2011-09-15

    Highlights: {yields} Zero-dimensional low-throughput combustion model for real-time control in diesel engine applications. {yields} Feed-forward control of MFB50, p{sub max} and IMEP in both conventional and PCCI combustion modes. {yields} Capability of resolving the contribution to HRR of each injection pulse in multiple injection schedule. {yields} Ignition delay and model parameters estimated through physically consistent and easy-to-tune correlations. - Abstract: An innovative zero-dimensional predictive combustion model has been developed for the estimation of HRR (heat release rate) and in-cylinder pressure traces. This model has been assessed and applied to conventional and PCCI (premixed charge compression ignition) DI diesel engines for model-based feed-forward control purposes. The injection rate profile is calculated on the basis of the injected fuel quantities and on the injection parameters, such as SOI (start of injection), ET (energizing time), and DT (dwell time), taking the injector NOD (nozzle opening delay) and NCD (nozzle closure delay) into account. The injection rate profile in turn allows the released chemical energy Q{sub ch} to be estimated. The approach starts from the assumption that, at each time instant, the HRR is proportional to the energy associated with the accumulated fuel mass in the combustion chamber. The main novelties of the proposed approach consist of the method that is adopted to estimate the fuel ignition delay and of injection rate splitting for HRR estimation. The procedure allows an accurate calculation to be made of the different combustion parameters that are important for engine calibration, such as SOC (start of combustion) and MFB50 (50% of fuel mass fraction burned angle). On the basis of an estimation of the fuel released chemical energy, of the heat globally exchanged from the charge with the walls and of the energy associated with the fuel evaporation, the charge net energy is calculated, for a subsequent

  17. Spike-timing computation properties of a feed-forward neural network model

    Directory of Open Access Journals (Sweden)

    Drew Benjamin Sinha

    2014-01-01

    Full Text Available Brain function is characterized by dynamical interactions among networks of neurons. These interactions are mediated by network topology at many scales ranging from microcircuits to brain areas. Understanding how networks operate can be aided by understanding how the transformation of inputs depends upon network connectivity patterns, e.g. serial and parallel pathways. To tractably determine how single synapses or groups of synapses in such pathways shape transformations, we modeled feed-forward networks of 7-22 neurons in which synaptic strength changed according to a spike-timing dependent plasticity rule. We investigated how activity varied when dynamics were perturbed by an activity-dependent electrical stimulation protocol (spike-triggered stimulation; STS in networks of different topologies and background input correlations. STS can successfully reorganize functional brain networks in vivo, but with a variability in effectiveness that may derive partially from the underlying network topology. In a simulated network with a single disynaptic pathway driven by uncorrelated background activity, structured spike-timing relationships between polysynaptically connected neurons were not observed. When background activity was correlated or parallel disynaptic pathways were added, however, robust polysynaptic spike timing relationships were observed, and application of STS yielded predictable changes in synaptic strengths and spike-timing relationships. These observations suggest that precise input-related or topologically induced temporal relationships in network activity are necessary for polysynaptic signal propagation. Such constraints for polysynaptic computation suggest potential roles for higher-order topological structure in network organization, such as maintaining polysynaptic correlation in the face of relatively weak synapses.

  18. The role of incoherent microRNA-mediated feedforward loops in noise buffering.

    Directory of Open Access Journals (Sweden)

    Matteo Osella

    2011-03-01

    Full Text Available MicroRNAs are endogenous non-coding RNAs which negatively regulate the expression of protein-coding genes in plants and animals. They are known to play an important role in several biological processes and, together with transcription factors, form a complex and highly interconnected regulatory network. Looking at the structure of this network, it is possible to recognize a few overrepresented motifs which are expected to perform important elementary regulatory functions. Among them, a special role is played by the microRNA-mediated feedforward loop in which a master transcription factor regulates a microRNA and, together with it, a set of target genes. In this paper we show analytically and through simulations that the incoherent version of this motif can couple the fine-tuning of a target protein level with an efficient noise control, thus conferring precision and stability to the overall gene expression program, especially in the presence of fluctuations in upstream regulators. Among the other results, a nontrivial prediction of our model is that the optimal attenuation of fluctuations coincides with a modest repression of the target expression. This feature is coherent with the expected fine-tuning function and in agreement with experimental observations of the actual impact of a wide class of microRNAs on the protein output of their targets. Finally, we describe the impact on noise-buffering efficiency of the cross-talk between microRNA targets that can naturally arise if the microRNA-mediated circuit is not considered as isolated, but embedded in a larger network of regulations.

  19. Improving the performance of interferometric imaging through the use of disturbance feedforward.

    Science.gov (United States)

    Böhm, Michael; Glück, Martin; Keck, Alexander; Pott, Jörg-Uwe; Sawodny, Oliver

    2017-05-01

    In this paper, we present a disturbance compensation technique to improve the performance of interferometric imaging for extremely large ground-based telescopes, e.g., the Large Binocular Telescope (LBT), which serves as the application example in this contribution. The most significant disturbance sources at ground-based telescopes are wind-induced mechanical vibrations in the range of 8-60 Hz. Traditionally, their optical effect is eliminated by feedback systems, such as the adaptive optics control loop combined with a fringe tracking system within the interferometric instrument. In this paper, accelerometers are used to measure the vibrations. These measurements are used to estimate the motion of the mirrors, i.e., tip, tilt and piston, with a dynamic estimator. Additional delay compensation methods are presented to cancel sensor network delays and actuator input delays, improving the estimation result even more, particularly at higher frequencies. Because various instruments benefit from the implementation of telescope vibration mitigation, the estimator is implemented as a separate, independent software on the telescope, publishing the estimated values via multicast on the telescope's ethernet. Every client capable of using and correcting the estimated disturbances can subscribe and use these values in a feedforward for its compensation device, e.g., the deformable mirror, the piston mirror of LINC-NIRVANA, or the fast path length corrector of the Large Binocular Telescope Interferometer. This easy-to-use approach eventually leveraged the presented technology for interferometric use at the LBT and now significantly improves the sky coverage, performance, and operational robustness of interferometric imaging on a regular basis.

  20. Patient DF's visual brain in action: Visual feedforward control in visual form agnosia.

    Science.gov (United States)

    Whitwell, Robert L; Milner, A David; Cavina-Pratesi, Cristiana; Barat, Masihullah; Goodale, Melvyn A

    2015-05-01

    Patient DF, who developed visual form agnosia following ventral-stream damage, is unable to discriminate the width of objects, performing at chance, for example, when asked to open her thumb and forefinger a matching amount. Remarkably, however, DF adjusts her hand aperture to accommodate the width of objects when reaching out to pick them up (grip scaling). While this spared ability to grasp objects is presumed to be mediated by visuomotor modules in her relatively intact dorsal stream, it is possible that it may rely abnormally on online visual or haptic feedback. We report here that DF's grip scaling remained intact when her vision was completely suppressed during grasp movements, and it still dissociated sharply from her poor perceptual estimates of target size. We then tested whether providing trial-by-trial haptic feedback after making such perceptual estimates might improve DF's performance, but found that they remained significantly impaired. In a final experiment, we re-examined whether DF's grip scaling depends on receiving veridical haptic feedback during grasping. In one condition, the haptic feedback was identical to the visual targets. In a second condition, the haptic feedback was of a constant intermediate width while the visual target varied trial by trial. Despite this incongruent feedback, DF still scaled her grip aperture to the visual widths of the target blocks, showing only normal adaptation to the false haptically-experienced width. Taken together, these results strengthen the view that DF's spared grasping relies on a normal mode of dorsal-stream functioning, based chiefly on visual feedforward processing. Copyright © 2014 Elsevier B.V. All rights reserved.