Forced Sequence Sequential Decoding
DEFF Research Database (Denmark)
Jensen, Ole Riis
In this thesis we describe a new concatenated decoding scheme based on iterations between an inner sequentially decoded convolutional code of rate R=1/4 and memory M=23, and block interleaved outer Reed-Solomon codes with non-uniform profile. With this scheme decoding with good performance...... is possible as low as Eb/No=0.6 dB, which is about 1.7 dB below the signal-to-noise ratio that marks the cut-off rate for the convolutional code. This is possible since the iteration process provides the sequential decoders with side information that allows a smaller average load and minimizes the probability...... of computational overflow. Analytical results for the probability that the first Reed-Solomon word is decoded after C computations are presented. This is supported by simulation results that are also extended to other parameters....
Forced Sequence Sequential Decoding
DEFF Research Database (Denmark)
Jensen, Ole Riis; Paaske, Erik
1998-01-01
We describe a new concatenated decoding scheme based on iterations between an inner sequentially decoded convolutional code of rate R=1/4 and memory M=23, and block interleaved outer Reed-Solomon (RS) codes with nonuniform profile. With this scheme decoding with good performance is possible as low...... as Eb/N0=0.6 dB, which is about 1.25 dB below the signal-to-noise ratio (SNR) that marks the cutoff rate for the full system. Accounting for about 0.45 dB due to the outer codes, sequential decoding takes place at about 1.7 dB below the SNR cutoff rate for the convolutional code. This is possible since...... the iteration process provides the sequential decoders with side information that allows a smaller average load and minimizes the probability of computational overflow. Analytical results for the probability that the first RS word is decoded after C computations are presented. These results are supported...
Concatenated coding system with iterated sequential inner decoding
DEFF Research Database (Denmark)
Jensen, Ole Riis; Paaske, Erik
1995-01-01
We describe a concatenated coding system with iterated sequential inner decoding. The system uses convolutional codes of very long constraint length and operates on iterations between an inner Fano decoder and an outer Reed-Solomon decoder......We describe a concatenated coding system with iterated sequential inner decoding. The system uses convolutional codes of very long constraint length and operates on iterations between an inner Fano decoder and an outer Reed-Solomon decoder...
Sequential decoders for large MIMO systems
Ali, Konpal S.; Abediseid, Walid; Alouini, Mohamed-Slim
2014-01-01
the Sequential Decoder using the Fano Algorithm for large MIMO systems. A parameter called the bias is varied to attain different performance-complexity trade-offs. Low values of the bias result in excellent performance but at the expense of high complexity
Sequential decoders for large MIMO systems
Ali, Konpal S.
2014-05-01
Due to their ability to provide high data rates, multiple-input multiple-output (MIMO) systems have become increasingly popular. Decoding of these systems with acceptable error performance is computationally very demanding. In this paper, we employ the Sequential Decoder using the Fano Algorithm for large MIMO systems. A parameter called the bias is varied to attain different performance-complexity trade-offs. Low values of the bias result in excellent performance but at the expense of high complexity and vice versa for higher bias values. Numerical results are done that show moderate bias values result in a decent performance-complexity trade-off. We also attempt to bound the error by bounding the bias, using the minimum distance of a lattice. The variations in complexity with SNR have an interesting trend that shows room for considerable improvement. Our work is compared against linear decoders (LDs) aided with Element-based Lattice Reduction (ELR) and Complex Lenstra-Lenstra-Lovasz (CLLL) reduction. © 2014 IFIP.
On Lattice Sequential Decoding for The Unconstrained AWGN Channel
Abediseid, Walid
2013-04-04
In this paper, the performance limits and the computational complexity of the lattice sequential decoder are analyzed for the unconstrained additive white Gaussian noise channel. The performance analysis available in the literature for such a channel has been studied only under the use of the minimum Euclidean distance decoder that is commonly referred to as the \\\\textit{lattice decoder}. Lattice decoders based on solutions to the NP-hard closest vector problem are very complex to implement, and the search for low complexity receivers for the detection of lattice codes is considered a challenging problem. However, the low computational complexity advantage that sequential decoding promises, makes it an alternative solution to the lattice decoder. In this work, we characterize the performance and complexity tradeoff via the error exponent and the decoding complexity, respectively, of such a decoder as a function of the decoding parameter --- the bias term. For the above channel, we derive the cut-off volume-to-noise ratio that is required to achieve a good error performance with low decoding complexity.
On Lattice Sequential Decoding for The Unconstrained AWGN Channel
Abediseid, Walid
2012-10-01
In this paper, the performance limits and the computational complexity of the lattice sequential decoder are analyzed for the unconstrained additive white Gaussian noise channel. The performance analysis available in the literature for such a channel has been studied only under the use of the minimum Euclidean distance decoder that is commonly referred to as the lattice decoder. Lattice decoders based on solutions to the NP-hard closest vector problem are very complex to implement, and the search for low complexity receivers for the detection of lattice codes is considered a challenging problem. However, the low computational complexity advantage that sequential decoding promises, makes it an alternative solution to the lattice decoder. In this work, we characterize the performance and complexity tradeoff via the error exponent and the decoding complexity, respectively, of such a decoder as a function of the decoding parameter --- the bias term. For the above channel, we derive the cut-off volume-to-noise ratio that is required to achieve a good error performance with low decoding complexity.
On Lattice Sequential Decoding for The Unconstrained AWGN Channel
Abediseid, Walid; Alouini, Mohamed-Slim
2012-01-01
In this paper, the performance limits and the computational complexity of the lattice sequential decoder are analyzed for the unconstrained additive white Gaussian noise channel. The performance analysis available in the literature for such a channel has been studied only under the use of the minimum Euclidean distance decoder that is commonly referred to as the lattice decoder. Lattice decoders based on solutions to the NP-hard closest vector problem are very complex to implement, and the search for low complexity receivers for the detection of lattice codes is considered a challenging problem. However, the low computational complexity advantage that sequential decoding promises, makes it an alternative solution to the lattice decoder. In this work, we characterize the performance and complexity tradeoff via the error exponent and the decoding complexity, respectively, of such a decoder as a function of the decoding parameter --- the bias term. For the above channel, we derive the cut-off volume-to-noise ratio that is required to achieve a good error performance with low decoding complexity.
Lexical decoder for continuous speech recognition: sequential neural network approach
International Nuclear Information System (INIS)
Iooss, Christine
1991-01-01
The work presented in this dissertation concerns the study of a connectionist architecture to treat sequential inputs. In this context, the model proposed by J.L. Elman, a recurrent multilayers network, is used. Its abilities and its limits are evaluated. Modifications are done in order to treat erroneous or noisy sequential inputs and to classify patterns. The application context of this study concerns the realisation of a lexical decoder for analytical multi-speakers continuous speech recognition. Lexical decoding is completed from lattices of phonemes which are obtained after an acoustic-phonetic decoding stage relying on a K Nearest Neighbors search technique. Test are done on sentences formed from a lexicon of 20 words. The results are obtained show the ability of the proposed connectionist model to take into account the sequentiality at the input level, to memorize the context and to treat noisy or erroneous inputs. (author) [fr
Systolic array processing of the sequential decoding algorithm
Chang, C. Y.; Yao, K.
1989-01-01
A systolic array processing technique is applied to implementing the stack algorithm form of the sequential decoding algorithm. It is shown that sorting, a key function in the stack algorithm, can be efficiently realized by a special type of systolic arrays known as systolic priority queues. Compared to the stack-bucket algorithm, this approach is shown to have the advantages that the decoding always moves along the optimal path, that it has a fast and constant decoding speed and that its simple and regular hardware architecture is suitable for VLSI implementation. Three types of systolic priority queues are discussed: random access scheme, shift register scheme and ripple register scheme. The property of the entries stored in the systolic priority queue is also investigated. The results are applicable to many other basic sorting type problems.
Decoding restricted participation in sequential electricity markets
Energy Technology Data Exchange (ETDEWEB)
Knaut, Andreas; Paschmann, Martin
2017-06-15
Restricted participation in sequential markets may cause high price volatility and welfare losses. In this paper we therefore analyze the drivers of restricted participation in the German intraday auction which is a short-term electricity market with quarter-hourly products. Applying a fundamental electricity market model with 15-minute temporal resolution, we identify the lack of sub-hourly market coupling being the most relevant driver of restricted participation. We derive a proxy for price volatility and find that full market coupling may trigger quarter-hourly price volatility to decrease by a factor close to four.
On Lattice Sequential Decoding for Large MIMO Systems
Ali, Konpal S.
2014-04-01
Due to their ability to provide high data rates, Multiple-Input Multiple-Output (MIMO) wireless communication systems have become increasingly popular. Decoding of these systems with acceptable error performance is computationally very demanding. In the case of large overdetermined MIMO systems, we employ the Sequential Decoder using the Fano Algorithm. A parameter called the bias is varied to attain different performance-complexity trade-offs. Low values of the bias result in excellent performance but at the expense of high complexity and vice versa for higher bias values. We attempt to bound the error by bounding the bias, using the minimum distance of a lattice. Also, a particular trend is observed with increasing SNR: a region of low complexity and high error, followed by a region of high complexity and error falling, and finally a region of low complexity and low error. For lower bias values, the stages of the trend are incurred at lower SNR than for higher bias values. This has the important implication that a low enough bias value, at low to moderate SNR, can result in low error and low complexity even for large MIMO systems. Our work is compared against Lattice Reduction (LR) aided Linear Decoders (LDs). Another impressive observation for low bias values that satisfy the error bound is that the Sequential Decoder\\'s error is seen to fall with increasing system size, while it grows for the LR-aided LDs. For the case of large underdetermined MIMO systems, Sequential Decoding with two preprocessing schemes is proposed – 1) Minimum Mean Square Error Generalized Decision Feedback Equalization (MMSE-GDFE) preprocessing 2) MMSE-GDFE preprocessing, followed by Lattice Reduction and Greedy Ordering. Our work is compared against previous work which employs Sphere Decoding preprocessed using MMSE-GDFE, Lattice Reduction and Greedy Ordering. For the case of large systems, this results in high complexity and difficulty in choosing the sphere radius. Our schemes
Sequential decoding of intramuscular EMG signals via estimation of a Markov model.
Monsifrot, Jonathan; Le Carpentier, Eric; Aoustin, Yannick; Farina, Dario
2014-09-01
This paper addresses the sequential decoding of intramuscular single-channel electromyographic (EMG) signals to extract the activity of individual motor neurons. A hidden Markov model is derived from the physiological generation of the EMG signal. The EMG signal is described as a sum of several action potentials (wavelet) trains, embedded in noise. For each train, the time interval between wavelets is modeled by a process that parameters are linked to the muscular activity. The parameters of this process are estimated sequentially by a Bayes filter, along with the firing instants. The method was tested on some simulated signals and an experimental one, from which the rates of detection and classification of action potentials were above 95% with respect to the reference decomposition. The method works sequentially in time, and is the first to address the problem of intramuscular EMG decomposition online. It has potential applications for man-machine interfacing based on motor neuron activities.
On Lattice Sequential Decoding for The Unconstrained AWGN Channel
Abediseid, Walid; Alouini, Mohamed-Slim
2013-01-01
channel has been studied only under the use of the minimum Euclidean distance decoder that is commonly referred to as the \\textit{lattice decoder}. Lattice decoders based on solutions to the NP-hard closest vector problem are very complex to implement
Performance-complexity tradeoff in sequential decoding for the unconstrained AWGN channel
Abediseid, Walid
2013-06-01
In this paper, the performance limits and the computational complexity of the lattice sequential decoder are analyzed for the unconstrained additive white Gaussian noise channel. The performance analysis available in the literature for such a channel has been studied only under the use of the minimum Euclidean distance decoder that is commonly referred to as the lattice decoder. Lattice decoders based on solutions to the NP-hard closest vector problem are very complex to implement, and the search for low complexity receivers for the detection of lattice codes is considered a challenging problem. However, the low computational complexity advantage that sequential decoding promises, makes it an alternative solution to the lattice decoder. In this work, we characterize the performance and complexity tradeoff via the error exponent and the decoding complexity, respectively, of such a decoder as a function of the decoding parameter - the bias term. For the above channel, we derive the cut-off volume-to-noise ratio that is required to achieve a good error performance with low decoding complexity. © 2013 IEEE.
An Improved Unscented Kalman Filter Based Decoder for Cortical Brain-Machine Interfaces.
Li, Simin; Li, Jie; Li, Zheng
2016-01-01
Brain-machine interfaces (BMIs) seek to connect brains with machines or computers directly, for application in areas such as prosthesis control. For this application, the accuracy of the decoding of movement intentions is crucial. We aim to improve accuracy by designing a better encoding model of primary motor cortical activity during hand movements and combining this with decoder engineering refinements, resulting in a new unscented Kalman filter based decoder, UKF2, which improves upon our previous unscented Kalman filter decoder, UKF1. The new encoding model includes novel acceleration magnitude, position-velocity interaction, and target-cursor-distance features (the decoder does not require target position as input, it is decoded). We add a novel probabilistic velocity threshold to better determine the user's intent to move. We combine these improvements with several other refinements suggested by others in the field. Data from two Rhesus monkeys indicate that the UKF2 generates offline reconstructions of hand movements (mean CC 0.851) significantly more accurately than the UKF1 (0.833) and the popular position-velocity Kalman filter (0.812). The encoding model of the UKF2 could predict the instantaneous firing rate of neurons (mean CC 0.210), given kinematic variables and past spiking, better than the encoding models of these two decoders (UKF1: 0.138, p-v Kalman: 0.098). In closed-loop experiments where each monkey controlled a computer cursor with each decoder in turn, the UKF2 facilitated faster task completion (mean 1.56 s vs. 2.05 s) and higher Fitts's Law bit rate (mean 0.738 bit/s vs. 0.584 bit/s) than the UKF1. These results suggest that the modeling and decoder engineering refinements of the UKF2 improve decoding performance. We believe they can be used to enhance other decoders as well.
Weighted-Bit-Flipping-Based Sequential Scheduling Decoding Algorithms for LDPC Codes
Directory of Open Access Journals (Sweden)
Qing Zhu
2013-01-01
Full Text Available Low-density parity-check (LDPC codes can be applied in a lot of different scenarios such as video broadcasting and satellite communications. LDPC codes are commonly decoded by an iterative algorithm called belief propagation (BP over the corresponding Tanner graph. The original BP updates all the variable-nodes simultaneously, followed by all the check-nodes simultaneously as well. We propose a sequential scheduling algorithm based on weighted bit-flipping (WBF algorithm for the sake of improving the convergence speed. Notoriously, WBF is a low-complexity and simple algorithm. We combine it with BP to obtain advantages of these two algorithms. Flipping function used in WBF is borrowed to determine the priority of scheduling. Simulation results show that it can provide a good tradeoff between FER performance and computation complexity for short-length LDPC codes.
Decoder calibration with ultra small current sample set for intracortical brain-machine interface
Zhang, Peng; Ma, Xuan; Chen, Luyao; Zhou, Jin; Wang, Changyong; Li, Wei; He, Jiping
2018-04-01
Objective. Intracortical brain-machine interfaces (iBMIs) aim to restore efficient communication and movement ability for paralyzed patients. However, frequent recalibration is required for consistency and reliability, and every recalibration will require relatively large most current sample set. The aim in this study is to develop an effective decoder calibration method that can achieve good performance while minimizing recalibration time. Approach. Two rhesus macaques implanted with intracortical microelectrode arrays were trained separately on movement and sensory paradigm. Neural signals were recorded to decode reaching positions or grasping postures. A novel principal component analysis-based domain adaptation (PDA) method was proposed to recalibrate the decoder with only ultra small current sample set by taking advantage of large historical data, and the decoding performance was compared with other three calibration methods for evaluation. Main results. The PDA method closed the gap between historical and current data effectively, and made it possible to take advantage of large historical data for decoder recalibration in current data decoding. Using only ultra small current sample set (five trials of each category), the decoder calibrated using the PDA method could achieve much better and more robust performance in all sessions than using other three calibration methods in both monkeys. Significance. (1) By this study, transfer learning theory was brought into iBMIs decoder calibration for the first time. (2) Different from most transfer learning studies, the target data in this study were ultra small sample set and were transferred to the source data. (3) By taking advantage of historical data, the PDA method was demonstrated to be effective in reducing recalibration time for both movement paradigm and sensory paradigm, indicating a viable generalization. By reducing the demand for large current training data, this new method may facilitate the application
Performance-complexity tradeoff in sequential decoding for the unconstrained AWGN channel
Abediseid, Walid; Alouini, Mohamed-Slim
2013-01-01
channel has been studied only under the use of the minimum Euclidean distance decoder that is commonly referred to as the lattice decoder. Lattice decoders based on solutions to the NP-hard closest vector problem are very complex to implement
Online Sequential Projection Vector Machine with Adaptive Data Mean Update.
Chen, Lin; Jia, Ji-Ting; Zhang, Qiong; Deng, Wan-Yu; Wei, Wei
2016-01-01
We propose a simple online learning algorithm especial for high-dimensional data. The algorithm is referred to as online sequential projection vector machine (OSPVM) which derives from projection vector machine and can learn from data in one-by-one or chunk-by-chunk mode. In OSPVM, data centering, dimension reduction, and neural network training are integrated seamlessly. In particular, the model parameters including (1) the projection vectors for dimension reduction, (2) the input weights, biases, and output weights, and (3) the number of hidden nodes can be updated simultaneously. Moreover, only one parameter, the number of hidden nodes, needs to be determined manually, and this makes it easy for use in real applications. Performance comparison was made on various high-dimensional classification problems for OSPVM against other fast online algorithms including budgeted stochastic gradient descent (BSGD) approach, adaptive multihyperplane machine (AMM), primal estimated subgradient solver (Pegasos), online sequential extreme learning machine (OSELM), and SVD + OSELM (feature selection based on SVD is performed before OSELM). The results obtained demonstrated the superior generalization performance and efficiency of the OSPVM.
Online Sequential Projection Vector Machine with Adaptive Data Mean Update
Directory of Open Access Journals (Sweden)
Lin Chen
2016-01-01
Full Text Available We propose a simple online learning algorithm especial for high-dimensional data. The algorithm is referred to as online sequential projection vector machine (OSPVM which derives from projection vector machine and can learn from data in one-by-one or chunk-by-chunk mode. In OSPVM, data centering, dimension reduction, and neural network training are integrated seamlessly. In particular, the model parameters including (1 the projection vectors for dimension reduction, (2 the input weights, biases, and output weights, and (3 the number of hidden nodes can be updated simultaneously. Moreover, only one parameter, the number of hidden nodes, needs to be determined manually, and this makes it easy for use in real applications. Performance comparison was made on various high-dimensional classification problems for OSPVM against other fast online algorithms including budgeted stochastic gradient descent (BSGD approach, adaptive multihyperplane machine (AMM, primal estimated subgradient solver (Pegasos, online sequential extreme learning machine (OSELM, and SVD + OSELM (feature selection based on SVD is performed before OSELM. The results obtained demonstrated the superior generalization performance and efficiency of the OSPVM.
A bidirectional brain-machine interface featuring a neuromorphic hardware decoder
Directory of Open Access Journals (Sweden)
Fabio Boi
2016-12-01
Full Text Available Bidirectional brain-machine interfaces (BMIs establish a two-way direct communication link4 between the brain and the external world. A decoder translates recorded neural activity into motor5 commands and an encoder delivers sensory information collected from the environment directly6 to the brain creating a closed-loop system. These two modules are typically integrated in bulky7 external devices. However, the clinical support of patients with severe motor and sensory deficits8 requires compact, low-power, and fully implantable systems that can decode neural signals to9 control external devices. As a first step toward this goal, we developed a modular bidirectional BMI10 setup that uses a compact neuromorphic processor as a decoder. On this chip we implemented11 a network of spiking neurons built using its ultra-low-power mixed-signal analog/digital circuits.12 On-chip on-line spike-timing-dependent plasticity synapse circuits enabled the network to learn13 to decode neural signals recorded from the brain into motor outputs controlling the movements14 of an external device. The modularity of the BMI allowed us to tune the individual components15 of the setup without modifying the whole system. In this paper we present the features of16 this modular BMI, and describe how we configured the network of spiking neuron circuits to17 implement the decoder and to coordinate it with the encoder in an experimental BMI paradigm18 that connects bidirectionally the brain of an anesthetized rat with an external object. We show that19 the chip learned the decoding task correctly, allowing the interfaced brain to control the object’s20 trajectories robustly. Based on our demonstration, we propose that neuromorphic technology is21 mature enough for the development of BMI modules that are sufficiently low-power and compact,22 while being highly computationally powerful and adaptive.
A Bidirectional Brain-Machine Interface Featuring a Neuromorphic Hardware Decoder.
Boi, Fabio; Moraitis, Timoleon; De Feo, Vito; Diotalevi, Francesco; Bartolozzi, Chiara; Indiveri, Giacomo; Vato, Alessandro
2016-01-01
Bidirectional brain-machine interfaces (BMIs) establish a two-way direct communication link between the brain and the external world. A decoder translates recorded neural activity into motor commands and an encoder delivers sensory information collected from the environment directly to the brain creating a closed-loop system. These two modules are typically integrated in bulky external devices. However, the clinical support of patients with severe motor and sensory deficits requires compact, low-power, and fully implantable systems that can decode neural signals to control external devices. As a first step toward this goal, we developed a modular bidirectional BMI setup that uses a compact neuromorphic processor as a decoder. On this chip we implemented a network of spiking neurons built using its ultra-low-power mixed-signal analog/digital circuits. On-chip on-line spike-timing-dependent plasticity synapse circuits enabled the network to learn to decode neural signals recorded from the brain into motor outputs controlling the movements of an external device. The modularity of the BMI allowed us to tune the individual components of the setup without modifying the whole system. In this paper, we present the features of this modular BMI and describe how we configured the network of spiking neuron circuits to implement the decoder and to coordinate it with the encoder in an experimental BMI paradigm that connects bidirectionally the brain of an anesthetized rat with an external object. We show that the chip learned the decoding task correctly, allowing the interfaced brain to control the object's trajectories robustly. Based on our demonstration, we propose that neuromorphic technology is mature enough for the development of BMI modules that are sufficiently low-power and compact, while being highly computationally powerful and adaptive.
Liao, Yuxi; Li, Hongbao; Zhang, Qiaosheng; Fan, Gong; Wang, Yiwen; Zheng, Xiaoxiang
2014-01-01
Decoding algorithm in motor Brain Machine Interfaces translates the neural signals to movement parameters. They usually assume the connection between the neural firings and movements to be stationary, which is not true according to the recent studies that observe the time-varying neuron tuning property. This property results from the neural plasticity and motor learning etc., which leads to the degeneration of the decoding performance when the model is fixed. To track the non-stationary neuron tuning during decoding, we propose a dual model approach based on Monte Carlo point process filtering method that enables the estimation also on the dynamic tuning parameters. When applied on both simulated neural signal and in vivo BMI data, the proposed adaptive method performs better than the one with static tuning parameters, which raises a promising way to design a long-term-performing model for Brain Machine Interfaces decoder.
Efficient Embedded Decoding of Neural Network Language Models in a Machine Translation System.
Zamora-Martinez, Francisco; Castro-Bleda, Maria Jose
2018-02-22
Neural Network Language Models (NNLMs) are a successful approach to Natural Language Processing tasks, such as Machine Translation. We introduce in this work a Statistical Machine Translation (SMT) system which fully integrates NNLMs in the decoding stage, breaking the traditional approach based on [Formula: see text]-best list rescoring. The neural net models (both language models (LMs) and translation models) are fully coupled in the decoding stage, allowing to more strongly influence the translation quality. Computational issues were solved by using a novel idea based on memorization and smoothing of the softmax constants to avoid their computation, which introduces a trade-off between LM quality and computational cost. These ideas were studied in a machine translation task with different combinations of neural networks used both as translation models and as target LMs, comparing phrase-based and [Formula: see text]-gram-based systems, showing that the integrated approach seems more promising for [Formula: see text]-gram-based systems, even with nonfull-quality NNLMs.
Blind Decoding of Multiple Description Codes over OFDM Systems via Sequential Monte Carlo
Directory of Open Access Journals (Sweden)
Guo Dong
2005-01-01
Full Text Available We consider the problem of transmitting a continuous source through an OFDM system. Multiple description scalar quantization (MDSQ is applied to the source signal, resulting in two correlated source descriptions. The two descriptions are then OFDM modulated and transmitted through two parallel frequency-selective fading channels. At the receiver, a blind turbo receiver is developed for joint OFDM demodulation and MDSQ decoding. Transformation of the extrinsic information of the two descriptions are exchanged between each other to improve system performance. A blind soft-input soft-output OFDM detector is developed, which is based on the techniques of importance sampling and resampling. Such a detector is capable of exchanging the so-called extrinsic information with the other component in the above turbo receiver, and successively improving the overall receiver performance. Finally, we also treat channel-coded systems, and a novel blind turbo receiver is developed for joint demodulation, channel decoding, and MDSQ source decoding.
Milekovic, Tomislav; Fischer, Jörg; Pistohl, Tobias; Ruescher, Johanna; Schulze-Bonhage, Andreas; Aertsen, Ad; Rickert, Jörn; Ball, Tonio; Mehring, Carsten
2012-08-01
A brain-machine interface (BMI) can be used to control movements of an artificial effector, e.g. movements of an arm prosthesis, by motor cortical signals that control the equivalent movements of the corresponding body part, e.g. arm movements. This approach has been successfully applied in monkeys and humans by accurately extracting parameters of movements from the spiking activity of multiple single neurons. We show that the same approach can be realized using brain activity measured directly from the surface of the human cortex using electrocorticography (ECoG). Five subjects, implanted with ECoG implants for the purpose of epilepsy assessment, took part in our study. Subjects used directionally dependent ECoG signals, recorded during active movements of a single arm, to control a computer cursor in one out of two directions. Significant BMI control was achieved in four out of five subjects with correct directional decoding in 69%-86% of the trials (75% on average). Our results demonstrate the feasibility of an online BMI using decoding of movement direction from human ECoG signals. Thus, to achieve such BMIs, ECoG signals might be used in conjunction with or as an alternative to intracortical neural signals.
Gallivan, Jason P.; Johnsrude, Ingrid S.; Randall Flanagan, J.
2016-01-01
Object-manipulation tasks (e.g., drinking from a cup) typically involve sequencing together a series of distinct motor acts (e.g., reaching toward, grasping, lifting, and transporting the cup) in order to accomplish some overarching goal (e.g., quenching thirst). Although several studies in humans have investigated the neural mechanisms supporting the planning of visually guided movements directed toward objects (such as reaching or pointing), only a handful have examined how manipulatory sequences of actions—those that occur after an object has been grasped—are planned and represented in the brain. Here, using event-related functional MRI and pattern decoding methods, we investigated the neural basis of real-object manipulation using a delayed-movement task in which participants first prepared and then executed different object-directed action sequences that varied either in their complexity or final spatial goals. Consistent with previous reports of preparatory brain activity in non-human primates, we found that activity patterns in several frontoparietal areas reliably predicted entire action sequences in advance of movement. Notably, we found that similar sequence-related information could also be decoded from pre-movement signals in object- and body-selective occipitotemporal cortex (OTC). These findings suggest that both frontoparietal and occipitotemporal circuits are engaged in transforming object-related information into complex, goal-directed movements. PMID:25576538
Massey, J. L.
1976-01-01
Virtually all previously-suggested rate 1/2 binary convolutional codes with KE = 24 are compared. Their distance properties are given; and their performance, both in computation and in error probability, with sequential decoding on the deep-space channel is determined by simulation. Recommendations are made both for the choice of a specific KE = 24 code as well as for codes to be included in future coding standards for the deep-space channel. A new result given in this report is a method for determining the statistical significance of error probability data when the error probability is so small that it is not feasible to perform enough decoding simulations to obtain more than a very small number of decoding errors.
Directory of Open Access Journals (Sweden)
Dario Cuevas Rivera
2015-10-01
Full Text Available The olfactory information that is received by the insect brain is encoded in the form of spatiotemporal patterns in the projection neurons of the antennal lobe. These dense and overlapping patterns are transformed into a sparse code in Kenyon cells in the mushroom body. Although it is clear that this sparse code is the basis for rapid categorization of odors, it is yet unclear how the sparse code in Kenyon cells is computed and what information it represents. Here we show that this computation can be modeled by sequential firing rate patterns using Lotka-Volterra equations and Bayesian online inference. This new model can be understood as an 'intelligent coincidence detector', which robustly and dynamically encodes the presence of specific odor features. We found that the model is able to qualitatively reproduce experimentally observed activity in both the projection neurons and the Kenyon cells. In particular, the model explains mechanistically how sparse activity in the Kenyon cells arises from the dense code in the projection neurons. The odor classification performance of the model proved to be robust against noise and time jitter in the observed input sequences. As in recent experimental results, we found that recognition of an odor happened very early during stimulus presentation in the model. Critically, by using the model, we found surprising but simple computational explanations for several experimental phenomena.
Design and validation of a real-time spiking-neural-network decoder for brain-machine interfaces
Dethier, Julie; Nuyujukian, Paul; Ryu, Stephen I.; Shenoy, Krishna V.; Boahen, Kwabena
2013-06-01
Objective. Cortically-controlled motor prostheses aim to restore functions lost to neurological disease and injury. Several proof of concept demonstrations have shown encouraging results, but barriers to clinical translation still remain. In particular, intracortical prostheses must satisfy stringent power dissipation constraints so as not to damage cortex. Approach. One possible solution is to use ultra-low power neuromorphic chips to decode neural signals for these intracortical implants. The first step is to explore in simulation the feasibility of translating decoding algorithms for brain-machine interface (BMI) applications into spiking neural networks (SNNs). Main results. Here we demonstrate the validity of the approach by implementing an existing Kalman-filter-based decoder in a simulated SNN using the Neural Engineering Framework (NEF), a general method for mapping control algorithms onto SNNs. To measure this system’s robustness and generalization, we tested it online in closed-loop BMI experiments with two rhesus monkeys. Across both monkeys, a Kalman filter implemented using a 2000-neuron SNN has comparable performance to that of a Kalman filter implemented using standard floating point techniques. Significance. These results demonstrate the tractability of SNN implementations of statistical signal processing algorithms on different monkeys and for several tasks, suggesting that a SNN decoder, implemented on a neuromorphic chip, may be a feasible computational platform for low-power fully-implanted prostheses. The validation of this closed-loop decoder system and the demonstration of its robustness and generalization hold promise for SNN implementations on an ultra-low power neuromorphic chip using the NEF.
Conditions for Model Matching of Switched Asynchronous Sequential Machines with Output Feedback
Jung–Min Yang
2016-01-01
Solvability of the model matching problem for input/output switched asynchronous sequential machines is discussed in this paper. The control objective is to determine the existence condition and design algorithm for a corrective controller that can match the stable-state behavior of the closed-loop system to that of a reference model. Switching operations and correction procedures are incorporated using output feedback so that the controlled switched machine can show the ...
International Nuclear Information System (INIS)
Taniguchi, Yuu; Okano, Shigetaka; Mochizuki, Masahito
2017-01-01
The excessive tensile residual stress generated by welding after surface machining may be an important factor to cause stress corrosion cracking (SCC) in nuclear power plants. Therefore we need to understand and control the residual stress distribution appropriately. In this study, residual stress distributions within surface machined layer generated by surface machining and sequential welding were evaluated by X-ray diffraction method. Depth directional distributions were also investigated by electrolytic polishing. In addition, to consider the effect of work hardened layer on the residual stress distributions, we also measured full width at half maximum (FWHM) obtained from X-ray diffraction. Testing material was a low-carbon austenitic stainless steel type SUS316L. Test specimens were prepared by surface machining with different cutting conditions. Then, bead-on-plate welding under the same welding condition was carried out on the test specimens with different surface machined layer. As a result, the tensile residual stress generated by surface machining increased with increasing cutting speed and showed nearly uniform distributions on the surface. Furthermore, the tensile residual stress drastically decreased with increasing measurement depth within surface machined layer. Then, the residual stress approached 0 MPa after the compressive value showed. FWHM also decreased drastically with increasing measurement depth and almost constant value from a certain depth, which was almost equal regardless of the machining condition, within surface machined layer in all specimens. After welding, the transverse distribution of the longitudinal residual stress varied in the area apart from the weld center according to machining conditions and had a maximum value in heat affected zone. The magnitude of the maximum residual stress was almost equal regardless of the machining condition and decreased with increasing measurement depth within surface machined layer. Finally, the
On Coding the States of Sequential Machines with the Use of Partition Pairs
DEFF Research Database (Denmark)
Zahle, Torben U.
1966-01-01
This article introduces a new technique of making state assignment for sequential machines. The technique is in line with the approach used by Hartmanis [l], Stearns and Hartmanis [3], and Curtis [4]. It parallels the work of Dolotta and McCluskey [7], although it was developed independently...
Application of full-face round by the sequential blasting machine in tunnel excavation
Energy Technology Data Exchange (ETDEWEB)
Cho, Y.D.; Park, B.K.; Lee, S.E.; Lim, H.U.
1995-12-31
Many methods and techniques have been developed to reduce ground vibrations. Some of them are an adoption of electric millisecond detonators with a sequential blasting machine and an improvement of initiating system with an adequate number of delay intervals. To reduce the level of ground vibration in tunnel excavation, the sequential blasting machine (S.B.M.) with decisecond detonators was adopted. A total of 134 blasts was recorded at various sites and the results were analyzed. The distances blast-to-structures were ranged from 20.3 to 42.0 meter, where charge weights were varied from 0.25 to 0.75kg per delay. It is proved that the sequential blasting in tunnel excavation is very effective to control ground vibration.
Ebersole, M. M.; Lecoq, P. E.
1968-01-01
This report presents a description of a computer program mechanized to perform the Paull and Unger process of simplifying incompletely specified sequential machines. An understanding of the process, as given in Ref. 3, is a prerequisite to the use of the techniques presented in this report. This process has specific application in the design of asynchronous digital machines and was used in the design of operational support equipment for the Mariner 1966 central computer and sequencer. A typical sequential machine design problem is presented to show where the Paull and Unger process has application. A description of the Paull and Unger process together with a description of the computer algorithms used to develop the program mechanization are presented. Several examples are used to clarify the Paull and Unger process and the computer algorithms. Program flow diagrams, program listings, and a program user operating procedures are included as appendixes.
Directory of Open Access Journals (Sweden)
Hisato eSugata
2014-08-01
Full Text Available Brain signals recorded from the primary motor cortex (M1 are known to serve a significant role in coding the information brain-machine interfaces (BMIs need to perform real and imagined movements, and also to form several functional networks with motor association areas. However, whether functional networks between M1 and other brain regions, such as these motor association areas, are related to performance of BMIs is unclear. To examine the relationship between functional connectivity and performance of BMIs, we analyzed the correlation coefficient between performance of neural decoding and functional connectivity over the whole brain using magnetoencephalography. Ten healthy participants were instructed to execute or imagine three simple right upper limb movements. To decode the movement type, we extracted 40 virtual channels in the left M1 via the beamforming approach, and used them as a decoding feature. In addition, seed-based functional connectivities of activities in the alpha band during real and imagined movements were calculated using imaginary coherence. Seed voxels were set as the same virtual channels in M1. After calculating the imaginary coherence in individuals, the correlation coefficient between decoding accuracy and strength of imaginary coherence was calculated over the whole brain. The significant correlations were distributed mainly to motor association areas for both real and imagined movements. These regions largely overlapped with brain regions that had significant connectivity to M1. Our results suggest that use of the strength of functional connectivity between M1 and motor association areas has the potential to improve the performance of BMIs to perform real and imagined movements.
Sachs, Nicholas A.; Ruiz-Torres, Ricardo; Perreault, Eric J.; Miller, Lee E.
2016-02-01
Objective. It is quite remarkable that brain machine interfaces (BMIs) can be used to control complex movements with fewer than 100 neurons. Success may be due in part to the limited range of dynamical conditions under which most BMIs are tested. Achieving high-quality control that spans these conditions with a single linear mapping will be more challenging. Even for simple reaching movements, existing BMIs must reduce the stochastic noise of neurons by averaging the control signals over time, instead of over the many neurons that normally control movement. This forces a compromise between a decoder with dynamics allowing rapid movement and one that allows postures to be maintained with little jitter. Our current work presents a method for addressing this compromise, which may also generalize to more highly varied dynamical situations, including movements with more greatly varying speed. Approach. We have developed a system that uses two independent Wiener filters as individual components in a single decoder, one optimized for movement, and the other for postural control. We computed an LDA classifier using the same neural inputs. The decoder combined the outputs of the two filters in proportion to the likelihood assigned by the classifier to each state. Main results. We have performed online experiments with two monkeys using this neural-classifier, dual-state decoder, comparing it to a standard, single-state decoder as well as to a dual-state decoder that switched states automatically based on the cursor’s proximity to a target. The performance of both monkeys using the classifier decoder was markedly better than that of the single-state decoder and comparable to the proximity decoder. Significance. We have demonstrated a novel strategy for dealing with the need to make rapid movements while also maintaining precise cursor control when approaching and stabilizing within targets. Further gains can undoubtedly be realized by optimizing the performance of the
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.
Mitsunaga, Erin M
2006-05-01
During the Korean War, International Business Machines (IBM) punch cards were created for every individual involved in military combat. Each card contained all pertinent personal information about the individual and was utilized to keep track of all soldiers involved. However, at present, all of the information known about these punch cards reveals only their format and their significance; there is little to no information on how these cards were created or how to interpret the information contained without the aid of the computer system used during the war. Today, it is believed there is no one available to explain this computerized system, nor do the original computers exist. This decode strategy is the result of an attempt to decipher the information on these cards through the use of all available medical and dental records for each individual examined. By cross-referencing the relevant personal information with the known format of the cards, a basic guess-and-check method was utilized. After examining hundreds of IBM punch cards, however, it has become clear that the punch card method of recording information was not infallible. In some cases, there are gaps of information on cards where there are data recorded on personal records; in others, information is punched incorrectly onto the cards, perhaps as the result of a transcription error. Taken all together, it is clear that the information contained on each individual's card should be taken solely as another form of personal documentation.
Directory of Open Access Journals (Sweden)
Yanjiao Li
2017-08-01
Full Text Available Gas utilization ratio (GUR is an important indicator used to measure the operating status and energy consumption of blast furnaces (BFs. In this paper, we present a soft-sensor approach, i.e., a novel online sequential extreme learning machine (OS-ELM named DU-OS-ELM, to establish a data-driven model for GUR prediction. In DU-OS-ELM, firstly, the old collected data are discarded gradually and the newly acquired data are given more attention through a novel dynamic forgetting factor (DFF, depending on the estimation errors to enhance the dynamic tracking ability. Furthermore, we develop an updated selection strategy (USS to judge whether the model needs to be updated with the newly coming data, so that the proposed approach is more in line with the actual production situation. Then, the convergence analysis of the proposed DU-OS-ELM is presented to ensure the estimation of output weight converge to the true value with the new data arriving. Meanwhile, the proposed DU-OS-ELM is applied to build a soft-sensor model to predict GUR. Experimental results demonstrate that the proposed DU-OS-ELM obtains better generalization performance and higher prediction accuracy compared with a number of existing related approaches using the real production data from a BF and the created GUR prediction model can provide an effective guidance for further optimization operation.
Li, Yanjiao; Zhang, Sen; Yin, Yixin; Xiao, Wendong; Zhang, Jie
2017-08-10
Gas utilization ratio (GUR) is an important indicator used to measure the operating status and energy consumption of blast furnaces (BFs). In this paper, we present a soft-sensor approach, i.e., a novel online sequential extreme learning machine (OS-ELM) named DU-OS-ELM, to establish a data-driven model for GUR prediction. In DU-OS-ELM, firstly, the old collected data are discarded gradually and the newly acquired data are given more attention through a novel dynamic forgetting factor (DFF), depending on the estimation errors to enhance the dynamic tracking ability. Furthermore, we develop an updated selection strategy (USS) to judge whether the model needs to be updated with the newly coming data, so that the proposed approach is more in line with the actual production situation. Then, the convergence analysis of the proposed DU-OS-ELM is presented to ensure the estimation of output weight converge to the true value with the new data arriving. Meanwhile, the proposed DU-OS-ELM is applied to build a soft-sensor model to predict GUR. Experimental results demonstrate that the proposed DU-OS-ELM obtains better generalization performance and higher prediction accuracy compared with a number of existing related approaches using the real production data from a BF and the created GUR prediction model can provide an effective guidance for further optimization operation.
Lima, Aranildo R.; Hsieh, William W.; Cannon, Alex J.
2017-12-01
In situations where new data arrive continually, online learning algorithms are computationally much less costly than batch learning ones in maintaining the model up-to-date. The extreme learning machine (ELM), a single hidden layer artificial neural network with random weights in the hidden layer, is solved by linear least squares, and has an online learning version, the online sequential ELM (OSELM). As more data become available during online learning, information on the longer time scale becomes available, so ideally the model complexity should be allowed to change, but the number of hidden nodes (HN) remains fixed in OSELM. A variable complexity VC-OSELM algorithm is proposed to dynamically add or remove HN in the OSELM, allowing the model complexity to vary automatically as online learning proceeds. The performance of VC-OSELM was compared with OSELM in daily streamflow predictions at two hydrological stations in British Columbia, Canada, with VC-OSELM significantly outperforming OSELM in mean absolute error, root mean squared error and Nash-Sutcliffe efficiency at both stations.
Neural Decoder for Topological Codes
Torlai, Giacomo; Melko, Roger G.
2017-07-01
We present an algorithm for error correction in topological codes that exploits modern machine learning techniques. Our decoder is constructed from a stochastic neural network called a Boltzmann machine, of the type extensively used in deep learning. We provide a general prescription for the training of the network and a decoding strategy that is applicable to a wide variety of stabilizer codes with very little specialization. We demonstrate the neural decoder numerically on the well-known two-dimensional toric code with phase-flip errors.
Model Predictive Engine Air-Ratio Control Using Online Sequential Relevance Vector Machine
Directory of Open Access Journals (Sweden)
Hang-cheong Wong
2012-01-01
Full Text Available Engine power, brake-specific fuel consumption, and emissions relate closely to air ratio (i.e., lambda among all the engine variables. An accurate and adaptive model for lambda prediction is essential to effective lambda control for long term. This paper utilizes an emerging technique, relevance vector machine (RVM, to build a reliable time-dependent lambda model which can be continually updated whenever a sample is added to, or removed from, the estimated lambda model. The paper also presents a new model predictive control (MPC algorithm for air-ratio regulation based on RVM. This study shows that the accuracy, training, and updating time of the RVM model are superior to the latest modelling methods, such as diagonal recurrent neural network (DRNN and decremental least-squares support vector machine (DLSSVM. Moreover, the control algorithm has been implemented on a real car to test. Experimental results reveal that the control performance of the proposed relevance vector machine model predictive controller (RVMMPC is also superior to DRNNMPC, support vector machine-based MPC, and conventional proportional-integral (PI controller in production cars. Therefore, the proposed RVMMPC is a promising scheme to replace conventional PI controller for engine air-ratio control.
International Nuclear Information System (INIS)
Chen Hanying; Gao Puzhen; Tan Sichao; Tang Jiguo; Hou Xiaofan; Xu Huiqiang; Wu Xiangcheng
2015-01-01
The coupling of multiple thermal-hydraulic parameters can result in complex flow instability in natural circulation system under rolling motion. A real-time thermal-hydraulic condition prediction is helpful to the operation of systems in such condition. A single hidden layer feedforward neural networks algorithm named extreme learning machine (ELM) is considered as suitable method for this application because of its extremely fast training time, good accuracy and simplicity. However, traditional ELM assumes that all the training data are ready before the training process, while the training data is received sequentially in practical forecasting of flowrate. Therefore, this paper proposes a forecasting method for flowrate under rolling motion based on on-line sequential ELM (OS-ELM), which can learn the data one by one or chunk-by-chunk. The experiment results show that the OS-ELM method can achieve a better forecasting performance than basic ELM method and still keep the advantage of fast training and simplicity. (author)
A real-time MPEG software decoder using a portable message-passing library
Energy Technology Data Exchange (ETDEWEB)
Kwong, Man Kam; Tang, P.T. Peter; Lin, Biquan
1995-12-31
We present a real-time MPEG software decoder that uses message-passing libraries such as MPL, p4 and MPI. The parallel MPEG decoder currently runs on the IBM SP system but can be easil ported to other parallel machines. This paper discusses our parallel MPEG decoding algorithm as well as the parallel programming environment under which it uses. Several technical issues are discussed, including balancing of decoding speed, memory limitation, 1/0 capacities, and optimization of MPEG decoding components. This project shows that a real-time portable software MPEG decoder is feasible in a general-purpose parallel machine.
Low-Power Bitstream-Residual Decoder for H.264/AVC Baseline Profile Decoding
Directory of Open Access Journals (Sweden)
Xu Ke
2009-01-01
Full Text Available Abstract We present the design and VLSI implementation of a novel low-power bitstream-residual decoder for H.264/AVC baseline profile. It comprises a syntax parser, a parameter decoder, and an Inverse Quantization Inverse Transform (IQIT decoder. The syntax parser detects and decodes each incoming codeword in the bitstream under the control of a hierarchical Finite State Machine (FSM; the IQIT decoder performs inverse transform and quantization with pipelining and parallelism. Various power reduction techniques, such as data-driven based on statistic results, nonuniform partition, precomputation, guarded evaluation, hierarchical FSM decomposition, TAG method, zero-block skipping, and clock gating , are adopted and integrated throughout the bitstream-residual decoder. With innovative architecture, the proposed design is able to decode QCIF video sequences of 30 fps at a clock rate as low as 1.5 MHz. A prototype H.264/AVC baseline decoding chip utilizing the proposed decoder is fabricated in UMC 0.18 m 1P6M CMOS technology. The proposed design is measured under 1 V 1.8 V supply with 0.1 V step. It dissipates 76 W at 1 V and 253 W at 1.8 V.
Directory of Open Access Journals (Sweden)
Pak Kin Wong
2014-01-01
Full Text Available Most adaptive neural control schemes are based on stochastic gradient-descent backpropagation (SGBP, which suffers from local minima problem. Although the recently proposed regularized online sequential-extreme learning machine (ReOS-ELM can overcome this issue, it requires a batch of representative initial training data to construct a base model before online learning. The initial data is usually difficult to collect in adaptive control applications. Therefore, this paper proposes an improved version of ReOS-ELM, entitled fully online sequential-extreme learning machine (FOS-ELM. While retaining the advantages of ReOS-ELM, FOS-ELM discards the initial training phase, and hence becomes suitable for adaptive control applications. To demonstrate its effectiveness, FOS-ELM was applied to the adaptive control of engine air-fuel ratio based on a simulated engine model. Besides, controller parameters were also analyzed, in which it is found that large hidden node number with small regularization parameter leads to the best performance. A comparison among FOS-ELM and SGBP was also conducted. The result indicates that FOS-ELM achieves better tracking and convergence performance than SGBP, since FOS-ELM tends to learn the unknown engine model globally whereas SGBP tends to “forget” what it has learnt. This implies that FOS-ELM is more preferable for adaptive control applications.
Decoding subjective mental states from fMRI activity patterns
International Nuclear Information System (INIS)
Tamaki, Masako; Kamitani, Yukiyasu
2011-01-01
In recent years, functional magnetic resonance imaging (fMRI) decoding has emerged as a powerful tool to read out detailed stimulus features from multi-voxel brain activity patterns. Moreover, the method has been extended to perform a primitive form of 'mind-reading,' by applying a decoder 'objectively' trained using stimulus features to more 'subjective' conditions. In this paper, we first introduce basic procedures for fMRI decoding based on machine learning techniques. Second, we discuss the source of information used for decoding, in particular, the possibility of extracting information from subvoxel neural structures. We next introduce two experimental designs for decoding subjective mental states: the 'objective-to-subjective design' and the 'subjective-to-subjective design.' Then, we illustrate recent studies on the decoding of a variety of mental states, such as, attention, awareness, decision making, memory, and mental imagery. Finally, we discuss the challenges and new directions of fMRI decoding. (author)
Belief propagation decoding of quantum channels by passing quantum messages
International Nuclear Information System (INIS)
Renes, Joseph M
2017-01-01
The belief propagation (BP) algorithm is a powerful tool in a wide range of disciplines from statistical physics to machine learning to computational biology, and is ubiquitous in decoding classical error-correcting codes. The algorithm works by passing messages between nodes of the factor graph associated with the code and enables efficient decoding of the channel, in some cases even up to the Shannon capacity. Here we construct the first BP algorithm which passes quantum messages on the factor graph and is capable of decoding the classical–quantum channel with pure state outputs. This gives explicit decoding circuits whose number of gates is quadratic in the code length. We also show that this decoder can be modified to work with polar codes for the pure state channel and as part of a decoder for transmitting quantum information over the amplitude damping channel. These represent the first explicit capacity-achieving decoders for non-Pauli channels. (fast track communication)
Belief propagation decoding of quantum channels by passing quantum messages
Renes, Joseph M.
2017-07-01
The belief propagation (BP) algorithm is a powerful tool in a wide range of disciplines from statistical physics to machine learning to computational biology, and is ubiquitous in decoding classical error-correcting codes. The algorithm works by passing messages between nodes of the factor graph associated with the code and enables efficient decoding of the channel, in some cases even up to the Shannon capacity. Here we construct the first BP algorithm which passes quantum messages on the factor graph and is capable of decoding the classical-quantum channel with pure state outputs. This gives explicit decoding circuits whose number of gates is quadratic in the code length. We also show that this decoder can be modified to work with polar codes for the pure state channel and as part of a decoder for transmitting quantum information over the amplitude damping channel. These represent the first explicit capacity-achieving decoders for non-Pauli channels.
DEFF Research Database (Denmark)
Justesen, Jørn; Høholdt, Tom; Hjaltason, Johan
2005-01-01
We analyze the relation between iterative decoding and the extended parity check matrix. By considering a modified version of bit flipping, which produces a list of decoded words, we derive several relations between decodable error patterns and the parameters of the code. By developing a tree...... of codewords at minimal distance from the received vector, we also obtain new information about the code....
Anomaly Detection in Gas Turbine Fuel Systems Using a Sequential Symbolic Method
Directory of Open Access Journals (Sweden)
Fei Li
2017-05-01
Full Text Available Anomaly detection plays a significant role in helping gas turbines run reliably and economically. Considering the collective anomalous data and both sensitivity and robustness of the anomaly detection model, a sequential symbolic anomaly detection method is proposed and applied to the gas turbine fuel system. A structural Finite State Machine is used to evaluate posterior probabilities of observing symbolic sequences and the most probable state sequences they may locate. Hence an estimation-based model and a decoding-based model are used to identify anomalies in two different ways. Experimental results indicate that both models have both ideal performance overall, but the estimation-based model has a strong robustness ability, whereas the decoding-based model has a strong accuracy ability, particularly in a certain range of sequence lengths. Therefore, the proposed method can facilitate well existing symbolic dynamic analysis- based anomaly detection methods, especially in the gas turbine domain.
International Nuclear Information System (INIS)
Dobler, Barbara; Pohl, Fabian; Bogner, Ludwig; Koelbl, Oliver
2007-01-01
To evaluate the effects of direct machine parameter optimization in the treatment planning of intensity-modulated radiation therapy (IMRT) for hypopharyngeal cancer as compared to subsequent leaf sequencing in Oncentra Masterplan v1.5. For 10 hypopharyngeal cancer patients IMRT plans were generated in Oncentra Masterplan v1.5 (Nucletron BV, Veenendal, the Netherlands) for a Siemens Primus linear accelerator. For optimization the dose volume objectives (DVO) for the planning target volume (PTV) were set to 53 Gy minimum dose and 59 Gy maximum dose, in order to reach a dose of 56 Gy to the average of the PTV. For the parotids a median dose of 22 Gy was allowed and for the spinal cord a maximum dose of 35 Gy. The maximum DVO to the external contour of the patient was set to 59 Gy. The treatment plans were optimized with the direct machine parameter optimization ('Direct Step & Shoot', DSS, Raysearch Laboratories, Sweden) newly implemented in Masterplan v1.5 and the fluence modulation technique ('Intensity Modulation', IM) which was available in previous versions of Masterplan already. The two techniques were compared with regard to compliance to the DVO, plan quality, and number of monitor units (MU) required per fraction dose. The plans optimized with the DSS technique met the DVO for the PTV significantly better than the plans optimized with IM (p = 0.007 for the min DVO and p < 0.0005 for the max DVO). No significant difference could be observed for compliance to the DVO for the organs at risk (OAR) (p > 0.05). Plan quality, target coverage and dose homogeneity inside the PTV were superior for the plans optimized with DSS for similar dose to the spinal cord and lower dose to the normal tissue. The mean dose to the parotids was lower for the plans optimized with IM. Treatment plan efficiency was higher for the DSS plans with (901 ± 160) MU compared to (1151 ± 157) MU for IM (p-value < 0.05). Renormalization of the IM plans to the mean of the
Lyles, Courtney Rees; Godbehere, Andrew; Le, Gem; El Ghaoui, Laurent; Sarkar, Urmimala
2016-06-10
It is difficult to synthesize the vast amount of textual data available from social media websites. Capturing real-world discussions via social media could provide insights into individuals' opinions and the decision-making process. We conducted a sequential mixed methods study to determine the utility of sparse machine learning techniques in summarizing Twitter dialogues. We chose a narrowly defined topic for this approach: cervical cancer discussions over a 6-month time period surrounding a change in Pap smear screening guidelines. We applied statistical methodologies, known as sparse machine learning algorithms, to summarize Twitter messages about cervical cancer before and after the 2012 change in Pap smear screening guidelines by the US Preventive Services Task Force (USPSTF). All messages containing the search terms "cervical cancer," "Pap smear," and "Pap test" were analyzed during: (1) January 1-March 13, 2012, and (2) March 14-June 30, 2012. Topic modeling was used to discern the most common topics from each time period, and determine the singular value criterion for each topic. The results were then qualitatively coded from top 10 relevant topics to determine the efficiency of clustering method in grouping distinct ideas, and how the discussion differed before vs. after the change in guidelines . This machine learning method was effective in grouping the relevant discussion topics about cervical cancer during the respective time periods (~20% overall irrelevant content in both time periods). Qualitative analysis determined that a significant portion of the top discussion topics in the second time period directly reflected the USPSTF guideline change (eg, "New Screening Guidelines for Cervical Cancer"), and many topics in both time periods were addressing basic screening promotion and education (eg, "It is Cervical Cancer Awareness Month! Click the link to see where you can receive a free or low cost Pap test.") It was demonstrated that machine learning
Haque, M Muksitul; Holder, Lawrence B; Skinner, Michael K
2015-01-01
Environmentally induced epigenetic transgenerational inheritance of disease and phenotypic variation involves germline transmitted epimutations. The primary epimutations identified involve altered differential DNA methylation regions (DMRs). Different environmental toxicants have been shown to promote exposure (i.e., toxicant) specific signatures of germline epimutations. Analysis of genomic features associated with these epimutations identified low-density CpG regions (machine learning computational approach to predict all potential epimutations in the genome. A number of previously identified sperm epimutations were used as training sets. A novel machine learning approach using a sequential combination of Active Learning and Imbalance Class Learner analysis was developed. The transgenerational sperm epimutation analysis identified approximately 50K individual sites with a 1 kb mean size and 3,233 regions that had a minimum of three adjacent sites with a mean size of 3.5 kb. A select number of the most relevant genomic features were identified with the low density CpG deserts being a critical genomic feature of the features selected. A similar independent analysis with transgenerational somatic cell epimutation training sets identified a smaller number of 1,503 regions of genome-wide predicted sites and differences in genomic feature contributions. The predicted genome-wide germline (sperm) epimutations were found to be distinct from the predicted somatic cell epimutations. Validation of the genome-wide germline predicted sites used two recently identified transgenerational sperm epimutation signature sets from the pesticides dichlorodiphenyltrichloroethane (DDT) and methoxychlor (MXC) exposure lineage F3 generation. Analysis of this positive validation data set showed a 100% prediction accuracy for all the DDT-MXC sperm epimutations. Observations further elucidate the genomic features associated with transgenerational germline epimutations and identify a genome
Liu, Jie; Cao, Ping; Han, Dongya
2016-04-01
The influence of confining stress on rock breakage by a tunnel boring machine cutter was investigated by conducting sequential indentation tests in a biaxial state. Combined with morphology measurements of breaking grooves and an analysis of surface and internal crack propagation between nicks, the effects of maximum confining stress and minimum stress on indentation efficiency, crack propagation and chip formation were investigated. Indentation tests and morphology measurements show that increasing a maximum confining stress will result in increased consumed energy in indentations, enlarged groove volumes and promoted indentation efficiency when the corresponding minimum confining stress is fixed. The energy consumed in indentations will increase with increase in minimum confining stress, however, because of the decreased groove volumes as the minimum confining stress increases, the efficiency will decrease. Observations of surface crack propagation show that more intensive fractures will be induced as the maximum confining stress increases, whereas the opposite occurs for an increase of minimum confining stress. An observation of the middle section, cracks and chips shows that as the maximum confining stress increases, chips tend to form in deeper parts when the minimum confining stress is fixed, whereas they tend to formed in shallower parts as the minimum confining stress increases when the maximum confining stress is fixed.
Decoding of finger trajectory from ECoG using deep learning
Xie, Ziqian; Schwartz, Odelia; Prasad, Abhishek
2018-06-01
Objective. Conventional decoding pipeline for brain-machine interfaces (BMIs) consists of chained different stages of feature extraction, time-frequency analysis and statistical learning models. Each of these stages uses a different algorithm trained in a sequential manner, which makes it difficult to make the whole system adaptive. The goal was to create an adaptive online system with a single objective function and a single learning algorithm so that the whole system can be trained in parallel to increase the decoding performance. Here, we used deep neural networks consisting of convolutional neural networks (CNN) and a special kind of recurrent neural network (RNN) called long short term memory (LSTM) to address these needs. Approach. We used electrocorticography (ECoG) data collected by Kubanek et al. The task consisted of individual finger flexions upon a visual cue. Our model combined a hierarchical feature extractor CNN and a RNN that was able to process sequential data and recognize temporal dynamics in the neural data. CNN was used as the feature extractor and LSTM was used as the regression algorithm to capture the temporal dynamics of the signal. Main results. We predicted the finger trajectory using ECoG signals and compared results for the least angle regression (LARS), CNN-LSTM, random forest, LSTM model (LSTM_HC, for using hard-coded features) and a decoding pipeline consisting of band-pass filtering, energy extraction, feature selection and linear regression. The results showed that the deep learning models performed better than the commonly used linear model. The deep learning models not only gave smoother and more realistic trajectories but also learned the transition between movement and rest state. Significance. This study demonstrated a decoding network for BMI that involved a convolutional and recurrent neural network model. It integrated the feature extraction pipeline into the convolution and pooling layer and used LSTM layer to capture the
Directory of Open Access Journals (Sweden)
M Muksitul Haque
Full Text Available Environmentally induced epigenetic transgenerational inheritance of disease and phenotypic variation involves germline transmitted epimutations. The primary epimutations identified involve altered differential DNA methylation regions (DMRs. Different environmental toxicants have been shown to promote exposure (i.e., toxicant specific signatures of germline epimutations. Analysis of genomic features associated with these epimutations identified low-density CpG regions (<3 CpG / 100bp termed CpG deserts and a number of unique DNA sequence motifs. The rat genome was annotated for these and additional relevant features. The objective of the current study was to use a machine learning computational approach to predict all potential epimutations in the genome. A number of previously identified sperm epimutations were used as training sets. A novel machine learning approach using a sequential combination of Active Learning and Imbalance Class Learner analysis was developed. The transgenerational sperm epimutation analysis identified approximately 50K individual sites with a 1 kb mean size and 3,233 regions that had a minimum of three adjacent sites with a mean size of 3.5 kb. A select number of the most relevant genomic features were identified with the low density CpG deserts being a critical genomic feature of the features selected. A similar independent analysis with transgenerational somatic cell epimutation training sets identified a smaller number of 1,503 regions of genome-wide predicted sites and differences in genomic feature contributions. The predicted genome-wide germline (sperm epimutations were found to be distinct from the predicted somatic cell epimutations. Validation of the genome-wide germline predicted sites used two recently identified transgenerational sperm epimutation signature sets from the pesticides dichlorodiphenyltrichloroethane (DDT and methoxychlor (MXC exposure lineage F3 generation. Analysis of this positive validation
DEFF Research Database (Denmark)
Martins, Bo; Forchhammer, Søren
1999-01-01
MPEG-2 video decoding is examined. A unified approach to quality improvement, chrominance upsampling, de-interlacing and superresolution is presented. The information over several frames is combined as part of the processing....
Visual perception as retrospective Bayesian decoding from high- to low-level features.
Ding, Stephanie; Cueva, Christopher J; Tsodyks, Misha; Qian, Ning
2017-10-24
When a stimulus is presented, its encoding is known to progress from low- to high-level features. How these features are decoded to produce perception is less clear, and most models assume that decoding follows the same low- to high-level hierarchy of encoding. There are also theories arguing for global precedence, reversed hierarchy, or bidirectional processing, but they are descriptive without quantitative comparison with human perception. Moreover, observers often inspect different parts of a scene sequentially to form overall perception, suggesting that perceptual decoding requires working memory, yet few models consider how working-memory properties may affect decoding hierarchy. We probed decoding hierarchy by comparing absolute judgments of single orientations and relative/ordinal judgments between two sequentially presented orientations. We found that lower-level, absolute judgments failed to account for higher-level, relative/ordinal judgments. However, when ordinal judgment was used to retrospectively decode memory representations of absolute orientations, striking aspects of absolute judgments, including the correlation and forward/backward aftereffects between two reported orientations in a trial, were explained. We propose that the brain prioritizes decoding of higher-level features because they are more behaviorally relevant, and more invariant and categorical, and thus easier to specify and maintain in noisy working memory, and that more reliable higher-level decoding constrains less reliable lower-level decoding. Published under the PNAS license.
Decoding communities in networks
Radicchi, Filippo
2018-02-01
According to a recent information-theoretical proposal, the problem of defining and identifying communities in networks can be interpreted as a classical communication task over a noisy channel: memberships of nodes are information bits erased by the channel, edges and nonedges in the network are parity bits introduced by the encoder but degraded through the channel, and a community identification algorithm is a decoder. The interpretation is perfectly equivalent to the one at the basis of well-known statistical inference algorithms for community detection. The only difference in the interpretation is that a noisy channel replaces a stochastic network model. However, the different perspective gives the opportunity to take advantage of the rich set of tools of coding theory to generate novel insights on the problem of community detection. In this paper, we illustrate two main applications of standard coding-theoretical methods to community detection. First, we leverage a state-of-the-art decoding technique to generate a family of quasioptimal community detection algorithms. Second and more important, we show that the Shannon's noisy-channel coding theorem can be invoked to establish a lower bound, here named as decodability bound, for the maximum amount of noise tolerable by an ideal decoder to achieve perfect detection of communities. When computed for well-established synthetic benchmarks, the decodability bound explains accurately the performance achieved by the best community detection algorithms existing on the market, telling us that only little room for their improvement is still potentially left.
Decoding communities in networks.
Radicchi, Filippo
2018-02-01
According to a recent information-theoretical proposal, the problem of defining and identifying communities in networks can be interpreted as a classical communication task over a noisy channel: memberships of nodes are information bits erased by the channel, edges and nonedges in the network are parity bits introduced by the encoder but degraded through the channel, and a community identification algorithm is a decoder. The interpretation is perfectly equivalent to the one at the basis of well-known statistical inference algorithms for community detection. The only difference in the interpretation is that a noisy channel replaces a stochastic network model. However, the different perspective gives the opportunity to take advantage of the rich set of tools of coding theory to generate novel insights on the problem of community detection. In this paper, we illustrate two main applications of standard coding-theoretical methods to community detection. First, we leverage a state-of-the-art decoding technique to generate a family of quasioptimal community detection algorithms. Second and more important, we show that the Shannon's noisy-channel coding theorem can be invoked to establish a lower bound, here named as decodability bound, for the maximum amount of noise tolerable by an ideal decoder to achieve perfect detection of communities. When computed for well-established synthetic benchmarks, the decodability bound explains accurately the performance achieved by the best community detection algorithms existing on the market, telling us that only little room for their improvement is still potentially left.
Reading Remediation Based on Sequential and Simultaneous Processing.
Gunnison, Judy; And Others
1982-01-01
The theory postulating a dichotomy between sequential and simultaneous processing is reviewed and its implications for remediating reading problems are reviewed. Research is cited on sequential-simultaneous processing for early and advanced reading. A list of remedial strategies based on the processing dichotomy addresses decoding and lexical…
Adaptive decoding of convolutional codes
Directory of Open Access Journals (Sweden)
K. Hueske
2007-06-01
Full Text Available Convolutional codes, which are frequently used as error correction codes in digital transmission systems, are generally decoded using the Viterbi Decoder. On the one hand the Viterbi Decoder is an optimum maximum likelihood decoder, i.e. the most probable transmitted code sequence is obtained. On the other hand the mathematical complexity of the algorithm only depends on the used code, not on the number of transmission errors. To reduce the complexity of the decoding process for good transmission conditions, an alternative syndrome based decoder is presented. The reduction of complexity is realized by two different approaches, the syndrome zero sequence deactivation and the path metric equalization. The two approaches enable an easy adaptation of the decoding complexity for different transmission conditions, which results in a trade-off between decoding complexity and error correction performance.
Adaptive decoding of convolutional codes
Hueske, K.; Geldmacher, J.; Götze, J.
2007-06-01
Convolutional codes, which are frequently used as error correction codes in digital transmission systems, are generally decoded using the Viterbi Decoder. On the one hand the Viterbi Decoder is an optimum maximum likelihood decoder, i.e. the most probable transmitted code sequence is obtained. On the other hand the mathematical complexity of the algorithm only depends on the used code, not on the number of transmission errors. To reduce the complexity of the decoding process for good transmission conditions, an alternative syndrome based decoder is presented. The reduction of complexity is realized by two different approaches, the syndrome zero sequence deactivation and the path metric equalization. The two approaches enable an easy adaptation of the decoding complexity for different transmission conditions, which results in a trade-off between decoding complexity and error correction performance.
DEFF Research Database (Denmark)
Nielsen, Rasmus Refslund
2002-01-01
This paper describes an efficient decoding method for a recent construction of good linear codes as well as an extension to the construction. Furthermore, asymptotic properties and list decoding of the codes are discussed.......This paper describes an efficient decoding method for a recent construction of good linear codes as well as an extension to the construction. Furthermore, asymptotic properties and list decoding of the codes are discussed....
Joint Estimation and Decoding of Space-Time Trellis Codes
Directory of Open Access Journals (Sweden)
Zhang Jianqiu
2002-01-01
Full Text Available We explore the possibility of using an emerging tool in statistical signal processing, sequential importance sampling (SIS, for joint estimation and decoding of space-time trellis codes (STTC. First, we provide background on SIS, and then we discuss its application to space-time trellis code (STTC systems. It is shown through simulations that SIS is suitable for joint estimation and decoding of STTC with time-varying flat-fading channels when phase ambiguity is avoided. We used a design criterion for STTCs and temporally correlated channels that combats phase ambiguity without pilot signaling. We have shown by simulations that the design is valid.
Neural decoding of visual imagery during sleep.
Horikawa, T; Tamaki, M; Miyawaki, Y; Kamitani, Y
2013-05-03
Visual imagery during sleep has long been a topic of persistent speculation, but its private nature has hampered objective analysis. Here we present a neural decoding approach in which machine-learning models predict the contents of visual imagery during the sleep-onset period, given measured brain activity, by discovering links between human functional magnetic resonance imaging patterns and verbal reports with the assistance of lexical and image databases. Decoding models trained on stimulus-induced brain activity in visual cortical areas showed accurate classification, detection, and identification of contents. Our findings demonstrate that specific visual experience during sleep is represented by brain activity patterns shared by stimulus perception, providing a means to uncover subjective contents of dreaming using objective neural measurement.
Efficient universal computing architectures for decoding neural activity.
Directory of Open Access Journals (Sweden)
Benjamin I Rapoport
Full Text Available The ability to decode neural activity into meaningful control signals for prosthetic devices is critical to the development of clinically useful brain- machine interfaces (BMIs. Such systems require input from tens to hundreds of brain-implanted recording electrodes in order to deliver robust and accurate performance; in serving that primary function they should also minimize power dissipation in order to avoid damaging neural tissue; and they should transmit data wirelessly in order to minimize the risk of infection associated with chronic, transcutaneous implants. Electronic architectures for brain- machine interfaces must therefore minimize size and power consumption, while maximizing the ability to compress data to be transmitted over limited-bandwidth wireless channels. Here we present a system of extremely low computational complexity, designed for real-time decoding of neural signals, and suited for highly scalable implantable systems. Our programmable architecture is an explicit implementation of a universal computing machine emulating the dynamics of a network of integrate-and-fire neurons; it requires no arithmetic operations except for counting, and decodes neural signals using only computationally inexpensive logic operations. The simplicity of this architecture does not compromise its ability to compress raw neural data by factors greater than [Formula: see text]. We describe a set of decoding algorithms based on this computational architecture, one designed to operate within an implanted system, minimizing its power consumption and data transmission bandwidth; and a complementary set of algorithms for learning, programming the decoder, and postprocessing the decoded output, designed to operate in an external, nonimplanted unit. The implementation of the implantable portion is estimated to require fewer than 5000 operations per second. A proof-of-concept, 32-channel field-programmable gate array (FPGA implementation of this portion
Indian Academy of Sciences (India)
Shannon limit of the channel. Among the earliest discovered codes that approach the. Shannon limit were the low density parity check (LDPC) codes. The term low density arises from the property of the parity check matrix defining the code. We will now define this matrix and the role that it plays in decoding. 2. Linear Codes.
Tracking Perceptual and Memory Decisions by Decoding Brain Activity
van Vugt, Marieke; Brandt, Armin; Schulze-Bonhage, Andreas
2017-01-01
Decision making is thought to involve a process of evidence accumulation, modelled as a drifting diffusion process. This modeling framework suggests that all single-stage decisions involve a similar evidence accumulation process. In this paper we use decoding by machine learning classifiers on
On minimizing the maximum broadcast decoding delay for instantly decodable network coding
Douik, Ahmed S.; Sorour, Sameh; Alouini, Mohamed-Slim; Ai-Naffouri, Tareq Y.
2014-01-01
In this paper, we consider the problem of minimizing the maximum broadcast decoding delay experienced by all the receivers of generalized instantly decodable network coding (IDNC). Unlike the sum decoding delay, the maximum decoding delay as a
An Optimized Three-Level Design of Decoder Based on Nanoscale Quantum-Dot Cellular Automata
Seyedi, Saeid; Navimipour, Nima Jafari
2018-03-01
Quantum-dot Cellular Automata (QCA) has been potentially considered as a supersede to Complementary Metal-Oxide-Semiconductor (CMOS) because of its inherent advantages. Many QCA-based logic circuits with smaller feature size, improved operating frequency, and lower power consumption than CMOS have been offered. This technology works based on electron relations inside quantum-dots. Due to the importance of designing an optimized decoder in any digital circuit, in this paper, we design, implement and simulate a new 2-to-4 decoder based on QCA with low delay, area, and complexity. The logic functionality of the 2-to-4 decoder is verified using the QCADesigner tool. The results have shown that the proposed QCA-based decoder has high performance in terms of a number of cells, covered area, and time delay. Due to the lower clock pulse frequency, the proposed 2-to-4 decoder is helpful for building QCA-based sequential digital circuits with high performance.
CERN. Geneva. Audiovisual Unit; Antonerakis, S E
2002-01-01
Decoding the Human genome is a very up-to-date topic, raising several questions besides purely scientific, in view of the two competing teams (public and private), the ethics of using the results, and the fact that the project went apparently faster and easier than expected. The lecture series will address the following chapters: Scientific basis and challenges. Ethical and social aspects of genomics.
Kernel Temporal Differences for Neural Decoding
Bae, Jihye; Sanchez Giraldo, Luis G.; Pohlmeyer, Eric A.; Francis, Joseph T.; Sanchez, Justin C.; Príncipe, José C.
2015-01-01
We study the feasibility and capability of the kernel temporal difference (KTD)(λ) algorithm for neural decoding. KTD(λ) is an online, kernel-based learning algorithm, which has been introduced to estimate value functions in reinforcement learning. This algorithm combines kernel-based representations with the temporal difference approach to learning. One of our key observations is that by using strictly positive definite kernels, algorithm's convergence can be guaranteed for policy evaluation. The algorithm's nonlinear functional approximation capabilities are shown in both simulations of policy evaluation and neural decoding problems (policy improvement). KTD can handle high-dimensional neural states containing spatial-temporal information at a reasonable computational complexity allowing real-time applications. When the algorithm seeks a proper mapping between a monkey's neural states and desired positions of a computer cursor or a robot arm, in both open-loop and closed-loop experiments, it can effectively learn the neural state to action mapping. Finally, a visualization of the coadaptation process between the decoder and the subject shows the algorithm's capabilities in reinforcement learning brain machine interfaces. PMID:25866504
Sequential logic analysis and synthesis
Cavanagh, Joseph
2007-01-01
Until now, there was no single resource for actual digital system design. Using both basic and advanced concepts, Sequential Logic: Analysis and Synthesis offers a thorough exposition of the analysis and synthesis of both synchronous and asynchronous sequential machines. With 25 years of experience in designing computing equipment, the author stresses the practical design of state machines. He clearly delineates each step of the structured and rigorous design principles that can be applied to practical applications. The book begins by reviewing the analysis of combinatorial logic and Boolean a
Decoding Facial Expressions: A New Test with Decoding Norms.
Leathers, Dale G.; Emigh, Ted H.
1980-01-01
Describes the development and testing of a new facial meaning sensitivity test designed to determine how specialized are the meanings that can be decoded from facial expressions. Demonstrates the use of the test to measure a receiver's current level of skill in decoding facial expressions. (JMF)
List Decoding of Algebraic Codes
DEFF Research Database (Denmark)
Nielsen, Johan Sebastian Rosenkilde
We investigate three paradigms for polynomial-time decoding of Reed–Solomon codes beyond half the minimum distance: the Guruswami–Sudan algorithm, Power decoding and the Wu algorithm. The main results concern shaping the computational core of all three methods to a problem solvable by module...... Hermitian codes using Guruswami–Sudan or Power decoding faster than previously known, and we show how to Wu list decode binary Goppa codes....... to solve such using module minimisation, or using our new Demand–Driven algorithm which is also based on module minimisation. The decoding paradigms are all derived and analysed in a self-contained manner, often in new ways or examined in greater depth than previously. Among a number of new results, we...
Bogler, Carsten; Mehnert, Jan; Steinbrink, Jens; Haynes, John-Dylan
2014-01-01
Sustained, long-term cognitive workload is associated with variations and decrements in performance. Such fluctuations in vigilance can be a risk factor especially during dangerous attention demanding activities. Functional MRI studies have shown that attentional performance is correlated with BOLD-signals, especially in parietal and prefrontal cortical regions. An interesting question is whether these BOLD-signals could be measured in real-world scenarios, say to warn in a dangerous workplace whenever a subjects' vigilance is low. Because fMRI lacks the mobility needed for such applications, we tested whether the monitoring of vigilance might be possible using Near-Infrared Spectroscopy (NIRS). NIRS is a highly mobile technique that measures hemodynamics in the surface of the brain. We demonstrate that non-invasive NIRS signals correlate with vigilance. These signals carry enough information to decode subjects' reaction times at a single trial level.
Directory of Open Access Journals (Sweden)
Carsten Bogler
Full Text Available Sustained, long-term cognitive workload is associated with variations and decrements in performance. Such fluctuations in vigilance can be a risk factor especially during dangerous attention demanding activities. Functional MRI studies have shown that attentional performance is correlated with BOLD-signals, especially in parietal and prefrontal cortical regions. An interesting question is whether these BOLD-signals could be measured in real-world scenarios, say to warn in a dangerous workplace whenever a subjects' vigilance is low. Because fMRI lacks the mobility needed for such applications, we tested whether the monitoring of vigilance might be possible using Near-Infrared Spectroscopy (NIRS. NIRS is a highly mobile technique that measures hemodynamics in the surface of the brain. We demonstrate that non-invasive NIRS signals correlate with vigilance. These signals carry enough information to decode subjects' reaction times at a single trial level.
Astrophysics Decoding the cosmos
Irwin, Judith A
2007-01-01
Astrophysics: Decoding the Cosmos is an accessible introduction to the key principles and theories underlying astrophysics. This text takes a close look at the radiation and particles that we receive from astronomical objects, providing a thorough understanding of what this tells us, drawing the information together using examples to illustrate the process of astrophysics. Chapters dedicated to objects showing complex processes are written in an accessible manner and pull relevant background information together to put the subject firmly into context. The intention of the author is that the book will be a 'tool chest' for undergraduate astronomers wanting to know the how of astrophysics. Students will gain a thorough grasp of the key principles, ensuring that this often-difficult subject becomes more accessible.
Fast decoding algorithms for geometric coded apertures
International Nuclear Information System (INIS)
Byard, Kevin
2015-01-01
Fast decoding algorithms are described for the class of coded aperture designs known as geometric coded apertures which were introduced by Gourlay and Stephen. When compared to the direct decoding method, the algorithms significantly reduce the number of calculations required when performing the decoding for these apertures and hence speed up the decoding process. Experimental tests confirm the efficacy of these fast algorithms, demonstrating a speed up of approximately two to three orders of magnitude over direct decoding.
Bizer, David S; DeMarzo, Peter M
1992-01-01
The authors study environments in which agents may borrow sequentially from more than one leader. Although debt is prioritized, additional lending imposes an externality on prior debt because, with moral hazard, the probability of repayment of prior loans decreases. Equilibrium interest rates are higher than they would be if borrowers could commit to borrow from at most one bank. Even though the loan terms are less favorable than they would be under commitment, the indebtedness of borrowers i...
Deep learning: Using machine learning to study biological vision
Majaj, Najib; Pelli, Denis
2017-01-01
Today most vision-science presentations mention machine learning. Many neuroscientists use machine learning to decode neural responses. Many perception scientists try to understand recognition by living organisms. To them, machine learning offers a reference of attainable performance based on learned stimuli. This brief overview of the use of machine learning in biological vision touches on its strengths, weaknesses, milestones, controversies, and current directions.
Modified Dynamic Decode-and-Forward Relaying Protocol for Type II Relay in LTE-Advanced and Beyond.
Nam, Sung Sik; Alouini, Mohamed-Slim; Choi, Seyeong
2016-01-01
In this paper, we propose a modified dynamic decode-and-forward (MoDDF) relaying protocol to meet the critical requirements for user equipment (UE) relays in next-generation cellular systems (e.g., LTE-Advanced and beyond). The proposed MoDDF realizes the fast jump-in relaying and the sequential decoding with an application of random codeset to encoding and re-encoding process at the source and the multiple UE relays, respectively. A subframe-by-subframe decoding based on the accumulated (or buffered) messages is employed to achieve energy, information, or mixed combining. Finally, possible early termination of decoding at the end user can lead to the higher spectral efficiency and more energy saving by reducing the frequency of redundant subframe transmission and decoding. These attractive features eliminate the need of directly exchanging control messages between multiple UE relays and the end user, which is an important prerequisite for the practical UE relay deployment.
Multi-Temporal Land Cover Classification with Sequential Recurrent Encoders
Rußwurm, Marc; Körner, Marco
2018-03-01
Earth observation (EO) sensors deliver data with daily or weekly temporal resolution. Most land use and land cover (LULC) approaches, however, expect cloud-free and mono-temporal observations. The increasing temporal capabilities of today's sensors enables the use of temporal, along with spectral and spatial features. Domains, such as speech recognition or neural machine translation, work with inherently temporal data and, today, achieve impressive results using sequential encoder-decoder structures. Inspired by these sequence-to-sequence models, we adapt an encoder structure with convolutional recurrent layers in order to approximate a phenological model for vegetation classes based on a temporal sequence of Sentinel 2 (S2) images. In our experiments, we visualize internal activations over a sequence of cloudy and non-cloudy images and find several recurrent cells, which reduce the input activity for cloudy observations. Hence, we assume that our network has learned cloud-filtering schemes solely from input data, which could alleviate the need for tedious cloud-filtering as a preprocessing step for many EO approaches. Moreover, using unfiltered temporal series of top-of-atmosphere (TOA) reflectance data, we achieved in our experiments state-of-the-art classification accuracies on a large number of crop classes with minimal preprocessing compared to other classification approaches.
Decoding English Alphabet Letters Using EEG Phase Information
Directory of Open Access Journals (Sweden)
YiYan Wang
2018-02-01
Full Text Available Increasing evidence indicates that the phase pattern and power of the low frequency oscillations of brain electroencephalograms (EEG contain significant information during the human cognition of sensory signals such as auditory and visual stimuli. Here, we investigate whether and how the letters of the alphabet can be directly decoded from EEG phase and power data. In addition, we investigate how different band oscillations contribute to the classification and determine the critical time periods. An English letter recognition task was assigned, and statistical analyses were conducted to decode the EEG signal corresponding to each letter visualized on a computer screen. We applied support vector machine (SVM with gradient descent method to learn the potential features for classification. It was observed that the EEG phase signals have a higher decoding accuracy than the oscillation power information. Low-frequency theta and alpha oscillations have phase information with higher accuracy than do other bands. The decoding performance was best when the analysis period began from 180 to 380 ms after stimulus presentation, especially in the lateral occipital and posterior temporal scalp regions (PO7 and PO8. These results may provide a new approach for brain-computer interface techniques (BCI and may deepen our understanding of EEG oscillations in cognition.
Trellises and Trellis-Based Decoding Algorithms for Linear Block Codes
Lin, Shu
1998-01-01
A code trellis is a graphical representation of a code, block or convolutional, in which every path represents a codeword (or a code sequence for a convolutional code). This representation makes it possible to implement Maximum Likelihood Decoding (MLD) of a code with reduced decoding complexity. The most well known trellis-based MLD algorithm is the Viterbi algorithm. The trellis representation was first introduced and used for convolutional codes [23]. This representation, together with the Viterbi decoding algorithm, has resulted in a wide range of applications of convolutional codes for error control in digital communications over the last two decades. There are two major reasons for this inactive period of research in this area. First, most coding theorists at that time believed that block codes did not have simple trellis structure like convolutional codes and maximum likelihood decoding of linear block codes using the Viterbi algorithm was practically impossible, except for very short block codes. Second, since almost all of the linear block codes are constructed algebraically or based on finite geometries, it was the belief of many coding theorists that algebraic decoding was the only way to decode these codes. These two reasons seriously hindered the development of efficient soft-decision decoding methods for linear block codes and their applications to error control in digital communications. This led to a general belief that block codes are inferior to convolutional codes and hence, that they were not useful. Chapter 2 gives a brief review of linear block codes. The goal is to provide the essential background material for the development of trellis structure and trellis-based decoding algorithms for linear block codes in the later chapters. Chapters 3 through 6 present the fundamental concepts, finite-state machine model, state space formulation, basic structural properties, state labeling, construction procedures, complexity, minimality, and
Orientation decoding: Sense in spirals?
Clifford, Colin W G; Mannion, Damien J
2015-04-15
The orientation of a visual stimulus can be successfully decoded from the multivariate pattern of fMRI activity in human visual cortex. Whether this capacity requires coarse-scale orientation biases is controversial. We and others have advocated the use of spiral stimuli to eliminate a potential coarse-scale bias-the radial bias toward local orientations that are collinear with the centre of gaze-and hence narrow down the potential coarse-scale biases that could contribute to orientation decoding. The usefulness of this strategy is challenged by the computational simulations of Carlson (2014), who reported the ability to successfully decode spirals of opposite sense (opening clockwise or counter-clockwise) from the pooled output of purportedly unbiased orientation filters. Here, we elaborate the mathematical relationship between spirals of opposite sense to confirm that they cannot be discriminated on the basis of the pooled output of unbiased or radially biased orientation filters. We then demonstrate that Carlson's (2014) reported decoding ability is consistent with the presence of inadvertent biases in the set of orientation filters; biases introduced by their digital implementation and unrelated to the brain's processing of orientation. These analyses demonstrate that spirals must be processed with an orientation bias other than the radial bias for successful decoding of spiral sense. Copyright © 2014 Elsevier Inc. All rights reserved.
On the decoding process in ternary error-correcting output codes.
Escalera, Sergio; Pujol, Oriol; Radeva, Petia
2010-01-01
A common way to model multiclass classification problems is to design a set of binary classifiers and to combine them. Error-Correcting Output Codes (ECOC) represent a successful framework to deal with these type of problems. Recent works in the ECOC framework showed significant performance improvements by means of new problem-dependent designs based on the ternary ECOC framework. The ternary framework contains a larger set of binary problems because of the use of a "do not care" symbol that allows us to ignore some classes by a given classifier. However, there are no proper studies that analyze the effect of the new symbol at the decoding step. In this paper, we present a taxonomy that embeds all binary and ternary ECOC decoding strategies into four groups. We show that the zero symbol introduces two kinds of biases that require redefinition of the decoding design. A new type of decoding measure is proposed, and two novel decoding strategies are defined. We evaluate the state-of-the-art coding and decoding strategies over a set of UCI Machine Learning Repository data sets and into a real traffic sign categorization problem. The experimental results show that, following the new decoding strategies, the performance of the ECOC design is significantly improved.
Improved decoding for a concatenated coding system
DEFF Research Database (Denmark)
Paaske, Erik
1990-01-01
The concatenated coding system recommended by CCSDS (Consultative Committee for Space Data Systems) uses an outer (255,233) Reed-Solomon (RS) code based on 8-b symbols, followed by the block interleaver and an inner rate 1/2 convolutional code with memory 6. Viterbi decoding is assumed. Two new...... decoding procedures based on repeated decoding trials and exchange of information between the two decoders and the deinterleaver are proposed. In the first one, where the improvement is 0.3-0.4 dB, only the RS decoder performs repeated trials. In the second one, where the improvement is 0.5-0.6 dB, both...... decoders perform repeated decoding trials and decoding information is exchanged between them...
Soft-decision decoding of RS codes
DEFF Research Database (Denmark)
Justesen, Jørn
2005-01-01
By introducing a few simplifying assumptions we derive a simple condition for successful decoding using the Koetter-Vardy algorithm for soft-decision decoding of RS codes. We show that the algorithm has a significant advantage over hard decision decoding when the code rate is low, when two or more...
Toric Codes, Multiplicative Structure and Decoding
DEFF Research Database (Denmark)
Hansen, Johan Peder
2017-01-01
Long linear codes constructed from toric varieties over finite fields, their multiplicative structure and decoding. The main theme is the inherent multiplicative structure on toric codes. The multiplicative structure allows for \\emph{decoding}, resembling the decoding of Reed-Solomon codes and al...
FPGA Realization of Memory 10 Viterbi Decoder
DEFF Research Database (Denmark)
Paaske, Erik; Bach, Thomas Bo; Andersen, Jakob Dahl
1997-01-01
sequence mode when feedback from the Reed-Solomon decoder is available. The Viterbi decoder is realized using two Altera FLEX 10K50 FPGA's. The overall operating speed is 30 kbit/s, and since up to three iterations are performed for each frame and only one decoder is used, the operating speed...
Intention concepts and brain-machine interfacing.
Thinnes-Elker, Franziska; Iljina, Olga; Apostolides, John Kyle; Kraemer, Felicitas; Schulze-Bonhage, Andreas; Aertsen, Ad; Ball, Tonio
2012-01-01
Intentions, including their temporal properties and semantic content, are receiving increased attention, and neuroscientific studies in humans vary with respect to the topography of intention-related neural responses. This may reflect the fact that the kind of intentions investigated in one study may not be exactly the same kind investigated in the other. Fine-grained intention taxonomies developed in the philosophy of mind may be useful to identify the neural correlates of well-defined types of intentions, as well as to disentangle them from other related mental states, such as mere urges to perform an action. Intention-related neural signals may be exploited by brain-machine interfaces (BMIs) that are currently being developed to restore speech and motor control in paralyzed patients. Such BMI devices record the brain activity of the agent, interpret ("decode") the agent's intended action, and send the corresponding execution command to an artificial effector system, e.g., a computer cursor or a robotic arm. In the present paper, we evaluate the potential of intention concepts from philosophy of mind to improve the performance and safety of BMIs based on higher-order, intention-related control signals. To this end, we address the distinction between future-, present-directed, and motor intentions, as well as the organization of intentions in time, specifically to what extent it is sequential or hierarchical. This has consequences as to whether these different types of intentions can be expected to occur simultaneously or not. We further illustrate how it may be useful or even necessary to distinguish types of intentions exposited in philosophy, including yes- vs. no-intentions and oblique vs. direct intentions, to accurately decode the agent's intentions from neural signals in practical BMI applications.
Decoding bipedal locomotion from the rat sensorimotor cortex
Rigosa, J.; Panarese, A.; Dominici, N.; Friedli, L.; van den Brand, R.; Carpaneto, J.; DiGiovanna, J.; Courtine, G.; Micera, S.
2015-10-01
Objective. Decoding forelimb movements from the firing activity of cortical neurons has been interfaced with robotic and prosthetic systems to replace lost upper limb functions in humans. Despite the potential of this approach to improve locomotion and facilitate gait rehabilitation, decoding lower limb movement from the motor cortex has received comparatively little attention. Here, we performed experiments to identify the type and amount of information that can be decoded from neuronal ensemble activity in the hindlimb area of the rat motor cortex during bipedal locomotor tasks. Approach. Rats were trained to stand, step on a treadmill, walk overground and climb staircases in a bipedal posture. To impose this gait, the rats were secured in a robotic interface that provided support against the direction of gravity and in the mediolateral direction, but behaved transparently in the forward direction. After completion of training, rats were chronically implanted with a micro-wire array spanning the left hindlimb motor cortex to record single and multi-unit activity, and bipolar electrodes into 10 muscles of the right hindlimb to monitor electromyographic signals. Whole-body kinematics, muscle activity, and neural signals were simultaneously recorded during execution of the trained tasks over multiple days of testing. Hindlimb kinematics, muscle activity, gait phases, and locomotor tasks were decoded using offline classification algorithms. Main results. We found that the stance and swing phases of gait and the locomotor tasks were detected with accuracies as robust as 90% in all rats. Decoded hindlimb kinematics and muscle activity exhibited a larger variability across rats and tasks. Significance. Our study shows that the rodent motor cortex contains useful information for lower limb neuroprosthetic development. However, brain-machine interfaces estimating gait phases or locomotor behaviors, instead of continuous variables such as limb joint positions or speeds
Fast mental states decoding in mixed reality.
De Massari, Daniele; Pacheco, Daniel; Malekshahi, Rahim; Betella, Alberto; Verschure, Paul F M J; Birbaumer, Niels; Caria, Andrea
2014-01-01
The combination of Brain-Computer Interface (BCI) technology, allowing online monitoring and decoding of brain activity, with virtual and mixed reality (MR) systems may help to shape and guide implicit and explicit learning using ecological scenarios. Real-time information of ongoing brain states acquired through BCI might be exploited for controlling data presentation in virtual environments. Brain states discrimination during mixed reality experience is thus critical for adapting specific data features to contingent brain activity. In this study we recorded electroencephalographic (EEG) data while participants experienced MR scenarios implemented through the eXperience Induction Machine (XIM). The XIM is a novel framework modeling the integration of a sensing system that evaluates and measures physiological and psychological states with a number of actuators and effectors that coherently reacts to the user's actions. We then assessed continuous EEG-based discrimination of spatial navigation, reading and calculation performed in MR, using linear discriminant analysis (LDA) and support vector machine (SVM) classifiers. Dynamic single trial classification showed high accuracy of LDA and SVM classifiers in detecting multiple brain states as well as in differentiating between high and low mental workload, using a 5 s time-window shifting every 200 ms. Our results indicate overall better performance of LDA with respect to SVM and suggest applicability of our approach in a BCI-controlled MR scenario. Ultimately, successful prediction of brain states might be used to drive adaptation of data representation in order to boost information processing in MR.
Decoding intention at sensorimotor timescales.
Directory of Open Access Journals (Sweden)
Mathew Salvaris
Full Text Available The ability to decode an individual's intentions in real time has long been a 'holy grail' of research on human volition. For example, a reliable method could be used to improve scientific study of voluntary action by allowing external probe stimuli to be delivered at different moments during development of intention and action. Several Brain Computer Interface applications have used motor imagery of repetitive actions to achieve this goal. These systems are relatively successful, but only if the intention is sustained over a period of several seconds; much longer than the timescales identified in psychophysiological studies for normal preparation for voluntary action. We have used a combination of sensorimotor rhythms and motor imagery training to decode intentions in a single-trial cued-response paradigm similar to those used in human and non-human primate motor control research. Decoding accuracy of over 0.83 was achieved with twelve participants. With this approach, we could decode intentions to move the left or right hand at sub-second timescales, both for instructed choices instructed by an external stimulus and for free choices generated intentionally by the participant. The implications for volition are considered.
Dynamics of intracellular information decoding
International Nuclear Information System (INIS)
Kobayashi, Tetsuya J; Kamimura, Atsushi
2011-01-01
A variety of cellular functions are robust even to substantial intrinsic and extrinsic noise in intracellular reactions and the environment that could be strong enough to impair or limit them. In particular, of substantial importance is cellular decision-making in which a cell chooses a fate or behavior on the basis of information conveyed in noisy external signals. For robust decoding, the crucial step is filtering out the noise inevitably added during information transmission. As a minimal and optimal implementation of such an information decoding process, the autocatalytic phosphorylation and autocatalytic dephosphorylation (aPadP) cycle was recently proposed. Here, we analyze the dynamical properties of the aPadP cycle in detail. We describe the dynamical roles of the stationary and short-term responses in determining the efficiency of information decoding and clarify the optimality of the threshold value of the stationary response and its information-theoretical meaning. Furthermore, we investigate the robustness of the aPadP cycle against the receptor inactivation time and intrinsic noise. Finally, we discuss the relationship among information decoding with information-dependent actions, bet-hedging and network modularity
Dynamics of intracellular information decoding.
Kobayashi, Tetsuya J; Kamimura, Atsushi
2011-10-01
A variety of cellular functions are robust even to substantial intrinsic and extrinsic noise in intracellular reactions and the environment that could be strong enough to impair or limit them. In particular, of substantial importance is cellular decision-making in which a cell chooses a fate or behavior on the basis of information conveyed in noisy external signals. For robust decoding, the crucial step is filtering out the noise inevitably added during information transmission. As a minimal and optimal implementation of such an information decoding process, the autocatalytic phosphorylation and autocatalytic dephosphorylation (aPadP) cycle was recently proposed. Here, we analyze the dynamical properties of the aPadP cycle in detail. We describe the dynamical roles of the stationary and short-term responses in determining the efficiency of information decoding and clarify the optimality of the threshold value of the stationary response and its information-theoretical meaning. Furthermore, we investigate the robustness of the aPadP cycle against the receptor inactivation time and intrinsic noise. Finally, we discuss the relationship among information decoding with information-dependent actions, bet-hedging and network modularity.
Human Genome Research: Decoding DNA
dropdown arrow Site Map A-Z Index Menu Synopsis Human Genome Research: Decoding DNA Resources with of the DNA double helix during April 2003. James D. Watson, Francis Crick, and Maurice Wilkins were company Celera announced the completion of a "working draft" reference DNA sequence of the human
Liu, K. Y.
1986-01-01
High-speed decoder intended for use with Reed-Solomon (RS) codes of long code length and high error-correcting capability. Design based on algorithm that includes high-radix Fermat transform procedure, which is most efficient for high speeds. RS code in question has code-word length of 256 symbols, of which 224 are information symbols and 32 are redundant.
Encoding and Decoding Models in Cognitive Electrophysiology
Directory of Open Access Journals (Sweden)
Christopher R. Holdgraf
2017-09-01
Full Text Available Cognitive neuroscience has seen rapid growth in the size and complexity of data recorded from the human brain as well as in the computational tools available to analyze this data. This data explosion has resulted in an increased use of multivariate, model-based methods for asking neuroscience questions, allowing scientists to investigate multiple hypotheses with a single dataset, to use complex, time-varying stimuli, and to study the human brain under more naturalistic conditions. These tools come in the form of “Encoding” models, in which stimulus features are used to model brain activity, and “Decoding” models, in which neural features are used to generated a stimulus output. Here we review the current state of encoding and decoding models in cognitive electrophysiology and provide a practical guide toward conducting experiments and analyses in this emerging field. Our examples focus on using linear models in the study of human language and audition. We show how to calculate auditory receptive fields from natural sounds as well as how to decode neural recordings to predict speech. The paper aims to be a useful tutorial to these approaches, and a practical introduction to using machine learning and applied statistics to build models of neural activity. The data analytic approaches we discuss may also be applied to other sensory modalities, motor systems, and cognitive systems, and we cover some examples in these areas. In addition, a collection of Jupyter notebooks is publicly available as a complement to the material covered in this paper, providing code examples and tutorials for predictive modeling in python. The aim is to provide a practical understanding of predictive modeling of human brain data and to propose best-practices in conducting these analyses.
On Decoding Interleaved Chinese Remainder Codes
DEFF Research Database (Denmark)
Li, Wenhui; Sidorenko, Vladimir; Nielsen, Johan Sebastian Rosenkilde
2013-01-01
We model the decoding of Interleaved Chinese Remainder codes as that of finding a short vector in a Z-lattice. Using the LLL algorithm, we obtain an efficient decoding algorithm, correcting errors beyond the unique decoding bound and having nearly linear complexity. The algorithm can fail...... with a probability dependent on the number of errors, and we give an upper bound for this. Simulation results indicate that the bound is close to the truth. We apply the proposed decoding algorithm for decoding a single CR code using the idea of “Power” decoding, suggested for Reed-Solomon codes. A combination...... of these two methods can be used to decode low-rate Interleaved Chinese Remainder codes....
Directory of Open Access Journals (Sweden)
Vito De Feo
2017-05-01
Full Text Available Brain-machine interfaces (BMIs promise to improve the quality of life of patients suffering from sensory and motor disabilities by creating a direct communication channel between the brain and the external world. Yet, their performance is currently limited by the relatively small amount of information that can be decoded from neural activity recorded form the brain. We have recently proposed that such decoding performance may be improved when using state-dependent decoding algorithms that predict and discount the large component of the trial-to-trial variability of neural activity which is due to the dependence of neural responses on the network's current internal state. Here we tested this idea by using a bidirectional BMI to investigate the gain in performance arising from using a state-dependent decoding algorithm. This BMI, implemented in anesthetized rats, controlled the movement of a dynamical system using neural activity decoded from motor cortex and fed back to the brain the dynamical system's position by electrically microstimulating somatosensory cortex. We found that using state-dependent algorithms that tracked the dynamics of ongoing activity led to an increase in the amount of information extracted form neural activity by 22%, with a consequently increase in all of the indices measuring the BMI's performance in controlling the dynamical system. This suggests that state-dependent decoding algorithms may be used to enhance BMIs at moderate computational cost.
De Feo, Vito; Boi, Fabio; Safaai, Houman; Onken, Arno; Panzeri, Stefano; Vato, Alessandro
2017-01-01
Brain-machine interfaces (BMIs) promise to improve the quality of life of patients suffering from sensory and motor disabilities by creating a direct communication channel between the brain and the external world. Yet, their performance is currently limited by the relatively small amount of information that can be decoded from neural activity recorded form the brain. We have recently proposed that such decoding performance may be improved when using state-dependent decoding algorithms that predict and discount the large component of the trial-to-trial variability of neural activity which is due to the dependence of neural responses on the network's current internal state. Here we tested this idea by using a bidirectional BMI to investigate the gain in performance arising from using a state-dependent decoding algorithm. This BMI, implemented in anesthetized rats, controlled the movement of a dynamical system using neural activity decoded from motor cortex and fed back to the brain the dynamical system's position by electrically microstimulating somatosensory cortex. We found that using state-dependent algorithms that tracked the dynamics of ongoing activity led to an increase in the amount of information extracted form neural activity by 22%, with a consequently increase in all of the indices measuring the BMI's performance in controlling the dynamical system. This suggests that state-dependent decoding algorithms may be used to enhance BMIs at moderate computational cost.
Han, Yishi; Luo, Zhixiao; Wang, Jianhua; Min, Zhixuan; Qin, Xinyu; Sun, Yunlong
2014-09-01
In general, context-based adaptive variable length coding (CAVLC) decoding in H.264/AVC standard requires frequent access to the unstructured variable length coding tables (VLCTs) and significant memory accesses are consumed. Heavy memory accesses will cause high power consumption and time delays, which are serious problems for applications in portable multimedia devices. We propose a method for high-efficiency CAVLC decoding by using a program instead of all the VLCTs. The decoded codeword from VLCTs can be obtained without any table look-up and memory access. The experimental results show that the proposed algorithm achieves 100% memory access saving and 40% decoding time saving without degrading video quality. Additionally, the proposed algorithm shows a better performance compared with conventional CAVLC decoding, such as table look-up by sequential search, table look-up by binary search, Moon's method, and Kim's method.
Decoding Individual Finger Movements from One Hand Using Human EEG Signals
Gonzalez, Jania; Ding, Lei
2014-01-01
Brain computer interface (BCI) is an assistive technology, which decodes neurophysiological signals generated by the human brain and translates them into control signals to control external devices, e.g., wheelchairs. One problem challenging noninvasive BCI technologies is the limited control dimensions from decoding movements of, mainly, large body parts, e.g., upper and lower limbs. It has been reported that complicated dexterous functions, i.e., finger movements, can be decoded in electrocorticography (ECoG) signals, while it remains unclear whether noninvasive electroencephalography (EEG) signals also have sufficient information to decode the same type of movements. Phenomena of broadband power increase and low-frequency-band power decrease were observed in EEG in the present study, when EEG power spectra were decomposed by a principal component analysis (PCA). These movement-related spectral structures and their changes caused by finger movements in EEG are consistent with observations in previous ECoG study, as well as the results from ECoG data in the present study. The average decoding accuracy of 77.11% over all subjects was obtained in classifying each pair of fingers from one hand using movement-related spectral changes as features to be decoded using a support vector machine (SVM) classifier. The average decoding accuracy in three epilepsy patients using ECoG data was 91.28% with the similarly obtained features and same classifier. Both decoding accuracies of EEG and ECoG are significantly higher than the empirical guessing level (51.26%) in all subjects (pEEG as in ECoG, and demonstrates the feasibility of discriminating finger movements from one hand using EEG. These findings are promising to facilitate the development of BCIs with rich control signals using noninvasive technologies. PMID:24416360
LDPC Decoding on GPU for Mobile Device
Directory of Open Access Journals (Sweden)
Yiqin Lu
2016-01-01
Full Text Available A flexible software LDPC decoder that exploits data parallelism for simultaneous multicode words decoding on the mobile device is proposed in this paper, supported by multithreading on OpenCL based graphics processing units. By dividing the check matrix into several parts to make full use of both the local memory and private memory on GPU and properly modify the code capacity each time, our implementation on a mobile phone shows throughputs above 100 Mbps and delay is less than 1.6 millisecond in decoding, which make high-speed communication like video calling possible. To realize efficient software LDPC decoding on the mobile device, the LDPC decoding feature on communication baseband chip should be replaced to save the cost and make it easier to upgrade decoder to be compatible with a variety of channel access schemes.
A class of Sudan-decodable codes
DEFF Research Database (Denmark)
Nielsen, Rasmus Refslund
2000-01-01
In this article, Sudan's algorithm is modified into an efficient method to list-decode a class of codes which can be seen as a generalization of Reed-Solomon codes. The algorithm is specialized into a very efficient method for unique decoding. The code construction can be generalized based...... on algebraic-geometry codes and the decoding algorithms are generalized accordingly. Comparisons with Reed-Solomon and Hermitian codes are made....
Feature Selection Methods for Robust Decoding of Finger Movements in a Non-human Primate
Padmanaban, Subash; Baker, Justin; Greger, Bradley
2018-01-01
Objective: The performance of machine learning algorithms used for neural decoding of dexterous tasks may be impeded due to problems arising when dealing with high-dimensional data. The objective of feature selection algorithms is to choose a near-optimal subset of features from the original feature space to improve the performance of the decoding algorithm. The aim of our study was to compare the effects of four feature selection techniques, Wilcoxon signed-rank test, Relative Importance, Principal Component Analysis (PCA), and Mutual Information Maximization on SVM classification performance for a dexterous decoding task. Approach: A nonhuman primate (NHP) was trained to perform small coordinated movements—similar to typing. An array of microelectrodes was implanted in the hand area of the motor cortex of the NHP and used to record action potentials (AP) during finger movements. A Support Vector Machine (SVM) was used to classify which finger movement the NHP was making based upon AP firing rates. We used the SVM classification to examine the functional parameters of (i) robustness to simulated failure and (ii) longevity of classification. We also compared the effect of using isolated-neuron and multi-unit firing rates as the feature vector supplied to the SVM. Main results: The average decoding accuracy for multi-unit features and single-unit features using Mutual Information Maximization (MIM) across 47 sessions was 96.74 ± 3.5% and 97.65 ± 3.36% respectively. The reduction in decoding accuracy between using 100% of the features and 10% of features based on MIM was 45.56% (from 93.7 to 51.09%) and 4.75% (from 95.32 to 90.79%) for multi-unit and single-unit features respectively. MIM had best performance compared to other feature selection methods. Significance: These results suggest improved decoding performance can be achieved by using optimally selected features. The results based on clinically relevant performance metrics also suggest that the decoding
Interior point decoding for linear vector channels
International Nuclear Information System (INIS)
Wadayama, T
2008-01-01
In this paper, a novel decoding algorithm for low-density parity-check (LDPC) codes based on convex optimization is presented. The decoding algorithm, called interior point decoding, is designed for linear vector channels. The linear vector channels include many practically important channels such as inter-symbol interference channels and partial response channels. It is shown that the maximum likelihood decoding (MLD) rule for a linear vector channel can be relaxed to a convex optimization problem, which is called a relaxed MLD problem
Interior point decoding for linear vector channels
Energy Technology Data Exchange (ETDEWEB)
Wadayama, T [Nagoya Institute of Technology, Gokiso, Showa-ku, Nagoya, Aichi, 466-8555 (Japan)], E-mail: wadayama@nitech.ac.jp
2008-01-15
In this paper, a novel decoding algorithm for low-density parity-check (LDPC) codes based on convex optimization is presented. The decoding algorithm, called interior point decoding, is designed for linear vector channels. The linear vector channels include many practically important channels such as inter-symbol interference channels and partial response channels. It is shown that the maximum likelihood decoding (MLD) rule for a linear vector channel can be relaxed to a convex optimization problem, which is called a relaxed MLD problem.
Video encoder/decoder for encoding/decoding motion compensated images
1996-01-01
Video encoder and decoder, provided with a motion compensator for motion-compensated video coding or decoding in which a picture is coded or decoded in blocks in alternately horizontal and vertical steps. The motion compensator is provided with addressing means (160) and controlled multiplexers
Fast mental states decoding in mixed reality.
Directory of Open Access Journals (Sweden)
Daniele eDe Massari
2014-11-01
Full Text Available The combination of Brain-Computer Interface technology, allowing online monitoring and decoding of brain activity, with virtual and mixed reality systems may help to shape and guide implicit and explicit learning using ecological scenarios. Real-time information of ongoing brain states acquired through BCI might be exploited for controlling data presentation in virtual environments. In this context, assessing to what extent brain states can be discriminated during mixed reality experience is critical for adapting specific data features to contingent brain activity. In this study we recorded EEG data while participants experienced a mixed reality scenario implemented through the eXperience Induction Machine (XIM. The XIM is a novel framework modeling the integration of a sensing system that evaluates and measures physiological and psychological states with a number of actuators and effectors that coherently reacts to the user's actions. We then assessed continuous EEG-based discrimination of spatial navigation, reading and calculation performed in mixed reality, using LDA and SVM classifiers. Dynamic single trial classification showed high accuracy of LDA and SVM classifiers in detecting multiple brain states as well as in differentiating between high and low mental workload, using a 5 s time-window shifting every 200 ms. Our results indicate overall better performance of LDA with respect to SVM and suggest applicability of our approach in a BCI-controlled mixed reality scenario. Ultimately, successful prediction of brain states might be used to drive adaptation of data representation in order to boost information processing in mixed reality.
Evaluation framework for K-best sphere decoders
Shen, Chungan; Eltawil, Ahmed M.; Salama, Khaled N.
2010-01-01
or receive antennas. Tree-searching type decoder structures such as Sphere decoder and K-best decoder present an interesting trade-off between complexity and performance. Many algorithmic developments and VLSI implementations have been reported in literature
Application of Beyond Bound Decoding for High Speed Optical Communications
DEFF Research Database (Denmark)
Li, Bomin; Larsen, Knud J.; Vegas Olmos, Juan José
2013-01-01
This paper studies the application of beyond bound decoding method for high speed optical communications. This hard-decision decoding method outperforms traditional minimum distance decoding method, with a total net coding gain of 10.36 dB.......This paper studies the application of beyond bound decoding method for high speed optical communications. This hard-decision decoding method outperforms traditional minimum distance decoding method, with a total net coding gain of 10.36 dB....
On minimizing the maximum broadcast decoding delay for instantly decodable network coding
Douik, Ahmed S.
2014-09-01
In this paper, we consider the problem of minimizing the maximum broadcast decoding delay experienced by all the receivers of generalized instantly decodable network coding (IDNC). Unlike the sum decoding delay, the maximum decoding delay as a definition of delay for IDNC allows a more equitable distribution of the delays between the different receivers and thus a better Quality of Service (QoS). In order to solve this problem, we first derive the expressions for the probability distributions of maximum decoding delay increments. Given these expressions, we formulate the problem as a maximum weight clique problem in the IDNC graph. Although this problem is known to be NP-hard, we design a greedy algorithm to perform effective packet selection. Through extensive simulations, we compare the sum decoding delay and the max decoding delay experienced when applying the policies to minimize the sum decoding delay and our policy to reduce the max decoding delay. Simulations results show that our policy gives a good agreement among all the delay aspects in all situations and outperforms the sum decoding delay policy to effectively minimize the sum decoding delay when the channel conditions become harsher. They also show that our definition of delay significantly improve the number of served receivers when they are subject to strict delay constraints.
Best linear decoding of random mask images
International Nuclear Information System (INIS)
Woods, J.W.; Ekstrom, M.P.; Palmieri, T.M.; Twogood, R.E.
1975-01-01
In 1968 Dicke proposed coded imaging of x and γ rays via random pinholes. Since then, many authors have agreed with him that this technique can offer significant image improvement. A best linear decoding of the coded image is presented, and its superiority over the conventional matched filter decoding is shown. Experimental results in the visible light region are presented. (U.S.)
Oppositional Decoding as an Act of Resistance.
Steiner, Linda
1988-01-01
Argues that contributors to the "No Comment" feature of "Ms." magazine are engaging in oppositional decoding and speculates on why this is a satisfying group process. Also notes such decoding presents another challenge to the idea that mass media has the same effect on all audiences. (SD)
High Speed Frame Synchronization and Viterbi Decoding
DEFF Research Database (Denmark)
Paaske, Erik; Justesen, Jørn; Larsen, Knud J.
1996-01-01
The purpose of Phase 1 of the study is to describe the system structure and algorithms in sufficient detail to allow drawing the high level architecture of units containing frame synchronization and Viterbi decoding. The systems we consider are high data rate space communication systems. Also...... components. Node synchronization performed within a Viterbi decoder is discussed, and algorithms for frame synchronization are described and analyzed. We present a list of system configurations that we find potentially useful. Further, the high level architecture of units that contain frame synchronization...... and various other functions needed in a complete system is presented. Two such units are described, one for placement before the Viterbi decoder and another for placement after the decoder. The high level architectures of three possible implementations of Viterbi decoders are described: The first...
High Speed Frame Synchronization and Viterbi Decoding
DEFF Research Database (Denmark)
Paaske, Erik; Justesen, Jørn; Larsen, Knud J.
1998-01-01
The study has been divided into two phases. The purpose of Phase 1 of the study was to describe the system structure and algorithms in sufficient detail to allow drawing the high level architecture of units containing frame synchronization and Viterbi decoding. After selection of which specific...... potentially useful.Algorithms for frame synchronization are described and analyzed. Further, the high level architecture of units that contain frame synchronization and various other functions needed in a complete system is presented. Two such units are described, one for placement before the Viterbi decoder...... towards a realization in an FPGA.Node synchronization performed within a Viterbi decoder is discussed, and the high level architectures of three possible implementations of Viterbi decoders are described: The first implementation uses a number of commercially available decoders while the the two others...
Kim, Yong-Hee; Thakor, Nitish V; Schieber, Marc H; Kim, Hyoung-Nam
2015-05-01
Future generations of brain-machine interface (BMI) will require more dexterous motion control such as hand and finger movements. Since a population of neurons in the primary motor cortex (M1) area is correlated with finger movements, neural activities recorded in M1 area are used to reconstruct an intended finger movement. In a BMI system, decoding discrete finger movements from a large number of input neurons does not guarantee a higher decoding accuracy in spite of the increase in computational burden. Hence, we hypothesize that selecting neurons important for coding dexterous flexion/extension of finger movements would improve the BMI performance. In this paper, two metrics are presented to quantitatively measure the importance of each neuron based on Bayes risk minimization and deflection coefficient maximization in a statistical decision problem. Since motor cortical neurons are active with movements of several different fingers, the proposed method is more suitable for a discrete decoding of flexion-extension finger movements than the previous methods for decoding reaching movements. In particular, the proposed metrics yielded high decoding accuracies across all subjects and also in the case of including six combined two-finger movements. While our data acquisition and analysis was done off-line and post processing, our results point to the significance of highly coding neurons in improving BMI performance.
Remote Control and Testing of the Interactive TV-Decoder
Directory of Open Access Journals (Sweden)
K. Vlcek
1995-12-01
Full Text Available The article deals with assembling and application of a complex sequential circuit VHDL (VHSIC (Very High-Speed Integrated Circuit Hardware Description Language model. The circuit model is a core of a cryptographic device for the signal encoding and decoding of discreet transmissions by TV-cable net. The cryptographic algorithm is changable according to the user's wishes. The principles of creation and example implementations are presented in the article. The behavioural model is used to minimize mistakes in the ASICs (Application Specific Integrated Circuits. The circuit implementation uses the FPGA (Field Programmable Gate Array technology. The diagnostics of the circuit is based on remote testing by the IEEE Std 1149.1-1990. The VHDL model of diagnostic subsystem is created as an orthogonal model in relation to the cryptographic circuit VHDL model.
Fast decoders for qudit topological codes
International Nuclear Information System (INIS)
Anwar, Hussain; Brown, Benjamin J; Campbell, Earl T; Browne, Dan E
2014-01-01
Qudit toric codes are a natural higher-dimensional generalization of the well-studied qubit toric code. However, standard methods for error correction of the qubit toric code are not applicable to them. Novel decoders are needed. In this paper we introduce two renormalization group decoders for qudit codes and analyse their error correction thresholds and efficiency. The first decoder is a generalization of a ‘hard-decisions’ decoder due to Bravyi and Haah (arXiv:1112.3252). We modify this decoder to overcome a percolation effect which limits its threshold performance for many-level quantum systems. The second decoder is a generalization of a ‘soft-decisions’ decoder due to Poulin and Duclos-Cianci (2010 Phys. Rev. Lett. 104 050504), with a small cell size to optimize the efficiency of implementation in the high dimensional case. In each case, we estimate thresholds for the uncorrelated bit-flip error model and provide a comparative analysis of the performance of both these approaches to error correction of qudit toric codes. (paper)
Iterative Decoding of Concatenated Codes: A Tutorial
Directory of Open Access Journals (Sweden)
Phillip A. Regalia
2005-05-01
Full Text Available The turbo decoding algorithm of a decade ago constituted a milestone in error-correction coding for digital communications, and has inspired extensions to generalized receiver topologies, including turbo equalization, turbo synchronization, and turbo CDMA, among others. Despite an accrued understanding of iterative decoding over the years, the Ã¢Â€Âœturbo principleÃ¢Â€Â remains elusive to master analytically, thereby inciting interest from researchers outside the communications domain. In this spirit, we develop a tutorial presentation of iterative decoding for parallel and serial concatenated codes, in terms hopefully accessible to a broader audience. We motivate iterative decoding as a computationally tractable attempt to approach maximum-likelihood decoding, and characterize fixed points in terms of a Ã¢Â€ÂœconsensusÃ¢Â€Â property between constituent decoders. We review how the decoding algorithm for both parallel and serial concatenated codes coincides with an alternating projection algorithm, which allows one to identify conditions under which the algorithm indeed converges to a maximum-likelihood solution, in terms of particular likelihood functions factoring into the product of their marginals. The presentation emphasizes a common framework applicable to both parallel and serial concatenated codes.
Decoding small surface codes with feedforward neural networks
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.
The serial message-passing schedule for LDPC decoding algorithms
Liu, Mingshan; Liu, Shanshan; Zhou, Yuan; Jiang, Xue
2015-12-01
The conventional message-passing schedule for LDPC decoding algorithms is the so-called flooding schedule. It has the disadvantage that the updated messages cannot be used until next iteration, thus reducing the convergence speed . In this case, the Layered Decoding algorithm (LBP) based on serial message-passing schedule is proposed. In this paper the decoding principle of LBP algorithm is briefly introduced, and then proposed its two improved algorithms, the grouped serial decoding algorithm (Grouped LBP) and the semi-serial decoding algorithm .They can improve LBP algorithm's decoding speed while maintaining a good decoding performance.
Fast decoding algorithms for coded aperture systems
International Nuclear Information System (INIS)
Byard, Kevin
2014-01-01
Fast decoding algorithms are described for a number of established coded aperture systems. The fast decoding algorithms for all these systems offer significant reductions in the number of calculations required when reconstructing images formed by a coded aperture system and hence require less computation time to produce the images. The algorithms may therefore be of use in applications that require fast image reconstruction, such as near real-time nuclear medicine and location of hazardous radioactive spillage. Experimental tests confirm the efficacy of the fast decoding techniques
Decoding Algorithms for Random Linear Network Codes
DEFF Research Database (Denmark)
Heide, Janus; Pedersen, Morten Videbæk; Fitzek, Frank
2011-01-01
We consider the problem of efficient decoding of a random linear code over a finite field. In particular we are interested in the case where the code is random, relatively sparse, and use the binary finite field as an example. The goal is to decode the data using fewer operations to potentially...... achieve a high coding throughput, and reduce energy consumption.We use an on-the-fly version of the Gauss-Jordan algorithm as a baseline, and provide several simple improvements to reduce the number of operations needed to perform decoding. Our tests show that the improvements can reduce the number...
Three phase full wave dc motor decoder
Studer, P. A. (Inventor)
1977-01-01
A three phase decoder for dc motors is disclosed which employs an extremely simple six transistor circuit to derive six properly phased output signals for fullwave operation of dc motors. Six decoding transistors are coupled at their base-emitter junctions across a resistor network arranged in a delta configuration. Each point of the delta configuration is coupled to one of three position sensors which sense the rotational position of the motor. A second embodiment of the invention is disclosed in which photo-optical isolators are used in place of the decoding transistors.
Improved Power Decoding of One-Point Hermitian Codes
DEFF Research Database (Denmark)
Puchinger, Sven; Bouw, Irene; Rosenkilde, Johan Sebastian Heesemann
2017-01-01
We propose a new partial decoding algorithm for one-point Hermitian codes that can decode up to the same number of errors as the Guruswami–Sudan decoder. Simulations suggest that it has a similar failure probability as the latter one. The algorithm is based on a recent generalization of the power...... decoding algorithm for Reed–Solomon codes and does not require an expensive root-finding step. In addition, it promises improvements for decoding interleaved Hermitian codes....
Decoding of interleaved Reed-Solomon codes using improved power decoding
DEFF Research Database (Denmark)
Puchinger, Sven; Rosenkilde ne Nielsen, Johan
2017-01-01
We propose a new partial decoding algorithm for m-interleaved Reed-Solomon (IRS) codes that can decode, with high probability, a random error of relative weight 1 − Rm/m+1 at all code rates R, in time polynomial in the code length n. For m > 2, this is an asymptotic improvement over the previous...... state-of-the-art for all rates, and the first improvement for R > 1/3 in the last 20 years. The method combines collaborative decoding of IRS codes with power decoding up to the Johnson radius....
Decoding Dyslexia, a Common Learning Disability
... if they continue to struggle. Read More "Dyslexic" Articles In Their Own Words: Dealing with Dyslexia / Decoding Dyslexia, a Common Learning Disability / What is Dyslexia? / Special Education and Research ...
Optimal Achievable Encoding for Brain Machine Interface
2017-12-22
dictionary-based encoding approach to translate a visual image into sequential patterns of electrical stimulation in real time , in a manner that...including the time for reviewing instructions, searching existing data sources, gathering and maintaining the data needed, and completing and...networks, and by applying linear decoding to complete recorded populations of retinal ganglion cells for the first time . Third, we developed a greedy
Multiuser Random Coding Techniques for Mismatched Decoding
Scarlett, Jonathan; Martinez, Alfonso; Guillén i Fàbregas, Albert
2016-01-01
This paper studies multiuser random coding techniques for channel coding with a given (possibly suboptimal) decoding rule. For the mismatched discrete memoryless multiple-access channel, an error exponent is obtained that is tight with respect to the ensemble average, and positive within the interior of Lapidoth's achievable rate region. This exponent proves the ensemble tightness of the exponent of Liu and Hughes in the case of maximum-likelihood decoding. An equivalent dual form of Lapidoth...
Neural signatures of attention: insights from decoding population activity patterns.
Sapountzis, Panagiotis; Gregoriou, Georgia G
2018-01-01
Understanding brain function and the computations that individual neurons and neuronal ensembles carry out during cognitive functions is one of the biggest challenges in neuroscientific research. To this end, invasive electrophysiological studies have provided important insights by recording the activity of single neurons in behaving animals. To average out noise, responses are typically averaged across repetitions and across neurons that are usually recorded on different days. However, the brain makes decisions on short time scales based on limited exposure to sensory stimulation by interpreting responses of populations of neurons on a moment to moment basis. Recent studies have employed machine-learning algorithms in attention and other cognitive tasks to decode the information content of distributed activity patterns across neuronal ensembles on a single trial basis. Here, we review results from studies that have used pattern-classification decoding approaches to explore the population representation of cognitive functions. These studies have offered significant insights into population coding mechanisms. Moreover, we discuss how such advances can aid the development of cognitive brain-computer interfaces.
Deep learning with convolutional neural networks for EEG decoding and visualization.
Schirrmeister, Robin Tibor; Springenberg, Jost Tobias; Fiederer, Lukas Dominique Josef; Glasstetter, Martin; Eggensperger, Katharina; Tangermann, Michael; Hutter, Frank; Burgard, Wolfram; Ball, Tonio
2017-11-01
Deep learning with convolutional neural networks (deep ConvNets) has revolutionized computer vision through end-to-end learning, that is, learning from the raw data. There is increasing interest in using deep ConvNets for end-to-end EEG analysis, but a better understanding of how to design and train ConvNets for end-to-end EEG decoding and how to visualize the informative EEG features the ConvNets learn is still needed. Here, we studied deep ConvNets with a range of different architectures, designed for decoding imagined or executed tasks from raw EEG. Our results show that recent advances from the machine learning field, including batch normalization and exponential linear units, together with a cropped training strategy, boosted the deep ConvNets decoding performance, reaching at least as good performance as the widely used filter bank common spatial patterns (FBCSP) algorithm (mean decoding accuracies 82.1% FBCSP, 84.0% deep ConvNets). While FBCSP is designed to use spectral power modulations, the features used by ConvNets are not fixed a priori. Our novel methods for visualizing the learned features demonstrated that ConvNets indeed learned to use spectral power modulations in the alpha, beta, and high gamma frequencies, and proved useful for spatially mapping the learned features by revealing the topography of the causal contributions of features in different frequency bands to the decoding decision. Our study thus shows how to design and train ConvNets to decode task-related information from the raw EEG without handcrafted features and highlights the potential of deep ConvNets combined with advanced visualization techniques for EEG-based brain mapping. Hum Brain Mapp 38:5391-5420, 2017. © 2017 Wiley Periodicals, Inc. © 2017 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.
Long-Term Asynchronous Decoding of Arm Motion Using Electrocorticographic Signals in Monkeys
Chao, Zenas C.; Nagasaka, Yasuo; Fujii, Naotaka
2009-01-01
Brain–machine interfaces (BMIs) employ the electrical activity generated by cortical neurons directly for controlling external devices and have been conceived as a means for restoring human cognitive or sensory-motor functions. The dominant approach in BMI research has been to decode motor variables based on single-unit activity (SUA). Unfortunately, this approach suffers from poor long-term stability and daily recalibration is normally required to maintain reliable performance. A possible alternative is BMIs based on electrocorticograms (ECoGs), which measure population activity and may provide more durable and stable recording. However, the level of long-term stability that ECoG-based decoding can offer remains unclear. Here we propose a novel ECoG-based decoding paradigm and show that we have successfully decoded hand positions and arm joint angles during an asynchronous food-reaching task in monkeys when explicit cues prompting the onset of movement were not required. Performance using our ECoG-based decoder was comparable to existing SUA-based systems while evincing far superior stability and durability. In addition, the same decoder could be used for months without any drift in accuracy or recalibration. These results were achieved by incorporating the spatio-spectro-temporal integration of activity across multiple cortical areas to compensate for the lower fidelity of ECoG signals. These results show the feasibility of high-performance, chronic and versatile ECoG-based neuroprosthetic devices for real-life applications. This new method provides a stable platform for investigating cortical correlates for understanding motor control, sensory perception, and high-level cognitive processes. PMID:20407639
Deep learning with convolutional neural networks for EEG decoding and visualization
Springenberg, Jost Tobias; Fiederer, Lukas Dominique Josef; Glasstetter, Martin; Eggensperger, Katharina; Tangermann, Michael; Hutter, Frank; Burgard, Wolfram; Ball, Tonio
2017-01-01
Abstract Deep learning with convolutional neural networks (deep ConvNets) has revolutionized computer vision through end‐to‐end learning, that is, learning from the raw data. There is increasing interest in using deep ConvNets for end‐to‐end EEG analysis, but a better understanding of how to design and train ConvNets for end‐to‐end EEG decoding and how to visualize the informative EEG features the ConvNets learn is still needed. Here, we studied deep ConvNets with a range of different architectures, designed for decoding imagined or executed tasks from raw EEG. Our results show that recent advances from the machine learning field, including batch normalization and exponential linear units, together with a cropped training strategy, boosted the deep ConvNets decoding performance, reaching at least as good performance as the widely used filter bank common spatial patterns (FBCSP) algorithm (mean decoding accuracies 82.1% FBCSP, 84.0% deep ConvNets). While FBCSP is designed to use spectral power modulations, the features used by ConvNets are not fixed a priori. Our novel methods for visualizing the learned features demonstrated that ConvNets indeed learned to use spectral power modulations in the alpha, beta, and high gamma frequencies, and proved useful for spatially mapping the learned features by revealing the topography of the causal contributions of features in different frequency bands to the decoding decision. Our study thus shows how to design and train ConvNets to decode task‐related information from the raw EEG without handcrafted features and highlights the potential of deep ConvNets combined with advanced visualization techniques for EEG‐based brain mapping. Hum Brain Mapp 38:5391–5420, 2017. © 2017 Wiley Periodicals, Inc. PMID:28782865
Directory of Open Access Journals (Sweden)
Elaine Astrand
Full Text Available Decoding neuronal information is important in neuroscience, both as a basic means to understand how neuronal activity is related to cerebral function and as a processing stage in driving neuroprosthetic effectors. Here, we compare the readout performance of six commonly used classifiers at decoding two different variables encoded by the spiking activity of the non-human primate frontal eye fields (FEF: the spatial position of a visual cue, and the instructed orientation of the animal's attention. While the first variable is exogenously driven by the environment, the second variable corresponds to the interpretation of the instruction conveyed by the cue; it is endogenously driven and corresponds to the output of internal cognitive operations performed on the visual attributes of the cue. These two variables were decoded using either a regularized optimal linear estimator in its explicit formulation, an optimal linear artificial neural network estimator, a non-linear artificial neural network estimator, a non-linear naïve Bayesian estimator, a non-linear Reservoir recurrent network classifier or a non-linear Support Vector Machine classifier. Our results suggest that endogenous information such as the orientation of attention can be decoded from the FEF with the same accuracy as exogenous visual information. All classifiers did not behave equally in the face of population size and heterogeneity, the available training and testing trials, the subject's behavior and the temporal structure of the variable of interest. In most situations, the regularized optimal linear estimator and the non-linear Support Vector Machine classifiers outperformed the other tested decoders.
Distinct neural patterns enable grasp types decoding in monkey dorsal premotor cortex
Hao, Yaoyao; Zhang, Qiaosheng; Controzzi, Marco; Cipriani, Christian; Li, Yue; Li, Juncheng; Zhang, Shaomin; Wang, Yiwen; Chen, Weidong; Chiara Carrozza, Maria; Zheng, Xiaoxiang
2014-12-01
Objective. Recent studies have shown that dorsal premotor cortex (PMd), a cortical area in the dorsomedial grasp pathway, is involved in grasp movements. However, the neural ensemble firing property of PMd during grasp movements and the extent to which it can be used for grasp decoding are still unclear. Approach. To address these issues, we used multielectrode arrays to record both spike and local field potential (LFP) signals in PMd in macaque monkeys performing reaching and grasping of one of four differently shaped objects. Main results. Single and population neuronal activity showed distinct patterns during execution of different grip types. Cluster analysis of neural ensemble signals indicated that the grasp related patterns emerged soon (200-300 ms) after the go cue signal, and faded away during the hold period. The timing and duration of the patterns varied depending on the behaviors of individual monkey. Application of support vector machine model to stable activity patterns revealed classification accuracies of 94% and 89% for each of the two monkeys, indicating a robust, decodable grasp pattern encoded in the PMd. Grasp decoding using LFPs, especially the high-frequency bands, also produced high decoding accuracies. Significance. This study is the first to specify the neuronal population encoding of grasp during the time course of grasp. We demonstrate high grasp decoding performance in PMd. These findings, combined with previous evidence for reach related modulation studies, suggest that PMd may play an important role in generation and maintenance of grasp action and may be a suitable locus for brain-machine interface applications.
A novel parallel pipeline structure of VP9 decoder
Qin, Huabiao; Chen, Wu; Yi, Sijun; Tan, Yunfei; Yi, Huan
2018-04-01
To improve the efficiency of VP9 decoder, a novel parallel pipeline structure of VP9 decoder is presented in this paper. According to the decoding workflow, VP9 decoder can be divided into sub-modules which include entropy decoding, inverse quantization, inverse transform, intra prediction, inter prediction, deblocking and pixel adaptive compensation. By analyzing the computing time of each module, hotspot modules are located and the causes of low efficiency of VP9 decoder can be found. Then, a novel pipeline decoder structure is designed by using mixed parallel decoding methods of data division and function division. The experimental results show that this structure can greatly improve the decoding efficiency of VP9.
Coding and decoding with dendrites.
Papoutsi, Athanasia; Kastellakis, George; Psarrou, Maria; Anastasakis, Stelios; Poirazi, Panayiota
2014-02-01
Since the discovery of complex, voltage dependent mechanisms in the dendrites of multiple neuron types, great effort has been devoted in search of a direct link between dendritic properties and specific neuronal functions. Over the last few years, new experimental techniques have allowed the visualization and probing of dendritic anatomy, plasticity and integrative schemes with unprecedented detail. This vast amount of information has caused a paradigm shift in the study of memory, one of the most important pursuits in Neuroscience, and calls for the development of novel theories and models that will unify the available data according to some basic principles. Traditional models of memory considered neural cells as the fundamental processing units in the brain. Recent studies however are proposing new theories in which memory is not only formed by modifying the synaptic connections between neurons, but also by modifications of intrinsic and anatomical dendritic properties as well as fine tuning of the wiring diagram. In this review paper we present previous studies along with recent findings from our group that support a key role of dendrites in information processing, including the encoding and decoding of new memories, both at the single cell and the network level. Copyright © 2013 Elsevier Ltd. All rights reserved.
Modified Dynamic Decode-and-Forward Relaying Protocol for Type II Relay in LTE-Advanced and Beyond
Nam, Sung Sik
2016-11-29
In this paper, we propose a modified dynamic decode-and-forward (MoDDF) relaying protocol to meet the critical requirements for user equipment (UE) relays in next-generation cellular systems (e.g., LTE-Advanced and beyond). The proposed MoDDF realizes the fast jump-in relaying and the sequential decoding with an application of random codeset to encoding and re-encoding process at the source and the multiple UE relays, respectively. A subframe-by-subframe decoding based on the accumulated (or buffered) messages is employed to achieve energy, information, or mixed combining. Finally, possible early termination of decoding at the end user can lead to the higher spectral efficiency and more energy saving by reducing the frequency of redundant subframe transmission and decoding. These attractive features eliminate the need of directly exchanging control messages between multiple UE relays and the end user, which is an important prerequisite for the practical UE relay deployment. Copyright: © 2016 Nam et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Modified Dynamic Decode-and-Forward Relaying Protocol for Type II Relay in LTE-Advanced and Beyond
Nam, Sung Sik; Alouini, Mohamed-Slim; Choi, Seyeong
2016-01-01
In this paper, we propose a modified dynamic decode-and-forward (MoDDF) relaying protocol to meet the critical requirements for user equipment (UE) relays in next-generation cellular systems (e.g., LTE-Advanced and beyond). The proposed MoDDF realizes the fast jump-in relaying and the sequential decoding with an application of random codeset to encoding and re-encoding process at the source and the multiple UE relays, respectively. A subframe-by-subframe decoding based on the accumulated (or buffered) messages is employed to achieve energy, information, or mixed combining. Finally, possible early termination of decoding at the end user can lead to the higher spectral efficiency and more energy saving by reducing the frequency of redundant subframe transmission and decoding. These attractive features eliminate the need of directly exchanging control messages between multiple UE relays and the end user, which is an important prerequisite for the practical UE relay deployment. Copyright: © 2016 Nam et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Intention concepts and brain-machine interfacing
Directory of Open Access Journals (Sweden)
Franziska eThinnes-Elker
2012-11-01
Full Text Available Intentions, including their temporal properties and semantic content, are receiving increased attention, and neuroscientific studies in humans vary with respect to the topography of intention-related neural responses. This may reflect the fact that the kind of intentions investigated in one study may not be exactly the same kind investigated in the other. Fine-grained intention taxonomies developed in the philosophy of mind may be useful to identify the neural correlates of well-defined types of intentions, as well as to disentangle them from other related mental states, such as mere urges to perform an action. Intention-related neural signals may be exploited by brain-machine interfaces (BMIs that are currently being developed to restore speech and motor control in paralyzed subjects. Such BMI devices record the brain activity of the agent, interpret (‘decode’ the agent’s intended action, and send the corresponding execution command to an artificial effector system, e.g., a computer cursor or a robotic arm. In the present paper, we evaluate the potential of intention concepts from philosophy of mind to improve the performance and safety of BMIs based on higher-order, intention-related control signals. To this end, we address the distinction between future-, present-directed, and motor intentions, as well as the organization of intentions in time, specifically to what extent it is sequential or hierarchical. This has consequences as to whether these different types of intentions can be expected to occur simultaneously or not. We further illustrate how it may be useful or even necessary to distinguish types of intentions exposited in philosophy, including yes- vs. no-intentions and oblique vs. direct intentions, to accurately decode the agent’s intentions from neural signals in practical BMI applications.
Learning a common dictionary for subject-transfer decoding with resting calibration.
Morioka, Hiroshi; Kanemura, Atsunori; Hirayama, Jun-ichiro; Shikauchi, Manabu; Ogawa, Takeshi; Ikeda, Shigeyuki; Kawanabe, Motoaki; Ishii, Shin
2015-05-01
Brain signals measured over a series of experiments have inherent variability because of different physical and mental conditions among multiple subjects and sessions. Such variability complicates the analysis of data from multiple subjects and sessions in a consistent way, and degrades the performance of subject-transfer decoding in a brain-machine interface (BMI). To accommodate the variability in brain signals, we propose 1) a method for extracting spatial bases (or a dictionary) shared by multiple subjects, by employing a signal-processing technique of dictionary learning modified to compensate for variations between subjects and sessions, and 2) an approach to subject-transfer decoding that uses the resting-state activity of a previously unseen target subject as calibration data for compensating for variations, eliminating the need for a standard calibration based on task sessions. Applying our methodology to a dataset of electroencephalography (EEG) recordings during a selective visual-spatial attention task from multiple subjects and sessions, where the variability compensation was essential for reducing the redundancy of the dictionary, we found that the extracted common brain activities were reasonable in the light of neuroscience knowledge. The applicability to subject-transfer decoding was confirmed by improved performance over existing decoding methods. These results suggest that analyzing multisubject brain activities on common bases by the proposed method enables information sharing across subjects with low-burden resting calibration, and is effective for practical use of BMI in variable environments. Copyright © 2015 Elsevier Inc. All rights reserved.
Combined fMRI- and eye movement-based decoding of bistable plaid motion perception.
Wilbertz, Gregor; Ketkar, Madhura; Guggenmos, Matthias; Sterzer, Philipp
2018-05-01
The phenomenon of bistable perception, in which perception alternates spontaneously despite constant sensory stimulation, has been particularly useful in probing the neural bases of conscious perception. The study of such bistability requires access to the observer's perceptual dynamics, which is usually achieved via active report. This report, however, constitutes a confounding factor in the study of conscious perception and can also be biased in the context of certain experimental manipulations. One approach to circumvent these problems is to track perceptual alternations using signals from the eyes or the brain instead of observers' reports. Here we aimed to optimize such decoding of perceptual alternations by combining eye and brain signals. Eye-tracking and functional magnetic resonance imaging (fMRI) was performed in twenty participants while they viewed a bistable visual plaid motion stimulus and reported perceptual alternations. Multivoxel pattern analysis (MVPA) for fMRI was combined with eye-tracking in a Support vector machine to decode participants' perceptual time courses from fMRI and eye-movement signals. While both measures individually already yielded high decoding accuracies (on average 86% and 88% correct, respectively) classification based on the two measures together further improved the accuracy (91% correct). These findings show that leveraging on both fMRI and eye movement data may pave the way for optimized no-report paradigms through improved decodability of bistable motion perception and hence for a better understanding of the neural correlates of consciousness. Copyright © 2018 Elsevier Inc. All rights reserved.
A Tensor-Product-Kernel Framework for Multiscale Neural Activity Decoding and Control
Li, Lin; Brockmeier, Austin J.; Choi, John S.; Francis, Joseph T.; Sanchez, Justin C.; Príncipe, José C.
2014-01-01
Brain machine interfaces (BMIs) have attracted intense attention as a promising technology for directly interfacing computers or prostheses with the brain's motor and sensory areas, thereby bypassing the body. The availability of multiscale neural recordings including spike trains and local field potentials (LFPs) brings potential opportunities to enhance computational modeling by enriching the characterization of the neural system state. However, heterogeneity on data type (spike timing versus continuous amplitude signals) and spatiotemporal scale complicates the model integration of multiscale neural activity. In this paper, we propose a tensor-product-kernel-based framework to integrate the multiscale activity and exploit the complementary information available in multiscale neural activity. This provides a common mathematical framework for incorporating signals from different domains. The approach is applied to the problem of neural decoding and control. For neural decoding, the framework is able to identify the nonlinear functional relationship between the multiscale neural responses and the stimuli using general purpose kernel adaptive filtering. In a sensory stimulation experiment, the tensor-product-kernel decoder outperforms decoders that use only a single neural data type. In addition, an adaptive inverse controller for delivering electrical microstimulation patterns that utilizes the tensor-product kernel achieves promising results in emulating the responses to natural stimulation. PMID:24829569
FPGA implementation of low complexity LDPC iterative decoder
Verma, Shivani; Sharma, Sanjay
2016-07-01
Low-density parity-check (LDPC) codes, proposed by Gallager, emerged as a class of codes which can yield very good performance on the additive white Gaussian noise channel as well as on the binary symmetric channel. LDPC codes have gained lots of importance due to their capacity achieving property and excellent performance in the noisy channel. Belief propagation (BP) algorithm and its approximations, most notably min-sum, are popular iterative decoding algorithms used for LDPC and turbo codes. The trade-off between the hardware complexity and the decoding throughput is a critical factor in the implementation of the practical decoder. This article presents introduction to LDPC codes and its various decoding algorithms followed by realisation of LDPC decoder by using simplified message passing algorithm and partially parallel decoder architecture. Simplified message passing algorithm has been proposed for trade-off between low decoding complexity and decoder performance. It greatly reduces the routing and check node complexity of the decoder. Partially parallel decoder architecture possesses high speed and reduced complexity. The improved design of the decoder possesses a maximum symbol throughput of 92.95 Mbps and a maximum of 18 decoding iterations. The article presents implementation of 9216 bits, rate-1/2, (3, 6) LDPC decoder on Xilinx XC3D3400A device from Spartan-3A DSP family.
Performance breakdown in optimal stimulus decoding.
Lubomir Kostal; Lansky, Petr; Pilarski, Stevan
2015-06-01
One of the primary goals of neuroscience is to understand how neurons encode and process information about their environment. The problem is often approached indirectly by examining the degree to which the neuronal response reflects the stimulus feature of interest. In this context, the methods of signal estimation and detection theory provide the theoretical limits on the decoding accuracy with which the stimulus can be identified. The Cramér-Rao lower bound on the decoding precision is widely used, since it can be evaluated easily once the mathematical model of the stimulus-response relationship is determined. However, little is known about the behavior of different decoding schemes with respect to the bound if the neuronal population size is limited. We show that under broad conditions the optimal decoding displays a threshold-like shift in performance in dependence on the population size. The onset of the threshold determines a critical range where a small increment in size, signal-to-noise ratio or observation time yields a dramatic gain in the decoding precision. We demonstrate the existence of such threshold regions in early auditory and olfactory information coding. We discuss the origin of the threshold effect and its impact on the design of effective coding approaches in terms of relevant population size.
Symbol synchronization for the TDRSS decoder
Costello, D. J., Jr.
1983-01-01
Each 8 bits out of the Viterbi decoder correspond to one symbol of the R/S code. Synchronization must be maintained here so that each 8-bit symbol delivered to the R/S decoder corresponds to an 8-bit symbol from the R/S encoder. Lack of synchronization, would cause an error in almost every R/S symbol since even a - 1-bit sync slip shifts every bit in each 8-bit symbol by one position, therby confusing the mapping betweeen 8-bit sequences and symbols. The error correcting capability of the R/S code would be exceeded. Possible ways to correcting this condition include: (1) designing the R/S decoder to recognize the overload and shifting the output sequence of the inner decoder to establish a different sync state; (2) using the characteristics of the inner decoder to establish symbol synchronization for the outer code, with or without a deinterleaver and an interleaver; and (3) modifying the encoder to alternate periodically between two sets of generators.
Modified Decoding Algorithm of LLR-SPA
Directory of Open Access Journals (Sweden)
Zhongxun Wang
2014-09-01
Full Text Available In wireless sensor networks, the energy consumption is mainly occurred in the stage of information transmission. The Low Density Parity Check code can make full use of the channel information to save energy. Because of the widely used decoding algorithm of the Low Density Parity Check code, this paper proposes a new decoding algorithm which is based on the LLR-SPA (Sum-Product Algorithm in Log-Likelihood-domain to improve the accuracy of the decoding algorithm. In the modified algorithm, a piecewise linear function is used to approximate the complicated Jacobi correction term in LLR-SPA decoding algorithm. Construct the tangent by the tangency point to the function of Jacobi correction term, which is based on the first order Taylor Series. In this way, the proposed piecewise linear approximation offers almost a perfect match to the function of Jacobi correction term. Meanwhile, the proposed piecewise linear approximation could avoid the operation of logarithmic which is more suitable for practical application. The simulation results show that the proposed algorithm could improve the decoding accuracy greatly without noticeable variation of the computational complexity.
Sequential charged particle reaction
International Nuclear Information System (INIS)
Hori, Jun-ichi; Ochiai, Kentaro; Sato, Satoshi; Yamauchi, Michinori; Nishitani, Takeo
2004-01-01
The effective cross sections for producing the sequential reaction products in F82H, pure vanadium and LiF with respect to the 14.9-MeV neutron were obtained and compared with the estimation ones. Since the sequential reactions depend on the secondary charged particles behavior, the effective cross sections are corresponding to the target nuclei and the material composition. The effective cross sections were also estimated by using the EAF-libraries and compared with the experimental ones. There were large discrepancies between estimated and experimental values. Additionally, we showed the contribution of the sequential reaction on the induced activity and dose rate in the boundary region with water. From the present study, it has been clarified that the sequential reactions are of great importance to evaluate the dose rates around the surface of cooling pipe and the activated corrosion products. (author)
Higgs Machine Learning Challenge 2014
Olivier, A-P; Bourdarios, C ; LAL / Orsay; Goldfarb, S ; University of Michigan
2014-01-01
High Energy Physics (HEP) has been using Machine Learning (ML) techniques such as boosted decision trees (paper) and neural nets since the 90s. These techniques are now routinely used for difficult tasks such as the Higgs boson search. Nevertheless, formal connections between the two research fields are rather scarce, with some exceptions such as the AppStat group at LAL, founded in 2006. In collaboration with INRIA, AppStat promotes interdisciplinary research on machine learning, computational statistics, and high-energy particle and astroparticle physics. We are now exploring new ways to improve the cross-fertilization of the two fields by setting up a data challenge, following the footsteps of, among others, the astrophysics community (dark matter and galaxy zoo challenges) and neurobiology (connectomics and decoding the human brain). The organization committee consists of ATLAS physicists and machine learning researchers. The Challenge will run from Monday 12th to September 2014.
Completion time reduction in instantly decodable network coding through decoding delay control
Douik, Ahmed S.
2014-12-01
For several years, the completion time and the decoding delay problems in Instantly Decodable Network Coding (IDNC) were considered separately and were thought to completely act against each other. Recently, some works aimed to balance the effects of these two important IDNC metrics but none of them studied a further optimization of one by controlling the other. In this paper, we study the effect of controlling the decoding delay to reduce the completion time below its currently best known solution. We first derive the decoding-delay-dependent expressions of the users\\' and their overall completion times. Although using such expressions to find the optimal overall completion time is NP-hard, we use a heuristic that minimizes the probability of increasing the maximum of these decoding-delay-dependent completion time expressions after each transmission through a layered control of their decoding delays. Simulation results show that this new algorithm achieves both a lower mean completion time and mean decoding delay compared to the best known heuristic for completion time reduction. The gap in performance becomes significant for harsh erasure scenarios.
Completion time reduction in instantly decodable network coding through decoding delay control
Douik, Ahmed S.; Sorour, Sameh; Alouini, Mohamed-Slim; Al-Naffouri, Tareq Y.
2014-01-01
For several years, the completion time and the decoding delay problems in Instantly Decodable Network Coding (IDNC) were considered separately and were thought to completely act against each other. Recently, some works aimed to balance the effects of these two important IDNC metrics but none of them studied a further optimization of one by controlling the other. In this paper, we study the effect of controlling the decoding delay to reduce the completion time below its currently best known solution. We first derive the decoding-delay-dependent expressions of the users' and their overall completion times. Although using such expressions to find the optimal overall completion time is NP-hard, we use a heuristic that minimizes the probability of increasing the maximum of these decoding-delay-dependent completion time expressions after each transmission through a layered control of their decoding delays. Simulation results show that this new algorithm achieves both a lower mean completion time and mean decoding delay compared to the best known heuristic for completion time reduction. The gap in performance becomes significant for harsh erasure scenarios.
NP-hardness of decoding quantum error-correction codes
Hsieh, Min-Hsiu; Le Gall, François
2011-05-01
Although the theory of quantum error correction is intimately related to classical coding theory and, in particular, one can construct quantum error-correction codes (QECCs) from classical codes with the dual-containing property, this does not necessarily imply that the computational complexity of decoding QECCs is the same as their classical counterparts. Instead, decoding QECCs can be very much different from decoding classical codes due to the degeneracy property. Intuitively, one expects degeneracy would simplify the decoding since two different errors might not and need not be distinguished in order to correct them. However, we show that general quantum decoding problem is NP-hard regardless of the quantum codes being degenerate or nondegenerate. This finding implies that no considerably fast decoding algorithm exists for the general quantum decoding problems and suggests the existence of a quantum cryptosystem based on the hardness of decoding QECCs.
NP-hardness of decoding quantum error-correction codes
International Nuclear Information System (INIS)
Hsieh, Min-Hsiu; Le Gall, Francois
2011-01-01
Although the theory of quantum error correction is intimately related to classical coding theory and, in particular, one can construct quantum error-correction codes (QECCs) from classical codes with the dual-containing property, this does not necessarily imply that the computational complexity of decoding QECCs is the same as their classical counterparts. Instead, decoding QECCs can be very much different from decoding classical codes due to the degeneracy property. Intuitively, one expects degeneracy would simplify the decoding since two different errors might not and need not be distinguished in order to correct them. However, we show that general quantum decoding problem is NP-hard regardless of the quantum codes being degenerate or nondegenerate. This finding implies that no considerably fast decoding algorithm exists for the general quantum decoding problems and suggests the existence of a quantum cryptosystem based on the hardness of decoding QECCs.
Generalized Sudan's List Decoding for Order Domain Codes
DEFF Research Database (Denmark)
Geil, Hans Olav; Matsumoto, Ryutaroh
2007-01-01
We generalize Sudan's list decoding algorithm without multiplicity to evaluation codes coming from arbitrary order domains. The number of correctable errors by the proposed method is larger than the original list decoding without multiplicity....
Partially blind instantly decodable network codes for lossy feedback environment
Sorour, Sameh; Douik, Ahmed S.; Valaee, Shahrokh; Al-Naffouri, Tareq Y.; Alouini, Mohamed-Slim
2014-01-01
an expression for the expected decoding delay increment for any arbitrary transmission. This expression is then used to find the optimal policy that reduces the decoding delay in such lossy feedback environment. Results show that our proposed solutions both
Decoding human mental states by whole-head EEG+fNIRS during category fluency task performance
Omurtag, Ahmet; Aghajani, Haleh; Onur Keles, Hasan
2017-12-01
Objective. Concurrent scalp electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS), which we refer to as EEG+fNIRS, promises greater accuracy than the individual modalities while remaining nearly as convenient as EEG. We sought to quantify the hybrid system’s ability to decode mental states and compare it with its unimodal components. Approach. We recorded from healthy volunteers taking the category fluency test and applied machine learning techniques to the data. Main results. EEG+fNIRS’s decoding accuracy was greater than that of its subsystems, partly due to the new type of neurovascular features made available by hybrid data. Significance. Availability of an accurate and practical decoding method has potential implications for medical diagnosis, brain-computer interface design, and neuroergonomics.
Neuroprosthetic Decoder Training as Imitation Learning.
Merel, Josh; Carlson, David; Paninski, Liam; Cunningham, John P
2016-05-01
Neuroprosthetic brain-computer interfaces function via an algorithm which decodes neural activity of the user into movements of an end effector, such as a cursor or robotic arm. In practice, the decoder is often learned by updating its parameters while the user performs a task. When the user's intention is not directly observable, recent methods have demonstrated value in training the decoder against a surrogate for the user's intended movement. Here we show that training a decoder in this way is a novel variant of an imitation learning problem, where an oracle or expert is employed for supervised training in lieu of direct observations, which are not available. Specifically, we describe how a generic imitation learning meta-algorithm, dataset aggregation (DAgger), can be adapted to train a generic brain-computer interface. By deriving existing learning algorithms for brain-computer interfaces in this framework, we provide a novel analysis of regret (an important metric of learning efficacy) for brain-computer interfaces. This analysis allows us to characterize the space of algorithmic variants and bounds on their regret rates. Existing approaches for decoder learning have been performed in the cursor control setting, but the available design principles for these decoders are such that it has been impossible to scale them to naturalistic settings. Leveraging our findings, we then offer an algorithm that combines imitation learning with optimal control, which should allow for training of arbitrary effectors for which optimal control can generate goal-oriented control. We demonstrate this novel and general BCI algorithm with simulated neuroprosthetic control of a 26 degree-of-freedom model of an arm, a sophisticated and realistic end effector.
Neuroprosthetic Decoder Training as Imitation Learning.
Directory of Open Access Journals (Sweden)
Josh Merel
2016-05-01
Full Text Available Neuroprosthetic brain-computer interfaces function via an algorithm which decodes neural activity of the user into movements of an end effector, such as a cursor or robotic arm. In practice, the decoder is often learned by updating its parameters while the user performs a task. When the user's intention is not directly observable, recent methods have demonstrated value in training the decoder against a surrogate for the user's intended movement. Here we show that training a decoder in this way is a novel variant of an imitation learning problem, where an oracle or expert is employed for supervised training in lieu of direct observations, which are not available. Specifically, we describe how a generic imitation learning meta-algorithm, dataset aggregation (DAgger, can be adapted to train a generic brain-computer interface. By deriving existing learning algorithms for brain-computer interfaces in this framework, we provide a novel analysis of regret (an important metric of learning efficacy for brain-computer interfaces. This analysis allows us to characterize the space of algorithmic variants and bounds on their regret rates. Existing approaches for decoder learning have been performed in the cursor control setting, but the available design principles for these decoders are such that it has been impossible to scale them to naturalistic settings. Leveraging our findings, we then offer an algorithm that combines imitation learning with optimal control, which should allow for training of arbitrary effectors for which optimal control can generate goal-oriented control. We demonstrate this novel and general BCI algorithm with simulated neuroprosthetic control of a 26 degree-of-freedom model of an arm, a sophisticated and realistic end effector.
Decoding of concatenated codes with interleaved outer codes
DEFF Research Database (Denmark)
Justesen, Jørn; Høholdt, Tom; Thommesen, Christian
2004-01-01
Recently Bleichenbacher et al. proposed a decoding algorithm for interleaved (N, K) Reed-Solomon codes, which allows close to N-K errors to be corrected in many cases. We discuss the application of this decoding algorithm to concatenated codes.......Recently Bleichenbacher et al. proposed a decoding algorithm for interleaved (N, K) Reed-Solomon codes, which allows close to N-K errors to be corrected in many cases. We discuss the application of this decoding algorithm to concatenated codes....
Binary Systematic Network Coding for Progressive Packet Decoding
Jones, Andrew L.; Chatzigeorgiou, Ioannis; Tassi, Andrea
2015-01-01
We consider binary systematic network codes and investigate their capability of decoding a source message either in full or in part. We carry out a probability analysis, derive closed-form expressions for the decoding probability and show that systematic network coding outperforms conventional net- work coding. We also develop an algorithm based on Gaussian elimination that allows progressive decoding of source packets. Simulation results show that the proposed decoding algorithm can achieve ...
Decoding Hermitian Codes with Sudan's Algorithm
DEFF Research Database (Denmark)
Høholdt, Tom; Nielsen, Rasmus Refslund
1999-01-01
We present an efficient implementation of Sudan's algorithm for list decoding Hermitian codes beyond half the minimum distance. The main ingredients are an explicit method to calculate so-called increasing zero bases, an efficient interpolation algorithm for finding the Q-polynomial, and a reduct......We present an efficient implementation of Sudan's algorithm for list decoding Hermitian codes beyond half the minimum distance. The main ingredients are an explicit method to calculate so-called increasing zero bases, an efficient interpolation algorithm for finding the Q...
Decoding Interleaved Gabidulin Codes using Alekhnovich's Algorithm
DEFF Research Database (Denmark)
Puchinger, Sven; Müelich, Sven; Mödinger, David
2017-01-01
We prove that Alekhnovich's algorithm can be used for row reduction of skew polynomial matrices. This yields an O(ℓ3n(ω+1)/2log(n)) decoding algorithm for ℓ-Interleaved Gabidulin codes of length n, where ω is the matrix multiplication exponent.......We prove that Alekhnovich's algorithm can be used for row reduction of skew polynomial matrices. This yields an O(ℓ3n(ω+1)/2log(n)) decoding algorithm for ℓ-Interleaved Gabidulin codes of length n, where ω is the matrix multiplication exponent....
Decoding LDPC Convolutional Codes on Markov Channels
Directory of Open Access Journals (Sweden)
Kashyap Manohar
2008-01-01
Full Text Available Abstract This paper describes a pipelined iterative technique for joint decoding and channel state estimation of LDPC convolutional codes over Markov channels. Example designs are presented for the Gilbert-Elliott discrete channel model. We also compare the performance and complexity of our algorithm against joint decoding and state estimation of conventional LDPC block codes. Complexity analysis reveals that our pipelined algorithm reduces the number of operations per time step compared to LDPC block codes, at the expense of increased memory and latency. This tradeoff is favorable for low-power applications.
Decoding LDPC Convolutional Codes on Markov Channels
Directory of Open Access Journals (Sweden)
Chris Winstead
2008-04-01
Full Text Available This paper describes a pipelined iterative technique for joint decoding and channel state estimation of LDPC convolutional codes over Markov channels. Example designs are presented for the Gilbert-Elliott discrete channel model. We also compare the performance and complexity of our algorithm against joint decoding and state estimation of conventional LDPC block codes. Complexity analysis reveals that our pipelined algorithm reduces the number of operations per time step compared to LDPC block codes, at the expense of increased memory and latency. This tradeoff is favorable for low-power applications.
Decoding algorithm for vortex communications receiver
Kupferman, Judy; Arnon, Shlomi
2018-01-01
Vortex light beams can provide a tremendous alphabet for encoding information. We derive a symbol decoding algorithm for a direct detection matrix detector vortex beam receiver using Laguerre Gauss (LG) modes, and develop a mathematical model of symbol error rate (SER) for this receiver. We compare SER as a function of signal to noise ratio (SNR) for our algorithm and for the Pearson correlation algorithm. To our knowledge, this is the first comprehensive treatment of a decoding algorithm of a matrix detector for an LG receiver.
Image transmission system using adaptive joint source and channel decoding
Liu, Weiliang; Daut, David G.
2005-03-01
In this paper, an adaptive joint source and channel decoding method is designed to accelerate the convergence of the iterative log-dimain sum-product decoding procedure of LDPC codes as well as to improve the reconstructed image quality. Error resilience modes are used in the JPEG2000 source codec, which makes it possible to provide useful source decoded information to the channel decoder. After each iteration, a tentative decoding is made and the channel decoded bits are then sent to the JPEG2000 decoder. Due to the error resilience modes, some bits are known to be either correct or in error. The positions of these bits are then fed back to the channel decoder. The log-likelihood ratios (LLR) of these bits are then modified by a weighting factor for the next iteration. By observing the statistics of the decoding procedure, the weighting factor is designed as a function of the channel condition. That is, for lower channel SNR, a larger factor is assigned, and vice versa. Results show that the proposed joint decoding methods can greatly reduce the number of iterations, and thereby reduce the decoding delay considerably. At the same time, this method always outperforms the non-source controlled decoding method up to 5dB in terms of PSNR for various reconstructed images.
Decoding and Encoding Facial Expressions in Preschool-Age Children.
Zuckerman, Miron; Przewuzman, Sylvia J.
1979-01-01
Preschool-age children drew, decoded, and encoded facial expressions depicting five different emotions. Accuracy of drawing, decoding and encoding each of the five emotions was consistent across the three tasks; decoding ability was correlated with drawing ability among female subjects, but neither of these abilities was correlated with encoding…
Continual Learning through Evolvable Neural Turing Machines
DEFF Research Database (Denmark)
Lüders, Benno; Schläger, Mikkel; Risi, Sebastian
2016-01-01
Continual learning, i.e. the ability to sequentially learn tasks without catastrophic forgetting of previously learned ones, is an important open challenge in machine learning. In this paper we take a step in this direction by showing that the recently proposed Evolving Neural Turing Machine (ENTM...
Evolution of Replication Machines
Yao, Nina Y.; O'Donnell, Mike E.
2016-01-01
The machines that decode and regulate genetic information require the translation, transcription and replication pathways essential to all living cells. Thus, it might be expected that all cells share the same basic machinery for these pathways that were inherited from the primordial ancestor cell from which they evolved. A clear example of this is found in the translation machinery that converts RNA sequence to protein. The translation process requires numerous structural and catalytic RNAs and proteins, the central factors of which are homologous in all three domains of life, bacteria, archaea and eukarya. Likewise, the central actor in transcription, RNA polymerase, shows homology among the catalytic subunits in bacteria, archaea and eukarya. In contrast, while some “gears” of the genome replication machinery are homologous in all domains of life, most components of the replication machine appear to be unrelated between bacteria and those of archaea and eukarya. This review will compare and contrast the central proteins of the “replisome” machines that duplicate DNA in bacteria, archaea and eukarya, with an eye to understanding the issues surrounding the evolution of the DNA replication apparatus. PMID:27160337
Machine Shop Grinding Machines.
Dunn, James
This curriculum manual is one in a series of machine shop curriculum manuals intended for use in full-time secondary and postsecondary classes, as well as part-time adult classes. The curriculum can also be adapted to open-entry, open-exit programs. Its purpose is to equip students with basic knowledge and skills that will enable them to enter the…
On Rational Interpolation-Based List-Decoding and List-Decoding Binary Goppa Codes
DEFF Research Database (Denmark)
Beelen, Peter; Høholdt, Tom; Nielsen, Johan Sebastian Rosenkilde
2013-01-01
We derive the Wu list-decoding algorithm for generalized Reed–Solomon (GRS) codes by using Gröbner bases over modules and the Euclidean algorithm as the initial algorithm instead of the Berlekamp–Massey algorithm. We present a novel method for constructing the interpolation polynomial fast. We gi...... and a duality in the choice of parameters needed for decoding, both in the case of GRS codes and in the case of Goppa codes....
Superior arm-movement decoding from cortex with a new, unsupervised-learning algorithm
Makin, Joseph G.; O'Doherty, Joseph E.; Cardoso, Mariana M. B.; Sabes, Philip N.
2018-04-01
Objective. The aim of this work is to improve the state of the art for motor-control with a brain-machine interface (BMI). BMIs use neurological recording devices and decoding algorithms to transform brain activity directly into real-time control of a machine, archetypically a robotic arm or a cursor. The standard procedure treats neural activity—vectors of spike counts in small temporal windows—as noisy observations of the kinematic state (position, velocity, acceleration) of the fingertip. Inferring the state from the observations then takes the form of a dynamical filter, typically some variant on Kalman’s (KF). The KF, however, although fairly robust in practice, is optimal only when the relationships between variables are linear and the noise is Gaussian, conditions usually violated in practice. Approach. To overcome these limitations we introduce a new filter, the ‘recurrent exponential-family harmonium’ (rEFH), that models the spike counts explicitly as Poisson-distributed, and allows for arbitrary nonlinear dynamics and observation models. Furthermore, the model underlying the filter is acquired through unsupervised learning, which allows temporal correlations in spike counts to be explained by latent dynamics that do not necessarily correspond to the kinematic state of the fingertip. Main results. We test the rEFH on offline reconstruction of the kinematics of reaches in the plane. The rEFH outperforms the standard, as well as three other state-of-the-art, decoders, across three monkeys, two different tasks, most kinematic variables, and a range of bin widths, amounts of training data, and numbers of neurons. Significance. Our algorithm establishes a new state of the art for offline decoding of reaches—in particular, for fingertip velocities, the variable used for control in most online decoders.
Bayesian population decoding of spiking neurons.
Gerwinn, Sebastian; Macke, Jakob; Bethge, Matthias
2009-01-01
The timing of action potentials in spiking neurons depends on the temporal dynamics of their inputs and contains information about temporal fluctuations in the stimulus. Leaky integrate-and-fire neurons constitute a popular class of encoding models, in which spike times depend directly on the temporal structure of the inputs. However, optimal decoding rules for these models have only been studied explicitly in the noiseless case. Here, we study decoding rules for probabilistic inference of a continuous stimulus from the spike times of a population of leaky integrate-and-fire neurons with threshold noise. We derive three algorithms for approximating the posterior distribution over stimuli as a function of the observed spike trains. In addition to a reconstruction of the stimulus we thus obtain an estimate of the uncertainty as well. Furthermore, we derive a 'spike-by-spike' online decoding scheme that recursively updates the posterior with the arrival of each new spike. We use these decoding rules to reconstruct time-varying stimuli represented by a Gaussian process from spike trains of single neurons as well as neural populations.
Faster 2-regular information-set decoding
Bernstein, D.J.; Lange, T.; Peters, C.P.; Schwabe, P.; Chee, Y.M.
2011-01-01
Fix positive integers B and w. Let C be a linear code over F 2 of length Bw. The 2-regular-decoding problem is to find a nonzero codeword consisting of w length-B blocks, each of which has Hamming weight 0 or 2. This problem appears in attacks on the FSB (fast syndrome-based) hash function and
Bayesian population decoding of spiking neurons
Directory of Open Access Journals (Sweden)
Sebastian Gerwinn
2009-10-01
Full Text Available The timing of action potentials in spiking neurons depends on the temporal dynamics of their inputs and contains information about temporal fluctuations in the stimulus. Leaky integrate-and-fire neurons constitute a popular class of encoding models, in which spike times depend directly on the temporal structure of the inputs. However, optimal decoding rules for these models have only been studied explicitly in the noiseless case. Here, we study decoding rules for probabilistic inference of a continuous stimulus from the spike times of a population of leaky integrate-and-fire neurons with threshold noise. We derive three algorithms for approximating the posterior distribution over stimuli as a function of the observed spike trains. In addition to a reconstruction of the stimulus we thus obtain an estimate of the uncertainty as well. Furthermore, we derive a `spike-by-spike' online decoding scheme that recursively updates the posterior with the arrival of each new spike. We use these decoding rules to reconstruct time-varying stimuli represented by a Gaussian process from spike trains of single neurons as well as neural populations.
2010-10-01
..., satellite, public switched telephone network, or any other source that uses the EAS protocol. (2) Valid..., analog radio and television broadcast stations, analog cable systems and wireless cable systems may... program data must be retained even with power removed. (7) Outputs. Decoders shall have the following...
Older Adults Have Difficulty in Decoding Sarcasm
Phillips, Louise H.; Allen, Roy; Bull, Rebecca; Hering, Alexandra; Kliegel, Matthias; Channon, Shelley
2015-01-01
Younger and older adults differ in performance on a range of social-cognitive skills, with older adults having difficulties in decoding nonverbal cues to emotion and intentions. Such skills are likely to be important when deciding whether someone is being sarcastic. In the current study we investigated in a life span sample whether there are…
Bounded-Angle Iterative Decoding of LDPC Codes
Dolinar, Samuel; Andrews, Kenneth; Pollara, Fabrizio; Divsalar, Dariush
2009-01-01
Bounded-angle iterative decoding is a modified version of conventional iterative decoding, conceived as a means of reducing undetected-error rates for short low-density parity-check (LDPC) codes. For a given code, bounded-angle iterative decoding can be implemented by means of a simple modification of the decoder algorithm, without redesigning the code. Bounded-angle iterative decoding is based on a representation of received words and code words as vectors in an n-dimensional Euclidean space (where n is an integer).
A Scalable Architecture of a Structured LDPC Decoder
Lee, Jason Kwok-San; Lee, Benjamin; Thorpe, Jeremy; Andrews, Kenneth; Dolinar, Sam; Hamkins, Jon
2004-01-01
We present a scalable decoding architecture for a certain class of structured LDPC codes. The codes are designed using a small (n,r) protograph that is replicated Z times to produce a decoding graph for a (Z x n, Z x r) code. Using this architecture, we have implemented a decoder for a (4096,2048) LDPC code on a Xilinx Virtex-II 2000 FPGA, and achieved decoding speeds of 31 Mbps with 10 fixed iterations. The implemented message-passing algorithm uses an optimized 3-bit non-uniform quantizer that operates with 0.2dB implementation loss relative to a floating point decoder.
Sequential stochastic optimization
Cairoli, Renzo
1996-01-01
Sequential Stochastic Optimization provides mathematicians and applied researchers with a well-developed framework in which stochastic optimization problems can be formulated and solved. Offering much material that is either new or has never before appeared in book form, it lucidly presents a unified theory of optimal stopping and optimal sequential control of stochastic processes. This book has been carefully organized so that little prior knowledge of the subject is assumed; its only prerequisites are a standard graduate course in probability theory and some familiarity with discrete-paramet
SYMBOL LEVEL DECODING FOR DUO-BINARY TURBO CODES
Directory of Open Access Journals (Sweden)
Yogesh Beeharry
2017-05-01
Full Text Available This paper investigates the performance of three different symbol level decoding algorithms for Duo-Binary Turbo codes. Explicit details of the computations involved in the three decoding techniques, and a computational complexity analysis are given. Simulation results with different couple lengths, code-rates, and QPSK modulation reveal that the symbol level decoding with bit-level information outperforms the symbol level decoding by 0.1 dB on average in the error floor region. Moreover, a complexity analysis reveals that symbol level decoding with bit-level information reduces the decoding complexity by 19.6 % in terms of the total number of computations required for each half-iteration as compared to symbol level decoding.
Lin, Shu; Fossorier, Marc
1998-01-01
In a coded communication system with equiprobable signaling, MLD minimizes the word error probability and delivers the most likely codeword associated with the corresponding received sequence. This decoding has two drawbacks. First, minimization of the word error probability is not equivalent to minimization of the bit error probability. Therefore, MLD becomes suboptimum with respect to the bit error probability. Second, MLD delivers a hard-decision estimate of the received sequence, so that information is lost between the input and output of the ML decoder. This information is important in coded schemes where the decoded sequence is further processed, such as concatenated coding schemes, multi-stage and iterative decoding schemes. In this chapter, we first present a decoding algorithm which both minimizes bit error probability, and provides the corresponding soft information at the output of the decoder. This algorithm is referred to as the MAP (maximum aposteriori probability) decoding algorithm.
Sequential memory: Binding dynamics
Afraimovich, Valentin; Gong, Xue; Rabinovich, Mikhail
2015-10-01
Temporal order memories are critical for everyday animal and human functioning. Experiments and our own experience show that the binding or association of various features of an event together and the maintaining of multimodality events in sequential order are the key components of any sequential memories—episodic, semantic, working, etc. We study a robustness of binding sequential dynamics based on our previously introduced model in the form of generalized Lotka-Volterra equations. In the phase space of the model, there exists a multi-dimensional binding heteroclinic network consisting of saddle equilibrium points and heteroclinic trajectories joining them. We prove here the robustness of the binding sequential dynamics, i.e., the feasibility phenomenon for coupled heteroclinic networks: for each collection of successive heteroclinic trajectories inside the unified networks, there is an open set of initial points such that the trajectory going through each of them follows the prescribed collection staying in a small neighborhood of it. We show also that the symbolic complexity function of the system restricted to this neighborhood is a polynomial of degree L - 1, where L is the number of modalities.
Sequential Dependencies in Driving
Doshi, Anup; Tran, Cuong; Wilder, Matthew H.; Mozer, Michael C.; Trivedi, Mohan M.
2012-01-01
The effect of recent experience on current behavior has been studied extensively in simple laboratory tasks. We explore the nature of sequential effects in the more naturalistic setting of automobile driving. Driving is a safety-critical task in which delayed response times may have severe consequences. Using a realistic driving simulator, we find…
Mining compressing sequential problems
Hoang, T.L.; Mörchen, F.; Fradkin, D.; Calders, T.G.K.
2012-01-01
Compression based pattern mining has been successfully applied to many data mining tasks. We propose an approach based on the minimum description length principle to extract sequential patterns that compress a database of sequences well. We show that mining compressing patterns is NP-Hard and
Sequential Analysis of Metals in Municipal Dumpsite Composts of ...
African Journals Online (AJOL)
... Ni) in Municipal dumpsite compost were determined by the sequential extraction method. Chemical parameters such as pH, conductivity, and organic carbon contents of the samples were also determined. Analysis of the extracts was carried out by atomic absorption spectrophotometer machine (Buck Scientific VPG 210).
Pass-transistor asynchronous sequential circuits
Whitaker, Sterling R.; Maki, Gary K.
1989-01-01
Design methods for asynchronous sequential pass-transistor circuits, which result in circuits that are hazard- and critical-race-free and which have added degrees of freedom for the input signals, are discussed. The design procedures are straightforward and easy to implement. Two single-transition-time state assignment methods are presented, and hardware bounds for each are established. A surprising result is that the hardware realizations for each next state variable and output variable is identical for a given flow table. Thus, a state machine with N states and M outputs can be constructed using a single layout replicated N + M times.
Video coding for decoding power-constrained embedded devices
Lu, Ligang; Sheinin, Vadim
2004-01-01
Low power dissipation and fast processing time are crucial requirements for embedded multimedia devices. This paper presents a technique in video coding to decrease the power consumption at a standard video decoder. Coupled with a small dedicated video internal memory cache on a decoder, the technique can substantially decrease the amount of data traffic to the external memory at the decoder. A decrease in data traffic to the external memory at decoder will result in multiple benefits: faster real-time processing and power savings. The encoder, given prior knowledge of the decoder"s dedicated video internal memory cache management scheme, regulates its choice of motion compensated predictors to reduce the decoder"s external memory accesses. This technique can be used in any standard or proprietary encoder scheme to generate a compliant output bit stream decodable by standard CPU-based and dedicated hardware-based decoders for power savings with the best quality-power cost trade off. Our simulation results show that with a relatively small amount of dedicated video internal memory cache, the technique may decrease the traffic between CPU and external memory over 50%.
Decoding spikes in a spiking neuronal network
Energy Technology Data Exchange (ETDEWEB)
Feng Jianfeng [Department of Informatics, University of Sussex, Brighton BN1 9QH (United Kingdom); Ding, Mingzhou [Department of Mathematics, Florida Atlantic University, Boca Raton, FL 33431 (United States)
2004-06-04
We investigate how to reliably decode the input information from the output of a spiking neuronal network. A maximum likelihood estimator of the input signal, together with its Fisher information, is rigorously calculated. The advantage of the maximum likelihood estimation over the 'brute-force rate coding' estimate is clearly demonstrated. It is pointed out that the ergodic assumption in neuroscience, i.e. a temporal average is equivalent to an ensemble average, is in general not true. Averaging over an ensemble of neurons usually gives a biased estimate of the input information. A method on how to compensate for the bias is proposed. Reconstruction of dynamical input signals with a group of spiking neurons is extensively studied and our results show that less than a spike is sufficient to accurately decode dynamical inputs.
Decoding spikes in a spiking neuronal network
International Nuclear Information System (INIS)
Feng Jianfeng; Ding, Mingzhou
2004-01-01
We investigate how to reliably decode the input information from the output of a spiking neuronal network. A maximum likelihood estimator of the input signal, together with its Fisher information, is rigorously calculated. The advantage of the maximum likelihood estimation over the 'brute-force rate coding' estimate is clearly demonstrated. It is pointed out that the ergodic assumption in neuroscience, i.e. a temporal average is equivalent to an ensemble average, is in general not true. Averaging over an ensemble of neurons usually gives a biased estimate of the input information. A method on how to compensate for the bias is proposed. Reconstruction of dynamical input signals with a group of spiking neurons is extensively studied and our results show that less than a spike is sufficient to accurately decode dynamical inputs
Power decoding Reed-Solomon codes up to the Johnson radius
DEFF Research Database (Denmark)
Rosenkilde, Johan Sebastian Heesemann
2018-01-01
Power decoding, or "decoding using virtual interleaving" is a technique for decoding Reed-Solomon codes up to the Sudan radius. Since the method's inception, it has been an open question if it is possible to use this approach to decode up to the Johnson radius - the decoding radius of the Guruswami...
Directory of Open Access Journals (Sweden)
Jiri eHammer
2013-11-01
Full Text Available In neuronal population signals, including the electroencephalogram (EEG and electrocorticogram (ECoG, the low-frequency component (LFC is particularly informative about motor behavior and can be used for decoding movement parameters for brain-machine interface (BMI applications. An idea previously expressed, but as of yet not quantitatively tested, is that it is the LFC phase that is the main source of decodable information. To test this issue, we analyzed human ECoG recorded during a game-like, one-dimensional, continuous motor task with a novel decoding method suitable for unfolding magnitude and phase explicitly into a complex-valued, time-frequency signal representation, enabling quantification of the decodable information within the temporal, spatial and frequency domains and allowing disambiguation of the phase contribution from that of the spectral magnitude. The decoding accuracy based only on phase information was substantially (at least 2 fold and significantly higher than that based only on magnitudes for position, velocity and acceleration. The frequency profile of movement-related information in the ECoG data matched well with the frequency profile expected when assuming a close time-domain correlate of movement velocity in the ECoG, e.g., a (noisy copy of hand velocity. No such match was observed with the frequency profiles expected when assuming a copy of either hand position or acceleration. There was also no indication of additional magnitude-based mechanisms encoding movement information in the LFC range. Thus, our study contributes to elucidating the nature of the informative low-frequency component of motor cortical population activity and may hence contribute to improve decoding strategies and BMI performance.
Resource Efficient LDPC Decoders for Multimedia Communication
Chandrasetty, Vikram Arkalgud; Aziz, Syed Mahfuzul
2013-01-01
Achieving high image quality is an important aspect in an increasing number of wireless multimedia applications. These applications require resource efficient error correction hardware to detect and correct errors introduced by the communication channel. This paper presents an innovative flexible architecture for error correction using Low-Density Parity-Check (LDPC) codes. The proposed partially-parallel decoder architecture utilizes a novel code construction technique based on multi-level H...
Decoding divergent series in nonparaxial optics.
Borghi, Riccardo; Gori, Franco; Guattari, Giorgio; Santarsiero, Massimo
2011-03-15
A theoretical analysis aimed at investigating the divergent character of perturbative series involved in the study of free-space nonparaxial propagation of vectorial optical beams is proposed. Our analysis predicts a factorial divergence for such series and provides a theoretical framework within which the results of recently published numerical experiments concerning nonparaxial propagation of vectorial Gaussian beams find a meaningful interpretation in terms of the decoding operated on such series by the Weniger transformation.
Noise-robust speech recognition through auditory feature detection and spike sequence decoding.
Schafer, Phillip B; Jin, Dezhe Z
2014-03-01
Speech recognition in noisy conditions is a major challenge for computer systems, but the human brain performs it routinely and accurately. Automatic speech recognition (ASR) systems that are inspired by neuroscience can potentially bridge the performance gap between humans and machines. We present a system for noise-robust isolated word recognition that works by decoding sequences of spikes from a population of simulated auditory feature-detecting neurons. Each neuron is trained to respond selectively to a brief spectrotemporal pattern, or feature, drawn from the simulated auditory nerve response to speech. The neural population conveys the time-dependent structure of a sound by its sequence of spikes. We compare two methods for decoding the spike sequences--one using a hidden Markov model-based recognizer, the other using a novel template-based recognition scheme. In the latter case, words are recognized by comparing their spike sequences to template sequences obtained from clean training data, using a similarity measure based on the length of the longest common sub-sequence. Using isolated spoken digits from the AURORA-2 database, we show that our combined system outperforms a state-of-the-art robust speech recognizer at low signal-to-noise ratios. Both the spike-based encoding scheme and the template-based decoding offer gains in noise robustness over traditional speech recognition methods. Our system highlights potential advantages of spike-based acoustic coding and provides a biologically motivated framework for robust ASR development.
Decoding of top-down cognitive processing for SSVEP-controlled BMI
Min, Byoung-Kyong; Dähne, Sven; Ahn, Min-Hee; Noh, Yung-Kyun; Müller, Klaus-Robert
2016-11-01
We present a fast and accurate non-invasive brain-machine interface (BMI) based on demodulating steady-state visual evoked potentials (SSVEPs) in electroencephalography (EEG). Our study reports an SSVEP-BMI that, for the first time, decodes primarily based on top-down and not bottom-up visual information processing. The experimental setup presents a grid-shaped flickering line array that the participants observe while intentionally attending to a subset of flickering lines representing the shape of a letter. While the flickering pixels stimulate the participant’s visual cortex uniformly with equal probability, the participant’s intention groups the strokes and thus perceives a ‘letter Gestalt’. We observed decoding accuracy of 35.81% (up to 65.83%) with a regularized linear discriminant analysis; on average 2.05-fold, and up to 3.77-fold greater than chance levels in multi-class classification. Compared to the EEG signals, an electrooculogram (EOG) did not significantly contribute to decoding accuracies. Further analysis reveals that the top-down SSVEP paradigm shows the most focalised activation pattern around occipital visual areas; Granger causality analysis consistently revealed prefrontal top-down control over early visual processing. Taken together, the present paradigm provides the first neurophysiological evidence for the top-down SSVEP BMI paradigm, which potentially enables multi-class intentional control of EEG-BMIs without using gaze-shifting.
Behavioral decoding of working memory items inside and outside the focus of attention.
Mallett, Remington; Lewis-Peacock, Jarrod A
2018-03-31
How we attend to our thoughts affects how we attend to our environment. Holding information in working memory can automatically bias visual attention toward matching information. By observing attentional biases on reaction times to visual search during a memory delay, it is possible to reconstruct the source of that bias using machine learning techniques and thereby behaviorally decode the content of working memory. Can this be done when more than one item is held in working memory? There is some evidence that multiple items can simultaneously bias attention, but the effects have been inconsistent. One explanation may be that items are stored in different states depending on the current task demands. Recent models propose functionally distinct states of representation for items inside versus outside the focus of attention. Here, we use behavioral decoding to evaluate whether multiple memory items-including temporarily irrelevant items outside the focus of attention-exert biases on visual attention. Only the single item in the focus of attention was decodable. The other item showed a brief attentional bias that dissipated until it returned to the focus of attention. These results support the idea of dynamic, flexible states of working memory across time and priority. © 2018 New York Academy of Sciences.
Markov source model for printed music decoding
Kopec, Gary E.; Chou, Philip A.; Maltz, David A.
1995-03-01
This paper describes a Markov source model for a simple subset of printed music notation. The model is based on the Adobe Sonata music symbol set and a message language of our own design. Chord imaging is the most complex part of the model. Much of the complexity follows from a rule of music typography that requires the noteheads for adjacent pitches to be placed on opposite sides of the chord stem. This rule leads to a proliferation of cases for other typographic details such as dot placement. We describe the language of message strings accepted by the model and discuss some of the imaging issues associated with various aspects of the message language. We also point out some aspects of music notation that appear problematic for a finite-state representation. Development of the model was greatly facilitated by the duality between image synthesis and image decoding. Although our ultimate objective was a music image model for use in decoding, most of the development proceeded by using the evolving model for image synthesis, since it is computationally far less costly to image a message than to decode an image.
Sequential Power-Dependence Theory
Buskens, Vincent; Rijt, Arnout van de
2008-01-01
Existing methods for predicting resource divisions in laboratory exchange networks do not take into account the sequential nature of the experimental setting. We extend network exchange theory by considering sequential exchange. We prove that Sequential Power-Dependence Theory—unlike
Modelling sequentially scored item responses
Akkermans, W.
2000-01-01
The sequential model can be used to describe the variable resulting from a sequential scoring process. In this paper two more item response models are investigated with respect to their suitability for sequential scoring: the partial credit model and the graded response model. The investigation is
2017-01-01
This book provides an overview on current sustainable machining. Its chapters cover the concept in economic, social and environmental dimensions. It provides the reader with proper ways to handle several pollutants produced during the machining process. The book is useful on both undergraduate and postgraduate levels and it is of interest to all those working with manufacturing and machining technology.
Deep Learning Methods for Improved Decoding of Linear Codes
Nachmani, Eliya; Marciano, Elad; Lugosch, Loren; Gross, Warren J.; Burshtein, David; Be'ery, Yair
2018-02-01
The problem of low complexity, close to optimal, channel decoding of linear codes with short to moderate block length is considered. It is shown that deep learning methods can be used to improve a standard belief propagation decoder, despite the large example space. Similar improvements are obtained for the min-sum algorithm. It is also shown that tying the parameters of the decoders across iterations, so as to form a recurrent neural network architecture, can be implemented with comparable results. The advantage is that significantly less parameters are required. We also introduce a recurrent neural decoder architecture based on the method of successive relaxation. Improvements over standard belief propagation are also observed on sparser Tanner graph representations of the codes. Furthermore, we demonstrate that the neural belief propagation decoder can be used to improve the performance, or alternatively reduce the computational complexity, of a close to optimal decoder of short BCH codes.
Decoding Delay Controlled Completion Time Reduction in Instantly Decodable Network Coding
Douik, Ahmed
2016-06-27
For several years, the completion time and the decoding delay problems in Instantly Decodable Network Coding (IDNC) were considered separately and were thought to act completely against each other. Recently, some works aimed to balance the effects of these two important IDNC metrics but none of them studied a further optimization of one by controlling the other. This paper investigates the effect of controlling the decoding delay to reduce the completion time below its currently best-known solution in both perfect and imperfect feedback with persistent erasure channels. To solve the problem, the decodingdelay- dependent expressions of the users’ and overall completion times are derived in the complete feedback scenario. Although using such expressions to find the optimal overall completion time is NP-hard, the paper proposes two novel heuristics that minimizes the probability of increasing the maximum of these decoding-delay-dependent completion time expressions after each transmission through a layered control of their decoding delays. Afterward, the paper extends the study to the imperfect feedback scenario in which uncertainties at the sender affects its ability to anticipate accurately the decoding delay increase at each user. The paper formulates the problem in such environment and derives the expression of the minimum increase in the completion time. Simulation results show the performance of the proposed solutions and suggest that both heuristics achieves a lower mean completion time as compared to the best-known heuristics for the completion time reduction in perfect and imperfect feedback. The gap in performance becomes more significant as the erasure of the channel increases.
Decoding Delay Controlled Completion Time Reduction in Instantly Decodable Network Coding
Douik, Ahmed S.; Sorour, Sameh; Al-Naffouri, Tareq Y.; Alouini, Mohamed-Slim
2016-01-01
For several years, the completion time and the decoding delay problems in Instantly Decodable Network Coding (IDNC) were considered separately and were thought to act completely against each other. Recently, some works aimed to balance the effects of these two important IDNC metrics but none of them studied a further optimization of one by controlling the other. This paper investigates the effect of controlling the decoding delay to reduce the completion time below its currently best-known solution in both perfect and imperfect feedback with persistent erasure channels. To solve the problem, the decodingdelay- dependent expressions of the users’ and overall completion times are derived in the complete feedback scenario. Although using such expressions to find the optimal overall completion time is NP-hard, the paper proposes two novel heuristics that minimizes the probability of increasing the maximum of these decoding-delay-dependent completion time expressions after each transmission through a layered control of their decoding delays. Afterward, the paper extends the study to the imperfect feedback scenario in which uncertainties at the sender affects its ability to anticipate accurately the decoding delay increase at each user. The paper formulates the problem in such environment and derives the expression of the minimum increase in the completion time. Simulation results show the performance of the proposed solutions and suggest that both heuristics achieves a lower mean completion time as compared to the best-known heuristics for the completion time reduction in perfect and imperfect feedback. The gap in performance becomes more significant as the erasure of the channel increases.
Observations on Polar Coding with CRC-Aided List Decoding
2016-09-01
TECHNICAL REPORT 3041 September 2016 Observations on Polar Coding with CRC-Aided List Decoding David Wasserman Approved for public release. SSC...described in [2, 3]. In FY15 and FY16 we used cyclic redundancy check (CRC)-aided polar list decoding [4]. Section 2 describes the basics of polar coding ...and gives details of the encoders and decoders we used. In the course of our research, we performed simulations of polar codes in hundreds of cases
Polar Coding with CRC-Aided List Decoding
2015-08-01
TECHNICAL REPORT 2087 August 2015 Polar Coding with CRC-Aided List Decoding David Wasserman Approved...list decoding . RESULTS Our simulation results show that polar coding can produce results very similar to the FEC used in the Digital Video...standard. RECOMMENDATIONS In any application for which the DVB-S2 FEC is considered, polar coding with CRC-aided list decod - ing with N = 65536
A quantum algorithm for Viterbi decoding of classical convolutional codes
Grice, Jon R.; Meyer, David A.
2014-01-01
We present a quantum Viterbi algorithm (QVA) with better than classical performance under certain conditions. In this paper the proposed algorithm is applied to decoding classical convolutional codes, for instance; large constraint length $Q$ and short decode frames $N$. Other applications of the classical Viterbi algorithm where $Q$ is large (e.g. speech processing) could experience significant speedup with the QVA. The QVA exploits the fact that the decoding trellis is similar to the butter...
Design of a VLSI Decoder for Partially Structured LDPC Codes
Directory of Open Access Journals (Sweden)
Fabrizio Vacca
2008-01-01
of their parity matrix can be partitioned into two disjoint sets, namely, the structured and the random ones. For the proposed class of codes a constructive design method is provided. To assess the value of this method the constructed codes performance are presented. From these results, a novel decoding method called split decoding is introduced. Finally, to prove the effectiveness of the proposed approach a whole VLSI decoder is designed and characterized.
Interpolation decoding method with variable parameters for fractal image compression
International Nuclear Information System (INIS)
He Chuanjiang; Li Gaoping; Shen Xiaona
2007-01-01
The interpolation fractal decoding method, which is introduced by [He C, Yang SX, Huang X. Progressive decoding method for fractal image compression. IEE Proc Vis Image Signal Process 2004;3:207-13], involves generating progressively the decoded image by means of an interpolation iterative procedure with a constant parameter. It is well-known that the majority of image details are added at the first steps of iterations in the conventional fractal decoding; hence the constant parameter for the interpolation decoding method must be set as a smaller value in order to achieve a better progressive decoding. However, it needs to take an extremely large number of iterations to converge. It is thus reasonable for some applications to slow down the iterative process at the first stages of decoding and then to accelerate it afterwards (e.g., at some iteration as we need). To achieve the goal, this paper proposed an interpolation decoding scheme with variable (iteration-dependent) parameters and proved the convergence of the decoding process mathematically. Experimental results demonstrate that the proposed scheme has really achieved the above-mentioned goal
Joint Decoding of Concatenated VLEC and STTC System
Directory of Open Access Journals (Sweden)
Chen Huijun
2008-01-01
Full Text Available Abstract We consider the decoding of wireless communication systems with both source coding in the application layer and channel coding in the physical layer for high-performance transmission over fading channels. Variable length error correcting codes (VLECs and space time trellis codes (STTCs are used to provide bandwidth efficient data compression as well as coding and diversity gains. At the receiver, an iterative joint source and space time decoding scheme are developed to utilize redundancy in both STTC and VLEC to improve overall decoding performance. Issues such as the inseparable systematic information in the symbol level, the asymmetric trellis structure of VLEC, and information exchange between bit and symbol domains have been considered in the maximum a posteriori probability (MAP decoding algorithm. Simulation results indicate that the developed joint decoding scheme achieves a significant decoding gain over the separate decoding in fading channels, whether or not the channel information is perfectly known at the receiver. Furthermore, how rate allocation between STTC and VLEC affects the performance of the joint source and space-time decoder is investigated. Different systems with a fixed overall information rate are studied. It is shown that for a system with more redundancy dedicated to the source code and a higher order modulation of STTC, the joint decoding yields better performance, though with increased complexity.
Joint Decoding of Concatenated VLEC and STTC System
Directory of Open Access Journals (Sweden)
Huijun Chen
2008-07-01
Full Text Available We consider the decoding of wireless communication systems with both source coding in the application layer and channel coding in the physical layer for high-performance transmission over fading channels. Variable length error correcting codes (VLECs and space time trellis codes (STTCs are used to provide bandwidth efficient data compression as well as coding and diversity gains. At the receiver, an iterative joint source and space time decoding scheme are developed to utilize redundancy in both STTC and VLEC to improve overall decoding performance. Issues such as the inseparable systematic information in the symbol level, the asymmetric trellis structure of VLEC, and information exchange between bit and symbol domains have been considered in the maximum a posteriori probability (MAP decoding algorithm. Simulation results indicate that the developed joint decoding scheme achieves a significant decoding gain over the separate decoding in fading channels, whether or not the channel information is perfectly known at the receiver. Furthermore, how rate allocation between STTC and VLEC affects the performance of the joint source and space-time decoder is investigated. Different systems with a fixed overall information rate are studied. It is shown that for a system with more redundancy dedicated to the source code and a higher order modulation of STTC, the joint decoding yields better performance, though with increased complexity.
Grasp movement decoding from premotor and parietal cortex.
Townsend, Benjamin R; Subasi, Erk; Scherberger, Hansjörg
2011-10-05
Despite recent advances in harnessing cortical motor-related activity to control computer cursors and robotic devices, the ability to decode and execute different grasping patterns remains a major obstacle. Here we demonstrate a simple Bayesian decoder for real-time classification of grip type and wrist orientation in macaque monkeys that uses higher-order planning signals from anterior intraparietal cortex (AIP) and ventral premotor cortex (area F5). Real-time decoding was based on multiunit signals, which had similar tuning properties to cells in previous single-unit recording studies. Maximum decoding accuracy for two grasp types (power and precision grip) and five wrist orientations was 63% (chance level, 10%). Analysis of decoder performance showed that grip type decoding was highly accurate (90.6%), with most errors occurring during orientation classification. In a subsequent off-line analysis, we found small but significant performance improvements (mean, 6.25 percentage points) when using an optimized spike-sorting method (superparamagnetic clustering). Furthermore, we observed significant differences in the contributions of F5 and AIP for grasp decoding, with F5 being better suited for classification of the grip type and AIP contributing more toward decoding of object orientation. However, optimum decoding performance was maximal when using neural activity simultaneously from both areas. Overall, these results highlight quantitative differences in the functional representation of grasp movements in AIP and F5 and represent a first step toward using these signals for developing functional neural interfaces for hand grasping.
Sub-quadratic decoding of one-point hermitian codes
DEFF Research Database (Denmark)
Nielsen, Johan Sebastian Rosenkilde; Beelen, Peter
2015-01-01
We present the first two sub-quadratic complexity decoding algorithms for one-point Hermitian codes. The first is based on a fast realization of the Guruswami-Sudan algorithm using state-of-the-art algorithms from computer algebra for polynomial-ring matrix minimization. The second is a power...... decoding algorithm: an extension of classical key equation decoding which gives a probabilistic decoding algorithm up to the Sudan radius. We show how the resulting key equations can be solved by the matrix minimization algorithms from computer algebra, yielding similar asymptotic complexities....
International Nuclear Information System (INIS)
Yoshida, Toshihiro
1981-01-01
Probabilities of meson production in the sequential decay of Reggeons, which are formed from the projectile and the target in the hadron-hadron to Reggeon-Reggeon processes, are investigated. It is assumed that pair creation of heavy quarks and simultaneous creation of two antiquark-quark pairs are negligible. The leading-order terms with respect to ratio of creation probabilities of anti s s to anti u u (anti d d) are calculated. The production cross sections in the target fragmentation region are given in terms of probabilities in the initial decay of the Reggeons and an effect of manyparticle production. (author)
Brain-to-text: Decoding spoken phrases from phone representations in the brain
Directory of Open Access Journals (Sweden)
Christian eHerff
2015-06-01
Full Text Available It has long been speculated whether communication between humans and machines based on natural speech related cortical activity is possible. Over the past decade, studies have suggested that it is feasible to recognize isolated aspects of speech from neural signals, such as auditory features, phones or one of a few isolated words. However, until now it remained an unsolved challenge to decode continuously spoken speech from the neural substrate associated with speech and language processing. Here, we show for the first time that continuously spoken speech can be decoded into the expressed words from intracranial electrocorticographic (ECoG recordings. Specifically, we implemented a system, which we call Brain-To-Text that models single phones, employs techniques from automatic speech recognition (ASR, and thereby transforms brain activity while speaking into the corresponding textual representation. Our results demonstrate that our system achieved word error rates as low as 25% and phone error rates below 50%. Additionally, our approach contributes to the current understanding of the neural basis of continuous speech production by identifying those cortical regions that hold substantial information about individual phones. In conclusion, the Brain-To-Text system described in this paper represents an important step towards human-machine communication based on imagined speech.
Synthetic Aperture Sequential Beamforming
DEFF Research Database (Denmark)
Kortbek, Jacob; Jensen, Jørgen Arendt; Gammelmark, Kim Løkke
2008-01-01
A synthetic aperture focusing (SAF) technique denoted Synthetic Aperture Sequential Beamforming (SASB) suitable for 2D and 3D imaging is presented. The technique differ from prior art of SAF in the sense that SAF is performed on pre-beamformed data contrary to channel data. The objective is to im......A synthetic aperture focusing (SAF) technique denoted Synthetic Aperture Sequential Beamforming (SASB) suitable for 2D and 3D imaging is presented. The technique differ from prior art of SAF in the sense that SAF is performed on pre-beamformed data contrary to channel data. The objective...... is to improve and obtain a more range independent lateral resolution compared to conventional dynamic receive focusing (DRF) without compromising frame rate. SASB is a two-stage procedure using two separate beamformers. First a set of Bmode image lines using a single focal point in both transmit and receive...... is stored. The second stage applies the focused image lines from the first stage as input data. The SASB method has been investigated using simulations in Field II and by off-line processing of data acquired with a commercial scanner. The performance of SASB with a static image object is compared with DRF...
Sudan-decoding generalized geometric Goppa codes
DEFF Research Database (Denmark)
Heydtmann, Agnes Eileen
2003-01-01
Generalized geometric Goppa codes are vector spaces of n-tuples with entries from different extension fields of a ground field. They are derived from evaluating functions similar to conventional geometric Goppa codes, but allowing evaluation in places of arbitrary degree. A decoding scheme...... for these codes based on Sudan's improved algorithm is presented and its error-correcting capacity is analyzed. For the implementation of the algorithm it is necessary that the so-called increasing zero bases of certain spaces of functions are available. A method to obtain such bases is developed....
Memory-efficient decoding of LDPC codes
Kwok-San Lee, Jason; Thorpe, Jeremy; Hawkins, Jon
2005-01-01
We present a low-complexity quantization scheme for the implementation of regular (3,6) LDPC codes. The quantization parameters are optimized to maximize the mutual information between the source and the quantized messages. Using this non-uniform quantized belief propagation algorithm, we have simulated that an optimized 3-bit quantizer operates with 0.2dB implementation loss relative to a floating point decoder, and an optimized 4-bit quantizer operates less than 0.1dB quantization loss.
[Modulation of Metacognition with Decoded Neurofeedback].
Koizumi, Ai; Cortese, Aurelio; Amano, Kaoru; Kawato, Mitsuo; Lau, Hakwan
2017-12-01
Humans often assess their confidence in their own perception, e.g., feeling "confident" or "certain" of having seen a friend, or feeling "uncertain" about whether the phone rang. The neural mechanism underlying the metacognitive function that reflects subjective perception still remains under debate. We have previously used decoded neurofeedback (DecNef) to demonstrate that manipulating the multivoxel activation patterns in the frontoparietal network modulates perceptual confidence without affecting perceptual performance. The results provided clear evidence for a dissociation between perceptual confidence and performance and suggested a distinct role of the frontoparietal network in metacognition.
Maximum a posteriori decoder for digital communications
Altes, Richard A. (Inventor)
1997-01-01
A system and method for decoding by identification of the most likely phase coded signal corresponding to received data. The present invention has particular application to communication with signals that experience spurious random phase perturbations. The generalized estimator-correlator uses a maximum a posteriori (MAP) estimator to generate phase estimates for correlation with incoming data samples and for correlation with mean phases indicative of unique hypothesized signals. The result is a MAP likelihood statistic for each hypothesized transmission, wherein the highest value statistic identifies the transmitted signal.
Graybill, George
2007-01-01
Just how simple are simple machines? With our ready-to-use resource, they are simple to teach and easy to learn! Chocked full of information and activities, we begin with a look at force, motion and work, and examples of simple machines in daily life are given. With this background, we move on to different kinds of simple machines including: Levers, Inclined Planes, Wedges, Screws, Pulleys, and Wheels and Axles. An exploration of some compound machines follows, such as the can opener. Our resource is a real time-saver as all the reading passages, student activities are provided. Presented in s
Vectorization of Reed Solomon decoding and mapping on the EVP
Kumar, A.; Berkel, van C.H.
2008-01-01
Reed Solomon (RS) codes are used in a variety of (wireless) communication systems. Although commonly implemented in dedicated hardware, this paper explores the mapping of high-throughput RS decoding on vector DSPs. The four modules of such a decoder, viz. Syndrome Computation, Key Equation Solver,
LDPC Codes--Structural Analysis and Decoding Techniques
Zhang, Xiaojie
2012-01-01
Low-density parity-check (LDPC) codes have been the focus of much research over the past decade thanks to their near Shannon limit performance and to their efficient message-passing (MP) decoding algorithms. However, the error floor phenomenon observed in MP decoding, which manifests itself as an abrupt change in the slope of the error-rate curve,…
IQ Predicts Word Decoding Skills in Populations with Intellectual Disabilities
Levy, Yonata
2011-01-01
This is a study of word decoding in adolescents with Down syndrome and in adolescents with Intellectual Deficits of unknown etiology. It was designed as a replication of studies of word decoding in English speaking and in Hebrew speaking adolescents with Williams syndrome ([0230] and [0235]). Participants' IQ was matched to IQ in the groups with…
Word Processing in Dyslexics: An Automatic Decoding Deficit?
Yap, Regina; Van Der Leu, Aryan
1993-01-01
Compares dyslexic children with normal readers on measures of phonological decoding and automatic word processing. Finds that dyslexics have a deficit in automatic phonological decoding skills. Discusses results within the framework of the phonological deficit and the automatization deficit hypotheses. (RS)
Role of Gender and Linguistic Diversity in Word Decoding Development
Verhoeven, Ludo; van Leeuwe, Jan
2011-01-01
The purpose of the present study was to investigate the role of gender and linguistic diversity in the growth of Dutch word decoding skills throughout elementary school for a representative sample of children living in the Netherlands. Following a longitudinal design, the children's decoding abilities for (1) regular CVC words, (2) complex…
Decoding bipedal locomotion from the rat sensorimotor cortex
Rigosa, J.; Panarese, A.; Dominici, N.; Friedli, L.; van den Brand, R.; Carpaneto, J.; DiGiovanna, J.; Courtine, G.; Micera, S.
2015-01-01
Objective. Decoding forelimb movements from the firing activity of cortical neurons has been interfaced with robotic and prosthetic systems to replace lost upper limb functions in humans. Despite the potential of this approach to improve locomotion and facilitate gait rehabilitation, decoding lower
Multi-stage decoding of multi-level modulation codes
Lin, Shu; Kasami, Tadao; Costello, Daniel J., Jr.
1991-01-01
Various types of multi-stage decoding for multi-level modulation codes are investigated. It is shown that if the component codes of a multi-level modulation code and types of decoding at various stages are chosen properly, high spectral efficiency and large coding gain can be achieved with reduced decoding complexity. Particularly, it is shown that the difference in performance between the suboptimum multi-stage soft-decision maximum likelihood decoding of a modulation code and the single-stage optimum soft-decision decoding of the code is very small, only a fraction of dB loss in signal to noise ratio at a bit error rate (BER) of 10(exp -6).
Iterative List Decoding of Concatenated Source-Channel Codes
Directory of Open Access Journals (Sweden)
Hedayat Ahmadreza
2005-01-01
Full Text Available Whenever variable-length entropy codes are used in the presence of a noisy channel, any channel errors will propagate and cause significant harm. Despite using channel codes, some residual errors always remain, whose effect will get magnified by error propagation. Mitigating this undesirable effect is of great practical interest. One approach is to use the residual redundancy of variable length codes for joint source-channel decoding. In this paper, we improve the performance of residual redundancy source-channel decoding via an iterative list decoder made possible by a nonbinary outer CRC code. We show that the list decoding of VLC's is beneficial for entropy codes that contain redundancy. Such codes are used in state-of-the-art video coders, for example. The proposed list decoder improves the overall performance significantly in AWGN and fully interleaved Rayleigh fading channels.
Boosting reversible pushdown machines by preprocessing
DEFF Research Database (Denmark)
Axelsen, Holger Bock; Kutrib, Martin; Malcher, Andreas
2016-01-01
languages, whereas for reversible pushdown automata the accepted family of languages lies strictly in between the reversible deterministic context-free languages and the real-time deterministic context-free languages. Moreover, it is shown that the computational power of both types of machines...... is not changed by allowing the preprocessing sequential transducer to work irreversibly. Finally, we examine the closure properties of the family of languages accepted by such machines....
Decoding magnetoencephalographic rhythmic activity using spectrospatial information.
Kauppi, Jukka-Pekka; Parkkonen, Lauri; Hari, Riitta; Hyvärinen, Aapo
2013-12-01
We propose a new data-driven decoding method called Spectral Linear Discriminant Analysis (Spectral LDA) for the analysis of magnetoencephalography (MEG). The method allows investigation of changes in rhythmic neural activity as a result of different stimuli and tasks. The introduced classification model only assumes that each "brain state" can be characterized as a combination of neural sources, each of which shows rhythmic activity at one or several frequency bands. Furthermore, the model allows the oscillation frequencies to be different for each such state. We present decoding results from 9 subjects in a four-category classification problem defined by an experiment involving randomly alternating epochs of auditory, visual and tactile stimuli interspersed with rest periods. The performance of Spectral LDA was very competitive compared with four alternative classifiers based on different assumptions concerning the organization of rhythmic brain activity. In addition, the spectral and spatial patterns extracted automatically on the basis of trained classifiers showed that Spectral LDA offers a novel and interesting way of analyzing spectrospatial oscillatory neural activity across the brain. All the presented classification methods and visualization tools are freely available as a Matlab toolbox. © 2013.
Unsupervised learning of facial emotion decoding skills
Directory of Open Access Journals (Sweden)
Jan Oliver Huelle
2014-02-01
Full Text Available Research on the mechanisms underlying human facial emotion recognition has long focussed on genetically determined neural algorithms and often neglected the question of how these algorithms might be tuned by social learning. Here we show that facial emotion decoding skills can be significantly and sustainably improved by practise without an external teaching signal. Participants saw video clips of dynamic facial expressions of five different women and were asked to decide which of four possible emotions (anger, disgust, fear and sadness was shown in each clip. Although no external information about the correctness of the participant’s response or the sender’s true affective state was provided, participants showed a significant increase of facial emotion recognition accuracy both within and across two training sessions two days to several weeks apart. We discuss several similarities and differences between the unsupervised improvement of facial decoding skills observed in the current study, unsupervised perceptual learning of simple stimuli described in previous studies and practise effects often observed in cognitive tasks.
Unsupervised learning of facial emotion decoding skills.
Huelle, Jan O; Sack, Benjamin; Broer, Katja; Komlewa, Irina; Anders, Silke
2014-01-01
Research on the mechanisms underlying human facial emotion recognition has long focussed on genetically determined neural algorithms and often neglected the question of how these algorithms might be tuned by social learning. Here we show that facial emotion decoding skills can be significantly and sustainably improved by practice without an external teaching signal. Participants saw video clips of dynamic facial expressions of five different women and were asked to decide which of four possible emotions (anger, disgust, fear, and sadness) was shown in each clip. Although no external information about the correctness of the participant's response or the sender's true affective state was provided, participants showed a significant increase of facial emotion recognition accuracy both within and across two training sessions two days to several weeks apart. We discuss several similarities and differences between the unsupervised improvement of facial decoding skills observed in the current study, unsupervised perceptual learning of simple stimuli described in previous studies and practice effects often observed in cognitive tasks.
Decoding suprathreshold stochastic resonance with optimal weights
International Nuclear Information System (INIS)
Xu, Liyan; Vladusich, Tony; Duan, Fabing; Gunn, Lachlan J.; Abbott, Derek; McDonnell, Mark D.
2015-01-01
We investigate an array of stochastic quantizers for converting an analog input signal into a discrete output in the context of suprathreshold stochastic resonance. A new optimal weighted decoding is considered for different threshold level distributions. We show that for particular noise levels and choices of the threshold levels optimally weighting the quantizer responses provides a reduced mean square error in comparison with the original unweighted array. However, there are also many parameter regions where the original array provides near optimal performance, and when this occurs, it offers a much simpler approach than optimally weighting each quantizer's response. - Highlights: • A weighted summing array of independently noisy binary comparators is investigated. • We present an optimal linearly weighted decoding scheme for combining the comparator responses. • We solve for the optimal weights by applying least squares regression to simulated data. • We find that the MSE distortion of weighting before summation is superior to unweighted summation of comparator responses. • For some parameter regions, the decrease in MSE distortion due to weighting is negligible
Bayer image parallel decoding based on GPU
Hu, Rihui; Xu, Zhiyong; Wei, Yuxing; Sun, Shaohua
2012-11-01
In the photoelectrical tracking system, Bayer image is decompressed in traditional method, which is CPU-based. However, it is too slow when the images become large, for example, 2K×2K×16bit. In order to accelerate the Bayer image decoding, this paper introduces a parallel speedup method for NVIDA's Graphics Processor Unit (GPU) which supports CUDA architecture. The decoding procedure can be divided into three parts: the first is serial part, the second is task-parallelism part, and the last is data-parallelism part including inverse quantization, inverse discrete wavelet transform (IDWT) as well as image post-processing part. For reducing the execution time, the task-parallelism part is optimized by OpenMP techniques. The data-parallelism part could advance its efficiency through executing on the GPU as CUDA parallel program. The optimization techniques include instruction optimization, shared memory access optimization, the access memory coalesced optimization and texture memory optimization. In particular, it can significantly speed up the IDWT by rewriting the 2D (Tow-dimensional) serial IDWT into 1D parallel IDWT. Through experimenting with 1K×1K×16bit Bayer image, data-parallelism part is 10 more times faster than CPU-based implementation. Finally, a CPU+GPU heterogeneous decompression system was designed. The experimental result shows that it could achieve 3 to 5 times speed increase compared to the CPU serial method.
Energy Technology Data Exchange (ETDEWEB)
Hindle, D.
1999-06-01
The article surveys latest equipment available from the world`s manufacturers of a range of machines for tunnelling. These are grouped under headings: excavators; impact hammers; road headers; and shields and tunnel boring machines. Products of thirty manufacturers are referred to. Addresses and fax numbers of companies are supplied. 5 tabs., 13 photos.
El-Refaie, Ayman Mohamed Fawzi [Niskayuna, NY; Reddy, Patel Bhageerath [Madison, WI
2012-07-17
An interior permanent magnet electric machine is disclosed. The interior permanent magnet electric machine comprises a rotor comprising a plurality of radially placed magnets each having a proximal end and a distal end, wherein each magnet comprises a plurality of magnetic segments and at least one magnetic segment towards the distal end comprises a high resistivity magnetic material.
Kirrane, Diane E.
1990-01-01
As scientists seek to develop machines that can "learn," that is, solve problems by imitating the human brain, a gold mine of information on the processes of human learning is being discovered, expert systems are being improved, and human-machine interactions are being enhanced. (SK)
International Nuclear Information System (INIS)
Ritson, D.
1989-05-01
This talk examines methods available to minimize, but never entirely eliminate, degradation of machine performance caused by terrain following. Breaking of planar machine symmetry for engineering convenience and/or monetary savings must be balanced against small performance degradation, and can only be decided on a case-by-case basis. 5 refs
Squires, Katie Ellen
2013-01-01
This study investigated the differential contribution of auditory-verbal and visuospatial working memory (WM) on decoding skills in second- and fifth-grade children identified with poor decoding. Thirty-two second-grade students and 22 fifth-grade students completed measures that assessed simple and complex auditory-verbal and visuospatial memory,…
Decoding conjunctions of direction-of-motion and binocular disparity from human visual cortex.
Seymour, Kiley J; Clifford, Colin W G
2012-05-01
Motion and binocular disparity are two features in our environment that share a common correspondence problem. Decades of psychophysical research dedicated to understanding stereopsis suggest that these features interact early in human visual processing to disambiguate depth. Single-unit recordings in the monkey also provide evidence for the joint encoding of motion and disparity across much of the dorsal visual stream. Here, we used functional MRI and multivariate pattern analysis to examine where in the human brain conjunctions of motion and disparity are encoded. Subjects sequentially viewed two stimuli that could be distinguished only by their conjunctions of motion and disparity. Specifically, each stimulus contained the same feature information (leftward and rightward motion and crossed and uncrossed disparity) but differed exclusively in the way these features were paired. Our results revealed that a linear classifier could accurately decode which stimulus a subject was viewing based on voxel activation patterns throughout the dorsal visual areas and as early as V2. This decoding success was conditional on some voxels being individually sensitive to the unique conjunctions comprising each stimulus, thus a classifier could not rely on independent information about motion and binocular disparity to distinguish these conjunctions. This study expands on evidence that disparity and motion interact at many levels of human visual processing, particularly within the dorsal stream. It also lends support to the idea that stereopsis is subserved by early mechanisms also tuned to direction of motion.
Brain-Machine Interface Enables Bimanual Arm Movements in Monkeys
Ifft, Peter J.; Shokur, Solaiman; Li, Zheng; Lebedev, Mikhail A.; Nicolelis, Miguel A. L.
2014-01-01
Brain-machine interfaces (BMIs) are artificial systems that aim to restore sensation and movement to severely paralyzed patients. However, previous BMIs enabled only single arm functionality, and control of bimanual movements was a major challenge. Here, we developed and tested a bimanual BMI that enabled rhesus monkeys to control two avatar arms simultaneously. The bimanual BMI was based on the extracellular activity of 374–497 neurons recorded from several frontal and parietal cortical areas of both cerebral hemispheres. Cortical activity was transformed into movements of the two arms with a decoding algorithm called a 5th order unscented Kalman filter (UKF). The UKF is well-suited for BMI decoding because it accounts for both characteristics of reaching movements and their representation by cortical neurons. The UKF was trained either during a manual task performed with two joysticks or by having the monkeys passively observe the movements of avatar arms. Most cortical neurons changed their modulation patterns when both arms were engaged simultaneously. Representing the two arms jointly in a single UKF decoder resulted in improved decoding performance compared with using separate decoders for each arm. As the animals’ performance in bimanual BMI control improved over time, we observed widespread plasticity in frontal and parietal cortical areas. Neuronal representation of the avatar and reach targets was enhanced with learning, whereas pairwise correlations between neurons initially increased and then decreased. These results suggest that cortical networks may assimilate the two avatar arms through BMI control. PMID:24197735
Zydziak, Nicolas; Konrad, Waldemar; Feist, Florian; Afonin, Sergii; Weidner, Steffen; Barner-Kowollik, Christopher
2016-11-30
Designing artificial macromolecules with absolute sequence order represents a considerable challenge. Here we report an advanced light-induced avenue to monodisperse sequence-defined functional linear macromolecules up to decamers via a unique photochemical approach. The versatility of the synthetic strategy-combining sequential and modular concepts-enables the synthesis of perfect macromolecules varying in chemical constitution and topology. Specific functions are placed at arbitrary positions along the chain via the successive addition of monomer units and blocks, leading to a library of functional homopolymers, alternating copolymers and block copolymers. The in-depth characterization of each sequence-defined chain confirms the precision nature of the macromolecules. Decoding of the functional information contained in the molecular structure is achieved via tandem mass spectrometry without recourse to their synthetic history, showing that the sequence information can be read. We submit that the presented photochemical strategy is a viable and advanced concept for coding individual monomer units along a macromolecular chain.
Introduction to machine learning for brain imaging.
Lemm, Steven; Blankertz, Benjamin; Dickhaus, Thorsten; Müller, Klaus-Robert
2011-05-15
Machine learning and pattern recognition algorithms have in the past years developed to become a working horse in brain imaging and the computational neurosciences, as they are instrumental for mining vast amounts of neural data of ever increasing measurement precision and detecting minuscule signals from an overwhelming noise floor. They provide the means to decode and characterize task relevant brain states and to distinguish them from non-informative brain signals. While undoubtedly this machinery has helped to gain novel biological insights, it also holds the danger of potential unintentional abuse. Ideally machine learning techniques should be usable for any non-expert, however, unfortunately they are typically not. Overfitting and other pitfalls may occur and lead to spurious and nonsensical interpretation. The goal of this review is therefore to provide an accessible and clear introduction to the strengths and also the inherent dangers of machine learning usage in the neurosciences. Copyright © 2010 Elsevier Inc. All rights reserved.
The Machine within the Machine
Katarina Anthony
2014-01-01
Although Virtual Machines are widespread across CERN, you probably won't have heard of them unless you work for an experiment. Virtual machines - known as VMs - allow you to create a separate machine within your own, allowing you to run Linux on your Mac, or Windows on your Linux - whatever combination you need. Using a CERN Virtual Machine, a Linux analysis software runs on a Macbook. When it comes to LHC data, one of the primary issues collaborations face is the diversity of computing environments among collaborators spread across the world. What if an institute cannot run the analysis software because they use different operating systems? "That's where the CernVM project comes in," says Gerardo Ganis, PH-SFT staff member and leader of the CernVM project. "We were able to respond to experimentalists' concerns by providing a virtual machine package that could be used to run experiment software. This way, no matter what hardware they have ...
Energy Technology Data Exchange (ETDEWEB)
Nagao, M
1982-04-01
Each language has its own structure. In translating one language into another one, language attributes and grammatical interpretation must be defined in an unambiguous form. In order to parse a sentence, it is necessary to recognize its structure. A so-called context-free grammar can help in this respect for machine translation and machine-aided translation. Problems to be solved in studying machine translation are taken up in the paper, which discusses subjects for semantics and for syntactic analysis and translation software. 14 references.
O2-GIDNC: Beyond instantly decodable network coding
Aboutorab, Neda
2013-06-01
In this paper, we are concerned with extending the graph representation of generalized instantly decodable network coding (GIDNC) to a more general opportunistic network coding (ONC) scenario, referred to as order-2 GIDNC (O2-GIDNC). In the O2-GIDNC scheme, receivers can store non-instantly decodable packets (NIDPs) comprising two of their missing packets, and use them in a systematic way for later decodings. Once this graph representation is found, it can be used to extend the GIDNC graph-based analyses to the proposed O2-GIDNC scheme with a limited increase in complexity. In the proposed O2-GIDNC scheme, the information of the stored NIDPs at the receivers and the decoding opportunities they create can be exploited to improve the broadcast completion time and decoding delay compared to traditional GIDNC scheme. The completion time and decoding delay minimizing algorithms that can operate on the new O2-GIDNC graph are further described. The simulation results show that our proposed O2-GIDNC improves the completion time and decoding delay performance of the traditional GIDNC. © 2013 IEEE.
On decoding of multi-level MPSK modulation codes
Lin, Shu; Gupta, Alok Kumar
1990-01-01
The decoding problem of multi-level block modulation codes is investigated. The hardware design of soft-decision Viterbi decoder for some short length 8-PSK block modulation codes is presented. An effective way to reduce the hardware complexity of the decoder by reducing the branch metric and path metric, using a non-uniform floating-point to integer mapping scheme, is proposed and discussed. The simulation results of the design are presented. The multi-stage decoding (MSD) of multi-level modulation codes is also investigated. The cases of soft-decision and hard-decision MSD are considered and their performance are evaluated for several codes of different lengths and different minimum squared Euclidean distances. It is shown that the soft-decision MSD reduces the decoding complexity drastically and it is suboptimum. The hard-decision MSD further simplifies the decoding while still maintaining a reasonable coding gain over the uncoded system, if the component codes are chosen properly. Finally, some basic 3-level 8-PSK modulation codes using BCH codes as component codes are constructed and their coding gains are found for hard decision multistage decoding.
Encoder-decoder optimization for brain-computer interfaces.
Merel, Josh; Pianto, Donald M; Cunningham, John P; Paninski, Liam
2015-06-01
Neuroprosthetic brain-computer interfaces are systems that decode neural activity into useful control signals for effectors, such as a cursor on a computer screen. It has long been recognized that both the user and decoding system can adapt to increase the accuracy of the end effector. Co-adaptation is the process whereby a user learns to control the system in conjunction with the decoder adapting to learn the user's neural patterns. We provide a mathematical framework for co-adaptation and relate co-adaptation to the joint optimization of the user's control scheme ("encoding model") and the decoding algorithm's parameters. When the assumptions of that framework are respected, co-adaptation cannot yield better performance than that obtainable by an optimal initial choice of fixed decoder, coupled with optimal user learning. For a specific case, we provide numerical methods to obtain such an optimized decoder. We demonstrate our approach in a model brain-computer interface system using an online prosthesis simulator, a simple human-in-the-loop pyschophysics setup which provides a non-invasive simulation of the BCI setting. These experiments support two claims: that users can learn encoders matched to fixed, optimal decoders and that, once learned, our approach yields expected performance advantages.
Encoder-decoder optimization for brain-computer interfaces.
Directory of Open Access Journals (Sweden)
Josh Merel
2015-06-01
Full Text Available Neuroprosthetic brain-computer interfaces are systems that decode neural activity into useful control signals for effectors, such as a cursor on a computer screen. It has long been recognized that both the user and decoding system can adapt to increase the accuracy of the end effector. Co-adaptation is the process whereby a user learns to control the system in conjunction with the decoder adapting to learn the user's neural patterns. We provide a mathematical framework for co-adaptation and relate co-adaptation to the joint optimization of the user's control scheme ("encoding model" and the decoding algorithm's parameters. When the assumptions of that framework are respected, co-adaptation cannot yield better performance than that obtainable by an optimal initial choice of fixed decoder, coupled with optimal user learning. For a specific case, we provide numerical methods to obtain such an optimized decoder. We demonstrate our approach in a model brain-computer interface system using an online prosthesis simulator, a simple human-in-the-loop pyschophysics setup which provides a non-invasive simulation of the BCI setting. These experiments support two claims: that users can learn encoders matched to fixed, optimal decoders and that, once learned, our approach yields expected performance advantages.
Hard decoding algorithm for optimizing thresholds under general Markovian noise
Chamberland, Christopher; Wallman, Joel; Beale, Stefanie; Laflamme, Raymond
2017-04-01
Quantum error correction is instrumental in protecting quantum systems from noise in quantum computing and communication settings. Pauli channels can be efficiently simulated and threshold values for Pauli error rates under a variety of error-correcting codes have been obtained. However, realistic quantum systems can undergo noise processes that differ significantly from Pauli noise. In this paper, we present an efficient hard decoding algorithm for optimizing thresholds and lowering failure rates of an error-correcting code under general completely positive and trace-preserving (i.e., Markovian) noise. We use our hard decoding algorithm to study the performance of several error-correcting codes under various non-Pauli noise models by computing threshold values and failure rates for these codes. We compare the performance of our hard decoding algorithm to decoders optimized for depolarizing noise and show improvements in thresholds and reductions in failure rates by several orders of magnitude. Our hard decoding algorithm can also be adapted to take advantage of a code's non-Pauli transversal gates to further suppress noise. For example, we show that using the transversal gates of the 5-qubit code allows arbitrary rotations around certain axes to be perfectly corrected. Furthermore, we show that Pauli twirling can increase or decrease the threshold depending upon the code properties. Lastly, we show that even if the physical noise model differs slightly from the hypothesized noise model used to determine an optimized decoder, failure rates can still be reduced by applying our hard decoding algorithm.
Boltzmann machines for travelling salesman problems
Aarts, E.H.L.; Korst, J.H.M.
1989-01-01
Boltzmann machines are proposed as a massively parallel alternative to the (sequential) simulated annealing algorithm. Our approach is tailored to the travelling salesman problem, but it can also be applied to a more general class of combinatorial optimization problems. For two distinct 0–1
Decoding emotional valence from electroencephalographic rhythmic activity.
Celikkanat, Hande; Moriya, Hiroki; Ogawa, Takeshi; Kauppi, Jukka-Pekka; Kawanabe, Motoaki; Hyvarinen, Aapo
2017-07-01
We attempt to decode emotional valence from electroencephalographic rhythmic activity in a naturalistic setting. We employ a data-driven method developed in a previous study, Spectral Linear Discriminant Analysis, to discover the relationships between the classification task and independent neuronal sources, optimally utilizing multiple frequency bands. A detailed investigation of the classifier provides insight into the neuronal sources related with emotional valence, and the individual differences of the subjects in processing emotions. Our findings show: (1) sources whose locations are similar across subjects are consistently involved in emotional responses, with the involvement of parietal sources being especially significant, and (2) even though the locations of the involved neuronal sources are consistent, subjects can display highly varying degrees of valence-related EEG activity in the sources.
Decoding the mechanisms of Antikythera astronomical device
Lin, Jian-Liang
2016-01-01
This book presents a systematic design methodology for decoding the interior structure of the Antikythera mechanism, an astronomical device from ancient Greece. The historical background, surviving evidence and reconstructions of the mechanism are introduced, and the historical development of astronomical achievements and various astronomical instruments are investigated. Pursuing an approach based on the conceptual design of modern mechanisms and bearing in mind the standards of science and technology at the time, all feasible designs of the six lost/incomplete/unclear subsystems are synthesized as illustrated examples, and 48 feasible designs of the complete interior structure are presented. This approach provides not only a logical tool for applying modern mechanical engineering knowledge to the reconstruction of the Antikythera mechanism, but also an innovative research direction for identifying the original structures of the mechanism in the future. In short, the book offers valuable new insights for all...
Academic Training - Bioinformatics: Decoding the Genome
Chris Jones
2006-01-01
ACADEMIC TRAINING LECTURE SERIES 27, 28 February 1, 2, 3 March 2006 from 11:00 to 12:00 - Auditorium, bldg. 500 Decoding the Genome A special series of 5 lectures on: Recent extraordinary advances in the life sciences arising through new detection technologies and bioinformatics The past five years have seen an extraordinary change in the information and tools available in the life sciences. The sequencing of the human genome, the discovery that we possess far fewer genes than foreseen, the measurement of the tiny changes in the genomes that differentiate us, the sequencing of the genomes of many pathogens that lead to diseases such as malaria are all examples of completely new information that is now available in the quest for improved healthcare. New tools have allowed similar strides in the discovery of the associated protein structures, providing invaluable information for those searching for new drugs. New DNA microarray chips permit simultaneous measurement of the state of expression of tens...
Real-time minimal-bit-error probability decoding of convolutional codes
Lee, L.-N.
1974-01-01
A recursive procedure is derived for decoding of rate R = 1/n binary convolutional codes which minimizes the probability of the individual decoding decisions for each information bit, subject to the constraint that the decoding delay be limited to Delta branches. This new decoding algorithm is similar to, but somewhat more complex than, the Viterbi decoding algorithm. A real-time, i.e., fixed decoding delay, version of the Viterbi algorithm is also developed and used for comparison to the new algorithm on simulated channels. It is shown that the new algorithm offers advantages over Viterbi decoding in soft-decision applications, such as in the inner coding system for concatenated coding.
Real-time minimal bit error probability decoding of convolutional codes
Lee, L. N.
1973-01-01
A recursive procedure is derived for decoding of rate R=1/n binary convolutional codes which minimizes the probability of the individual decoding decisions for each information bit subject to the constraint that the decoding delay be limited to Delta branches. This new decoding algorithm is similar to, but somewhat more complex than, the Viterbi decoding algorithm. A real-time, i.e. fixed decoding delay, version of the Viterbi algorithm is also developed and used for comparison to the new algorithm on simulated channels. It is shown that the new algorithm offers advantages over Viterbi decoding in soft-decision applications such as in the inner coding system for concatenated coding.
CERN. Geneva
2017-01-01
Machine learning, which builds on ideas in computer science, statistics, and optimization, focuses on developing algorithms to identify patterns and regularities in data, and using these learned patterns to make predictions on new observations. Boosted by its industrial and commercial applications, the field of machine learning is quickly evolving and expanding. Recent advances have seen great success in the realms of computer vision, natural language processing, and broadly in data science. Many of these techniques have already been applied in particle physics, for instance for particle identification, detector monitoring, and the optimization of computer resources. Modern machine learning approaches, such as deep learning, are only just beginning to be applied to the analysis of High Energy Physics data to approach more and more complex problems. These classes will review the framework behind machine learning and discuss recent developments in the field.
Indian Academy of Sciences (India)
Research Mt System Example: The 'Janus' Translating Phone Project. The Janus ... based on laptops, and simultaneous translation of two speakers in a dialogue. For more ..... The current focus in MT research is on using machine learning.
Multiple LDPC decoding for distributed source coding and video coding
DEFF Research Database (Denmark)
Forchhammer, Søren; Luong, Huynh Van; Huang, Xin
2011-01-01
Distributed source coding (DSC) is a coding paradigm for systems which fully or partly exploit the source statistics at the decoder to reduce the computational burden at the encoder. Distributed video coding (DVC) is one example. This paper considers the use of Low Density Parity Check Accumulate...... (LDPCA) codes in a DSC scheme with feed-back. To improve the LDPC coding performance in the context of DSC and DVC, while retaining short encoder blocks, this paper proposes multiple parallel LDPC decoding. The proposed scheme passes soft information between decoders to enhance performance. Experimental...
Locally decodable codes and private information retrieval schemes
Yekhanin, Sergey
2010-01-01
Locally decodable codes (LDCs) are codes that simultaneously provide efficient random access retrieval and high noise resilience by allowing reliable reconstruction of an arbitrary bit of a message by looking at only a small number of randomly chosen codeword bits. Local decodability comes with a certain loss in terms of efficiency - specifically, locally decodable codes require longer codeword lengths than their classical counterparts. Private information retrieval (PIR) schemes are cryptographic protocols designed to safeguard the privacy of database users. They allow clients to retrieve rec
Neural network decoder for quantum error correcting codes
Krastanov, Stefan; Jiang, Liang
Artificial neural networks form a family of extremely powerful - albeit still poorly understood - tools used in anything from image and sound recognition through text generation to, in our case, decoding. We present a straightforward Recurrent Neural Network architecture capable of deducing the correcting procedure for a quantum error-correcting code from a set of repeated stabilizer measurements. We discuss the fault-tolerance of our scheme and the cost of training the neural network for a system of a realistic size. Such decoders are especially interesting when applied to codes, like the quantum LDPC codes, that lack known efficient decoding schemes.
EXIT Chart Analysis of Binary Message-Passing Decoders
DEFF Research Database (Denmark)
Lechner, Gottfried; Pedersen, Troels; Kramer, Gerhard
2007-01-01
Binary message-passing decoders for LDPC codes are analyzed using EXIT charts. For the analysis, the variable node decoder performs all computations in the L-value domain. For the special case of a hard decision channel, this leads to the well know Gallager B algorithm, while the analysis can...... be extended to channels with larger output alphabets. By increasing the output alphabet from hard decisions to four symbols, a gain of more than 1.0 dB is achieved using optimized codes. For this code optimization, the mixing property of EXIT functions has to be modified to the case of binary message......-passing decoders....
Turbo decoder architecture for beyond-4G applications
Wong, Cheng-Chi
2013-01-01
This book describes the most recent techniques for turbo decoder implementation, especially for 4G and beyond 4G applications. The authors reveal techniques for the design of high-throughput decoders for future telecommunication systems, enabling designers to reduce hardware cost and shorten processing time. Coverage includes an explanation of VLSI implementation of the turbo decoder, from basic functional units to advanced parallel architecture. The authors discuss both hardware architecture techniques and experimental results, showing the variations in area/throughput/performance with respec
Adaptive sequential controller
Energy Technology Data Exchange (ETDEWEB)
El-Sharkawi, Mohamed A. (Renton, WA); Xing, Jian (Seattle, WA); Butler, Nicholas G. (Newberg, OR); Rodriguez, Alonso (Pasadena, CA)
1994-01-01
An adaptive sequential controller (50/50') for controlling a circuit breaker (52) or other switching device to substantially eliminate transients on a distribution line caused by closing and opening the circuit breaker. The device adaptively compensates for changes in the response time of the circuit breaker due to aging and environmental effects. A potential transformer (70) provides a reference signal corresponding to the zero crossing of the voltage waveform, and a phase shift comparator circuit (96) compares the reference signal to the time at which any transient was produced when the circuit breaker closed, producing a signal indicative of the adaptive adjustment that should be made. Similarly, in controlling the opening of the circuit breaker, a current transformer (88) provides a reference signal that is compared against the time at which any transient is detected when the circuit breaker last opened. An adaptive adjustment circuit (102) produces a compensation time that is appropriately modified to account for changes in the circuit breaker response, including the effect of ambient conditions and aging. When next opened or closed, the circuit breaker is activated at an appropriately compensated time, so that it closes when the voltage crosses zero and opens when the current crosses zero, minimizing any transients on the distribution line. Phase angle can be used to control the opening of the circuit breaker relative to the reference signal provided by the potential transformer.
Adaptive sequential controller
El-Sharkawi, Mohamed A.; Xing, Jian; Butler, Nicholas G.; Rodriguez, Alonso
1994-01-01
An adaptive sequential controller (50/50') for controlling a circuit breaker (52) or other switching device to substantially eliminate transients on a distribution line caused by closing and opening the circuit breaker. The device adaptively compensates for changes in the response time of the circuit breaker due to aging and environmental effects. A potential transformer (70) provides a reference signal corresponding to the zero crossing of the voltage waveform, and a phase shift comparator circuit (96) compares the reference signal to the time at which any transient was produced when the circuit breaker closed, producing a signal indicative of the adaptive adjustment that should be made. Similarly, in controlling the opening of the circuit breaker, a current transformer (88) provides a reference signal that is compared against the time at which any transient is detected when the circuit breaker last opened. An adaptive adjustment circuit (102) produces a compensation time that is appropriately modified to account for changes in the circuit breaker response, including the effect of ambient conditions and aging. When next opened or closed, the circuit breaker is activated at an appropriately compensated time, so that it closes when the voltage crosses zero and opens when the current crosses zero, minimizing any transients on the distribution line. Phase angle can be used to control the opening of the circuit breaker relative to the reference signal provided by the potential transformer.
Study of bifurcation behavior of two-dimensional turbo product code decoders
International Nuclear Information System (INIS)
He Yejun; Lau, Francis C.M.; Tse, Chi K.
2008-01-01
Turbo codes, low-density parity-check (LDPC) codes and turbo product codes (TPCs) are high performance error-correction codes which employ iterative algorithms for decoding. Under different conditions, the behaviors of the decoders are different. While the nonlinear dynamical behaviors of turbo code decoders and LDPC decoders have been reported in the literature, the dynamical behavior of TPC decoders is relatively unexplored. In this paper, we investigate the behavior of the iterative algorithm of a two-dimensional TPC decoder when the input signal-to-noise ratio (SNR) varies. The quantity to be measured is the mean square value of the posterior probabilities of the information bits. Unlike turbo decoders or LDPC decoders, TPC decoders do not produce a clear 'waterfall region'. This is mainly because the TPC decoding algorithm does not converge to 'indecisive' fixed points even at very low SNR values
Study of bifurcation behavior of two-dimensional turbo product code decoders
Energy Technology Data Exchange (ETDEWEB)
He Yejun [Department of Electronic and Information Engineering, Hong Kong Polytechnic University, Hunghom, Hong Kong (China); Lau, Francis C.M. [Department of Electronic and Information Engineering, Hong Kong Polytechnic University, Hunghom, Hong Kong (China)], E-mail: encmlau@polyu.edu.hk; Tse, Chi K. [Department of Electronic and Information Engineering, Hong Kong Polytechnic University, Hunghom, Hong Kong (China)
2008-04-15
Turbo codes, low-density parity-check (LDPC) codes and turbo product codes (TPCs) are high performance error-correction codes which employ iterative algorithms for decoding. Under different conditions, the behaviors of the decoders are different. While the nonlinear dynamical behaviors of turbo code decoders and LDPC decoders have been reported in the literature, the dynamical behavior of TPC decoders is relatively unexplored. In this paper, we investigate the behavior of the iterative algorithm of a two-dimensional TPC decoder when the input signal-to-noise ratio (SNR) varies. The quantity to be measured is the mean square value of the posterior probabilities of the information bits. Unlike turbo decoders or LDPC decoders, TPC decoders do not produce a clear 'waterfall region'. This is mainly because the TPC decoding algorithm does not converge to 'indecisive' fixed points even at very low SNR values.
Architecture for time or transform domain decoding of reed-solomon codes
Shao, Howard M. (Inventor); Truong, Trieu-Kie (Inventor); Hsu, In-Shek (Inventor); Deutsch, Leslie J. (Inventor)
1989-01-01
Two pipeline (255,233) RS decoders, one a time domain decoder and the other a transform domain decoder, use the same first part to develop an errata locator polynomial .tau.(x), and an errata evaluator polynominal A(x). Both the time domain decoder and transform domain decoder have a modified GCD that uses an input multiplexer and an output demultiplexer to reduce the number of GCD cells required. The time domain decoder uses a Chien search and polynomial evaluator on the GCD outputs .tau.(x) and A(x), for the final decoding steps, while the transform domain decoder uses a transform error pattern algorithm operating on .tau.(x) and the initial syndrome computation S(x), followed by an inverse transform algorithm in sequence for the final decoding steps prior to adding the received RS coded message to produce a decoded output message.
Online transfer learning with extreme learning machine
Yin, Haibo; Yang, Yun-an
2017-05-01
In this paper, we propose a new transfer learning algorithm for online training. The proposed algorithm, which is called Online Transfer Extreme Learning Machine (OTELM), is based on Online Sequential Extreme Learning Machine (OSELM) while it introduces Semi-Supervised Extreme Learning Machine (SSELM) to transfer knowledge from the source to the target domain. With the manifold regularization, SSELM picks out instances from the source domain that are less relevant to those in the target domain to initialize the online training, so as to improve the classification performance. Experimental results demonstrate that the proposed OTELM can effectively use instances in the source domain to enhance the learning performance.
Machine-learning-assisted correction of correlated qubit errors in a topological code
Directory of Open Access Journals (Sweden)
Paul Baireuther
2018-01-01
Full Text Available A fault-tolerant quantum computation requires an efficient means to detect and correct errors that accumulate in encoded quantum information. In the context of machine learning, neural networks are a promising new approach to quantum error correction. Here we show that a recurrent neural network can be trained, using only experimentally accessible data, to detect errors in a widely used topological code, the surface code, with a performance above that of the established minimum-weight perfect matching (or blossom decoder. The performance gain is achieved because the neural network decoder can detect correlations between bit-flip (X and phase-flip (Z errors. The machine learning algorithm adapts to the physical system, hence no noise model is needed. The long short-term memory layers of the recurrent neural network maintain their performance over a large number of quantum error correction cycles, making it a practical decoder for forthcoming experimental realizations of the surface code.
Quantum Inequalities and Sequential Measurements
International Nuclear Information System (INIS)
Candelpergher, B.; Grandouz, T.; Rubinx, J.L.
2011-01-01
In this article, the peculiar context of sequential measurements is chosen in order to analyze the quantum specificity in the two most famous examples of Heisenberg and Bell inequalities: Results are found at some interesting variance with customary textbook materials, where the context of initial state re-initialization is described. A key-point of the analysis is the possibility of defining Joint Probability Distributions for sequential random variables associated to quantum operators. Within the sequential context, it is shown that Joint Probability Distributions can be defined in situations where not all of the quantum operators (corresponding to random variables) do commute two by two. (authors)
Construction and decoding of a class of algebraic geometry codes
DEFF Research Database (Denmark)
Justesen, Jørn; Larsen, Knud J.; Jensen, Helge Elbrønd
1989-01-01
A class of codes derived from algebraic plane curves is constructed. The concepts and results from algebraic geometry that were used are explained in detail; no further knowledge of algebraic geometry is needed. Parameters, generator and parity-check matrices are given. The main result is a decod...... is a decoding algorithm which turns out to be a generalization of the Peterson algorithm for decoding BCH decoder codes......A class of codes derived from algebraic plane curves is constructed. The concepts and results from algebraic geometry that were used are explained in detail; no further knowledge of algebraic geometry is needed. Parameters, generator and parity-check matrices are given. The main result...
Toward a universal decoder of linguistic meaning from brain activation.
Pereira, Francisco; Lou, Bin; Pritchett, Brianna; Ritter, Samuel; Gershman, Samuel J; Kanwisher, Nancy; Botvinick, Matthew; Fedorenko, Evelina
2018-03-06
Prior work decoding linguistic meaning from imaging data has been largely limited to concrete nouns, using similar stimuli for training and testing, from a relatively small number of semantic categories. Here we present a new approach for building a brain decoding system in which words and sentences are represented as vectors in a semantic space constructed from massive text corpora. By efficiently sampling this space to select training stimuli shown to subjects, we maximize the ability to generalize to new meanings from limited imaging data. To validate this approach, we train the system on imaging data of individual concepts, and show it can decode semantic vector representations from imaging data of sentences about a wide variety of both concrete and abstract topics from two separate datasets. These decoded representations are sufficiently detailed to distinguish even semantically similar sentences, and to capture the similarity structure of meaning relationships between sentences.
Illustrative examples in a bilingual decoding dictionary: An (un ...
African Journals Online (AJOL)
Keywords: Illustrative Examples, Bilingual Decoding Dictionary, Semantic Differences Between Source Language (Sl) And Target Language (Tl), Grammatical Differences Between Sl And Tl, Translation Of Examples, Transposition, Context-Dependent Translation, One-Word Equivalent, Zero Equivalent, Idiomatic ...
Decoding Reed-Solomon Codes beyond half the minimum distance
DEFF Research Database (Denmark)
Høholdt, Tom; Nielsen, Rasmus Refslund
1999-01-01
We describe an efficient implementation of M.Sudan"s algorithm for decoding Reed-Solomon codes beyond half the minimum distance. Furthermore we calculate an upper bound of the probabilty of getting more than one codeword as output...
Wakamiya, Eiji; Okumura, Tomohito; Nakanishi, Makoto; Takeshita, Takashi; Mizuta, Mekumi; Kurimoto, Naoko; Tamai, Hiroshi
2011-06-01
To clarify whether rapid naming ability itself is a main underpinning factor of rapid automatized naming tests (RAN) and how deep an influence the discrete decoding process has on reading, we performed discrete naming tasks and discrete hiragana reading tasks as well as sequential naming tasks and sequential hiragana reading tasks with 38 Japanese schoolchildren with reading difficulty. There were high correlations between both discrete and sequential hiragana reading and sentence reading, suggesting that some mechanism which automatizes hiragana reading makes sentence reading fluent. In object and color tasks, there were moderate correlations between sentence reading and sequential naming, and between sequential naming and discrete naming. But no correlation was found between reading tasks and discrete naming tasks. The influence of rapid naming ability of objects and colors upon reading seemed relatively small, and multi-item processing may work in relation to these. In contrast, in the digit naming task there was moderate correlation between sentence reading and discrete naming, while no correlation was seen between sequential naming and discrete naming. There was moderate correlation between reading tasks and sequential digit naming tasks. Digit rapid naming ability has more direct effect on reading while its effect on RAN is relatively limited. The ratio of how rapid naming ability influences RAN and reading seems to vary according to kind of the stimuli used. An assumption about components in RAN which influence reading is discussed in the context of both sequential processing and discrete naming speed. Copyright © 2010 The Japanese Society of Child Neurology. Published by Elsevier B.V. All rights reserved.
An overview of turbo decoding on fading channels
ATILGAN, Doğan
2009-01-01
A review of turbo coding and decoding has been presented in the literature [1]. In that paper, turbo coding and decoding on AWGN (Additive White Gaussian Noise) channels has been elaborated. In wireless communications, a phenomennon called multipath fading is frequently encountered. Therefore, investigation of efficient techniques to tackle with the destructive effects of fading is essential. Turbo coding has been proven as an efficient channel coding technique for AWGN channels. Some of the ...
Performance Analysis of a Decoding Algorithm for Algebraic Geometry Codes
DEFF Research Database (Denmark)
Jensen, Helge Elbrønd; Nielsen, Rasmus Refslund; Høholdt, Tom
1998-01-01
We analyse the known decoding algorithms for algebraic geometry codes in the case where the number of errors is greater than or equal to [(dFR-1)/2]+1, where dFR is the Feng-Rao distance......We analyse the known decoding algorithms for algebraic geometry codes in the case where the number of errors is greater than or equal to [(dFR-1)/2]+1, where dFR is the Feng-Rao distance...
Recent results in the decoding of Algebraic geometry codes
DEFF Research Database (Denmark)
Høholdt, Tom; Jensen, Helge Elbrønd; Nielsen, Rasmus Refslund
1998-01-01
We analyse the known decoding algorithms for algebraic geometry codes in the case where the number of errors is [(dFR-1)/2]+1, where dFR is the Feng-Rao distance......We analyse the known decoding algorithms for algebraic geometry codes in the case where the number of errors is [(dFR-1)/2]+1, where dFR is the Feng-Rao distance...
Effect of video decoder errors on video interpretability
Young, Darrell L.
2014-06-01
The advancement in video compression technology can result in more sensitivity to bit errors. Bit errors can propagate causing sustained loss of interpretability. In the worst case, the decoder "freezes" until it can re-synchronize with the stream. Detection of artifacts enables downstream processes to avoid corrupted frames. A simple template approach to detect block stripes and a more advanced cascade approach to detect compression artifacts was shown to correlate to the presence of artifacts and decoder messages.
Framework for sequential approximate optimization
Jacobs, J.H.; Etman, L.F.P.; Keulen, van F.; Rooda, J.E.
2004-01-01
An object-oriented framework for Sequential Approximate Optimization (SAO) isproposed. The framework aims to provide an open environment for thespecification and implementation of SAO strategies. The framework is based onthe Python programming language and contains a toolbox of Python
Wittevrongel, Benjamin; Van Wolputte, Elia; Van Hulle, Marc M
2017-11-08
When encoding visual targets using various lagged versions of a pseudorandom binary sequence of luminance changes, the EEG signal recorded over the viewer's occipital pole exhibits so-called code-modulated visual evoked potentials (cVEPs), the phase lags of which can be tied to these targets. The cVEP paradigm has enjoyed interest in the brain-computer interfacing (BCI) community for the reported high information transfer rates (ITR, in bits/min). In this study, we introduce a novel decoding algorithm based on spatiotemporal beamforming, and show that this algorithm is able to accurately identify the gazed target. Especially for a small number of repetitions of the coding sequence, our beamforming approach significantly outperforms an optimised support vector machine (SVM)-based classifier, which is considered state-of-the-art in cVEP-based BCI. In addition to the traditional 60 Hz stimulus presentation rate for the coding sequence, we also explore the 120 Hz rate, and show that the latter enables faster communication, with a maximal median ITR of 172.87 bits/min. Finally, we also report on a transition effect in the EEG signal following the onset of the stimulus sequence, and recommend to exclude the first 150 ms of the trials from decoding when relying on a single presentation of the stimulus sequence.
Single-Trial Decoding of Bistable Perception Based on Sparse Nonnegative Tensor Decomposition
Wang, Zhisong; Maier, Alexander; Logothetis, Nikos K.; Liang, Hualou
2008-01-01
The study of the neuronal correlates of the spontaneous alternation in perception elicited by bistable visual stimuli is promising for understanding the mechanism of neural information processing and the neural basis of visual perception and perceptual decision-making. In this paper, we develop a sparse nonnegative tensor factorization-(NTF)-based method to extract features from the local field potential (LFP), collected from the middle temporal (MT) visual cortex in a macaque monkey, for decoding its bistable structure-from-motion (SFM) perception. We apply the feature extraction approach to the multichannel time-frequency representation of the intracortical LFP data. The advantages of the sparse NTF-based feature extraction approach lies in its capability to yield components common across the space, time, and frequency domains yet discriminative across different conditions without prior knowledge of the discriminating frequency bands and temporal windows for a specific subject. We employ the support vector machines (SVMs) classifier based on the features of the NTF components for single-trial decoding the reported perception. Our results suggest that although other bands also have certain discriminability, the gamma band feature carries the most discriminative information for bistable perception, and that imposing the sparseness constraints on the nonnegative tensor factorization improves extraction of this feature. PMID:18528515
Gesture Decoding Using ECoG Signals from Human Sensorimotor Cortex: A Pilot Study
Directory of Open Access Journals (Sweden)
Yue Li
2017-01-01
Full Text Available Electrocorticography (ECoG has been demonstrated as a promising neural signal source for developing brain-machine interfaces (BMIs. However, many concerns about the disadvantages brought by large craniotomy for implanting the ECoG grid limit the clinical translation of ECoG-based BMIs. In this study, we collected clinical ECoG signals from the sensorimotor cortex of three epileptic participants when they performed hand gestures. The ECoG power spectrum in hybrid frequency bands was extracted to build a synchronous real-time BMI system. High decoding accuracy of the three gestures was achieved in both offline analysis (85.7%, 84.5%, and 69.7% and online tests (80% and 82%, tested on two participants only. We found that the decoding performance was maintained even with a subset of channels selected by a greedy algorithm. More importantly, these selected channels were mostly distributed along the central sulcus and clustered in the area of 3 interelectrode squares. Our findings of the reduced and clustered distribution of ECoG channels further supported the feasibility of clinically implementing the ECoG-based BMI system for the control of hand gestures.
Electrophysiological difference between mental state decoding and mental state reasoning.
Cao, Bihua; Li, Yiyuan; Li, Fuhong; Li, Hong
2012-06-29
Previous studies have explored the neural mechanism of Theory of Mind (ToM), but the neural correlates of its two components, mental state decoding and mental state reasoning, remain unclear. In the present study, participants were presented with various photographs, showing an actor looking at 1 of 2 objects, either with a happy or an unhappy expression. They were asked to either decode the emotion of the actor (mental state decoding task), predict which object would be chosen by the actor (mental state reasoning task), or judge at which object the actor was gazing (physical task), while scalp potentials were recorded. Results showed that (1) the reasoning task elicited an earlier N2 peak than the decoding task did over the prefrontal scalp sites; and (2) during the late positive component (240-440 ms), the reasoning task elicited a more positive deflection than the other two tasks did at the prefrontal scalp sites. In addition, neither the decoding task nor the reasoning task has no left/right hemisphere difference. These findings imply that mental state reasoning differs from mental state decoding early (210 ms) after stimulus onset, and that the prefrontal lobe is the neural basis of mental state reasoning. Copyright © 2012 Elsevier B.V. All rights reserved.
Evaluation framework for K-best sphere decoders
Shen, Chungan
2010-08-01
While Maximum-Likelihood (ML) is the optimum decoding scheme for most communication scenarios, practical implementation difficulties limit its use, especially for Multiple Input Multiple Output (MIMO) systems with a large number of transmit or receive antennas. Tree-searching type decoder structures such as Sphere decoder and K-best decoder present an interesting trade-off between complexity and performance. Many algorithmic developments and VLSI implementations have been reported in literature with widely varying performance to area and power metrics. In this semi-tutorial paper we present a holistic view of different Sphere decoding techniques and K-best decoding techniques, identifying the key algorithmic and implementation trade-offs. We establish a consistent benchmark framework to investigate and compare the delay cost, power cost, and power-delay-product cost incurred by each method. Finally, using the framework, we propose and analyze a novel architecture and compare that to other published approaches. Our goal is to explicitly elucidate the overall advantages and disadvantages of each proposed algorithms in one coherent framework. © 2010 World Scientific Publishing Company.
Partially blind instantly decodable network codes for lossy feedback environment
Sorour, Sameh
2014-09-01
In this paper, we study the multicast completion and decoding delay minimization problems for instantly decodable network coding (IDNC) in the case of lossy feedback. When feedback loss events occur, the sender falls into uncertainties about packet reception at the different receivers, which forces it to perform partially blind selections of packet combinations in subsequent transmissions. To determine efficient selection policies that reduce the completion and decoding delays of IDNC in such an environment, we first extend the perfect feedback formulation in our previous works to the lossy feedback environment, by incorporating the uncertainties resulting from unheard feedback events in these formulations. For the completion delay problem, we use this formulation to identify the maximum likelihood state of the network in events of unheard feedback and employ it to design a partially blind graph update extension to the multicast IDNC algorithm in our earlier work. For the decoding delay problem, we derive an expression for the expected decoding delay increment for any arbitrary transmission. This expression is then used to find the optimal policy that reduces the decoding delay in such lossy feedback environment. Results show that our proposed solutions both outperform previously proposed approaches and achieve tolerable degradation even at relatively high feedback loss rates.
Sequentially pulsed traveling wave accelerator
Caporaso, George J [Livermore, CA; Nelson, Scott D [Patterson, CA; Poole, Brian R [Tracy, CA
2009-08-18
A sequentially pulsed traveling wave compact accelerator having two or more pulse forming lines each with a switch for producing a short acceleration pulse along a short length of a beam tube, and a trigger mechanism for sequentially triggering the switches so that a traveling axial electric field is produced along the beam tube in synchronism with an axially traversing pulsed beam of charged particles to serially impart energy to the particle beam.
International Nuclear Information System (INIS)
Zerlauth, Markus; Schmidt, Rüdiger; Wenninger, Jörg
2012-01-01
The present architecture of the machine protection system is being recalled and the performance of the associated systems during the 2011 run will be briefly summarized. An analysis of the causes of beam dumps as well as an assessment of the dependability of the machine protection systems (MPS) itself is being presented. Emphasis will be given to events that risked exposing parts of the machine to damage. Further improvements and mitigations of potential holes in the protection systems will be evaluated along with their impact on the 2012 run. The role of rMPP during the various operational phases (commissioning, intensity ramp up, MDs...) will be discussed along with a proposal for the intensity ramp up for the start of beam operation in 2012
Energy Technology Data Exchange (ETDEWEB)
Chikkagoudar, Satish; Chatterjee, Samrat; Thomas, Dennis G.; Carroll, Thomas E.; Muller, George
2017-04-21
The absence of a robust and unified theory of cyber dynamics presents challenges and opportunities for using machine learning based data-driven approaches to further the understanding of the behavior of such complex systems. Analysts can also use machine learning approaches to gain operational insights. In order to be operationally beneficial, cybersecurity machine learning based models need to have the ability to: (1) represent a real-world system, (2) infer system properties, and (3) learn and adapt based on expert knowledge and observations. Probabilistic models and Probabilistic graphical models provide these necessary properties and are further explored in this chapter. Bayesian Networks and Hidden Markov Models are introduced as an example of a widely used data driven classification/modeling strategy.
Zerlauth, Markus; Wenninger, Jörg
2012-01-01
The present architecture of the machine protection system is being recalled and the performance of the associated systems during the 2011 run will be briefly summarized. An analysis of the causes of beam dumps as well as an assessment of the dependability of the machine protection systems (MPS) itself is being presented. Emphasis will be given to events that risked exposing parts of the machine to damage. Further improvements and mitigations of potential holes in the protection systems will be evaluated along with their impact on the 2012 run. The role of rMPP during the various operational phases (commissioning, intensity ramp up, MDs...) will be discussed along with a proposal for the intensity ramp up for the start of beam operation in 2012.
Energy Technology Data Exchange (ETDEWEB)
Zerlauth, Markus; Schmidt, Rüdiger; Wenninger, Jörg [European Organization for Nuclear Research, Geneva (Switzerland)
2012-07-01
The present architecture of the machine protection system is being recalled and the performance of the associated systems during the 2011 run will be briefly summarized. An analysis of the causes of beam dumps as well as an assessment of the dependability of the machine protection systems (MPS) itself is being presented. Emphasis will be given to events that risked exposing parts of the machine to damage. Further improvements and mitigations of potential holes in the protection systems will be evaluated along with their impact on the 2012 run. The role of rMPP during the various operational phases (commissioning, intensity ramp up, MDs...) will be discussed along with a proposal for the intensity ramp up for the start of beam operation in 2012.
Lei, Ted Chih-Wei; Tseng, Fan-Shuo
2017-07-01
This paper addresses the problem of high-computational complexity decoding in traditional Wyner-Ziv video coding (WZVC). The key focus is the migration of two traditionally high-computationally complex encoder algorithms, namely motion estimation and mode decision. In order to reduce the computational burden in this process, the proposed architecture adopts the partial boundary matching algorithm and four flexible types of block mode decision at the decoder. This approach does away with the need for motion estimation and mode decision at the encoder. The experimental results show that the proposed padding block-based WZVC not only decreases decoder complexity to approximately one hundredth that of the state-of-the-art DISCOVER decoding but also outperforms DISCOVER codec by up to 3 to 4 dB.
International Nuclear Information System (INIS)
Panyam, Vinatha S.; Rakshit, Sougata; Kulkarni, M.S.; Pradeepkumar, K.S.
2017-01-01
Radiation Standards Section (RSS), RSSD, BARC is the national metrology institute for ionizing radiation. RSS develops and maintains radiation standards for X-ray, beta, gamma and neutron radiations. In radiation dosimetry, traceability, accuracy and consistency of radiation measurements is very important especially in radiotherapy where the success of patient treatment is dependent on the accuracy of the dose delivered to the tumour. Cobalt teletherapy machines have been used in the treatment of cancer since the early 1950s and India had its first cobalt teletherapy machine installed at the Cancer Institute, Chennai in 1956
Singer product apertures—A coded aperture system with a fast decoding algorithm
International Nuclear Information System (INIS)
Byard, Kevin; Shutler, Paul M.E.
2017-01-01
A new type of coded aperture configuration that enables fast decoding of the coded aperture shadowgram data is presented. Based on the products of incidence vectors generated from the Singer difference sets, we call these Singer product apertures. For a range of aperture dimensions, we compare experimentally the performance of three decoding methods: standard decoding, induction decoding and direct vector decoding. In all cases the induction and direct vector methods are several orders of magnitude faster than the standard method, with direct vector decoding being significantly faster than induction decoding. For apertures of the same dimensions the increase in speed offered by direct vector decoding over induction decoding is better for lower throughput apertures.
An FPGA Implementation of (3,6-Regular Low-Density Parity-Check Code Decoder
Directory of Open Access Journals (Sweden)
Tong Zhang
2003-05-01
Full Text Available Because of their excellent error-correcting performance, low-density parity-check (LDPC codes have recently attracted a lot of attention. In this paper, we are interested in the practical LDPC code decoder hardware implementations. The direct fully parallel decoder implementation usually incurs too high hardware complexity for many real applications, thus partly parallel decoder design approaches that can achieve appropriate trade-offs between hardware complexity and decoding throughput are highly desirable. Applying a joint code and decoder design methodology, we develop a high-speed (3,k-regular LDPC code partly parallel decoder architecture based on which we implement a 9216-bit, rate-1/2(3,6-regular LDPC code decoder on Xilinx FPGA device. This partly parallel decoder supports a maximum symbol throughput of 54 Mbps and achieves BER 10Ã¢ÂˆÂ’6 at 2 dB over AWGN channel while performing maximum 18 decoding iterations.
Singer product apertures—A coded aperture system with a fast decoding algorithm
Energy Technology Data Exchange (ETDEWEB)
Byard, Kevin, E-mail: kevin.byard@aut.ac.nz [School of Economics, Faculty of Business, Economics and Law, Auckland University of Technology, Auckland 1142 (New Zealand); Shutler, Paul M.E. [National Institute of Education, Nanyang Technological University, 1 Nanyang Walk, Singapore 637616 (Singapore)
2017-06-01
A new type of coded aperture configuration that enables fast decoding of the coded aperture shadowgram data is presented. Based on the products of incidence vectors generated from the Singer difference sets, we call these Singer product apertures. For a range of aperture dimensions, we compare experimentally the performance of three decoding methods: standard decoding, induction decoding and direct vector decoding. In all cases the induction and direct vector methods are several orders of magnitude faster than the standard method, with direct vector decoding being significantly faster than induction decoding. For apertures of the same dimensions the increase in speed offered by direct vector decoding over induction decoding is better for lower throughput apertures.
Restoration of fMRI Decodability Does Not Imply Latent Working Memory States
Schneegans, Sebastian; Bays, Paul M.
2018-01-01
Recent imaging studies have challenged the prevailing view that working memory is mediated by sustained neural activity. Using machine learning methods to reconstruct memory content, these studies found that previously diminished representations can be restored by retrospective cueing or other forms of stimulation. These findings have been interpreted as evidence for an activity-silent working memory state that can be reactivated dependent on task demands. Here, we test the validity of this conclusion by formulating a neural process model of working memory based on sustained activity and using this model to emulate a spatial recall task with retrocueing. The simulation reproduces both behavioral and fMRI results previously taken as evidence for latent states, in particular the restoration of spatial reconstruction quality following an informative cue. Our results demonstrate that recovery of the decodability of an imaging signal does not provide compelling evidence for an activity-silent working memory state. PMID:28820674
Decoding reality the universe as quantum information
Vedral, Vlatko
2010-01-01
In Decoding Reality, Vlatko Vedral offers a mind-stretching look at the deepest questions about the universe--where everything comes from, why things are as they are, what everything is. The most fundamental definition of reality is not matter or energy, he writes, but information--and it is the processing of information that lies at the root of all physical, biological, economic, and social phenomena. This view allows Vedral to address a host of seemingly unrelated questions: Why does DNA bind like it does? What is the ideal diet for longevity? How do you make your first million dollars? We can unify all through the understanding that everything consists of bits of information, he writes, though that raises the question of where these bits come from. To find the answer, he takes us on a guided tour through the bizarre realm of quantum physics. At this sub-sub-subatomic level, we find such things as the interaction of separated quantum particles--what Einstein called "spooky action at a distance." In fact, V...
Statistical coding and decoding of heartbeat intervals.
Lucena, Fausto; Barros, Allan Kardec; Príncipe, José C; Ohnishi, Noboru
2011-01-01
The heart integrates neuroregulatory messages into specific bands of frequency, such that the overall amplitude spectrum of the cardiac output reflects the variations of the autonomic nervous system. This modulatory mechanism seems to be well adjusted to the unpredictability of the cardiac demand, maintaining a proper cardiac regulation. A longstanding theory holds that biological organisms facing an ever-changing environment are likely to evolve adaptive mechanisms to extract essential features in order to adjust their behavior. The key question, however, has been to understand how the neural circuitry self-organizes these feature detectors to select behaviorally relevant information. Previous studies in computational perception suggest that a neural population enhances information that is important for survival by minimizing the statistical redundancy of the stimuli. Herein we investigate whether the cardiac system makes use of a redundancy reduction strategy to regulate the cardiac rhythm. Based on a network of neural filters optimized to code heartbeat intervals, we learn a population code that maximizes the information across the neural ensemble. The emerging population code displays filter tuning proprieties whose characteristics explain diverse aspects of the autonomic cardiac regulation, such as the compromise between fast and slow cardiac responses. We show that the filters yield responses that are quantitatively similar to observed heart rate responses during direct sympathetic or parasympathetic nerve stimulation. Our findings suggest that the heart decodes autonomic stimuli according to information theory principles analogous to how perceptual cues are encoded by sensory systems.
Rate Aware Instantly Decodable Network Codes
Douik, Ahmed
2016-02-26
This paper addresses the problem of reducing the delivery time of data messages to cellular users using instantly decodable network coding (IDNC) with physical-layer rate awareness. While most of the existing literature on IDNC does not consider any physical layer complications, this paper proposes a cross-layer scheme that incorporates the different channel rates of the various users in the decision process of both the transmitted message combinations and the rates with which they are transmitted. The completion time minimization problem in such scenario is first shown to be intractable. The problem is, thus, approximated by reducing, at each transmission, the increase of an anticipated version of the completion time. The paper solves the problem by formulating it as a maximum weight clique problem over a newly designed rate aware IDNC (RA-IDNC) graph. Further, the paper provides a multi-layer solution to improve the completion time approximation. Simulation results suggest that the cross-layer design largely outperforms the uncoded transmissions strategies and the classical IDNC scheme. © 2015 IEEE.
Encoding and decoding messages with chaotic lasers
International Nuclear Information System (INIS)
Alsing, P.M.; Gavrielides, A.; Kovanis, V.; Roy, R.; Thornburg, K.S. Jr.
1997-01-01
We investigate the structure of the strange attractor of a chaotic loss-modulated solid-state laser utilizing return maps based on a combination of intensity maxima and interspike intervals, as opposed to those utilizing Poincare sections defined by the intensity maxima of the laser (I=0,Ie<0) alone. We find both experimentally and numerically that a simple, intrinsic relationship exists between an intensity maximum and the pair of preceding and succeeding interspike intervals. In addition, we numerically investigate encoding messages on the output of a chaotic transmitter laser and its subsequent decoding by a similar receiver laser. By exploiting the relationship between the intensity maxima and the interspike intervals, we demonstrate that the method utilized to encode the message is vital to the system close-quote s ability to hide the signal from unwanted deciphering. In this work alternative methods are studied in order to encode messages by modulating the magnitude of pumping of the transmitter laser and also by driving its loss modulation with more than one frequency. copyright 1997 The American Physical Society
Decoding P4-ATPase substrate interactions.
Roland, Bartholomew P; Graham, Todd R
Cellular membranes display a diversity of functions that are conferred by the unique composition and organization of their proteins and lipids. One important aspect of lipid organization is the asymmetric distribution of phospholipids (PLs) across the plasma membrane. The unequal distribution of key PLs between the cytofacial and exofacial leaflets of the bilayer creates physical surface tension that can be used to bend the membrane; and like Ca 2+ , a chemical gradient that can be used to transduce biochemical signals. PL flippases in the type IV P-type ATPase (P4-ATPase) family are the principle transporters used to set and repair this PL gradient and the asymmetric organization of these membranes are encoded by the substrate specificity of these enzymes. Thus, understanding the mechanisms of P4-ATPase substrate specificity will help reveal their role in membrane organization and cell biology. Further, decoding the structural determinants of substrate specificity provides investigators the opportunity to mutationally tune this specificity to explore the role of particular PL substrates in P4-ATPase cellular functions. This work reviews the role of P4-ATPases in membrane biology, presents our current understanding of P4-ATPase substrate specificity, and discusses how these fundamental aspects of P4-ATPase enzymology may be used to enhance our knowledge of cellular membrane biology.
Observing human movements helps decoding environmental forces.
Zago, Myrka; La Scaleia, Barbara; Miller, William L; Lacquaniti, Francesco
2011-11-01
Vision of human actions can affect several features of visual motion processing, as well as the motor responses of the observer. Here, we tested the hypothesis that action observation helps decoding environmental forces during the interception of a decelerating target within a brief time window, a task intrinsically very difficult. We employed a factorial design to evaluate the effects of scene orientation (normal or inverted) and target gravity (normal or inverted). Button-press triggered the motion of a bullet, a piston, or a human arm. We found that the timing errors were smaller for upright scenes irrespective of gravity direction in the Bullet group, while the errors were smaller for the standard condition of normal scene and gravity in the Piston group. In the Arm group, instead, performance was better when the directions of scene and target gravity were concordant, irrespective of whether both were upright or inverted. These results suggest that the default viewer-centered reference frame is used with inanimate scenes, such as those of the Bullet and Piston protocols. Instead, the presence of biological movements in animate scenes (as in the Arm protocol) may help processing target kinematics under the ecological conditions of coherence between scene and target gravity directions.
Rate Aware Instantly Decodable Network Codes
Douik, Ahmed; Sorour, Sameh; Al-Naffouri, Tareq Y.; Alouini, Mohamed-Slim
2016-01-01
This paper addresses the problem of reducing the delivery time of data messages to cellular users using instantly decodable network coding (IDNC) with physical-layer rate awareness. While most of the existing literature on IDNC does not consider any physical layer complications, this paper proposes a cross-layer scheme that incorporates the different channel rates of the various users in the decision process of both the transmitted message combinations and the rates with which they are transmitted. The completion time minimization problem in such scenario is first shown to be intractable. The problem is, thus, approximated by reducing, at each transmission, the increase of an anticipated version of the completion time. The paper solves the problem by formulating it as a maximum weight clique problem over a newly designed rate aware IDNC (RA-IDNC) graph. Further, the paper provides a multi-layer solution to improve the completion time approximation. Simulation results suggest that the cross-layer design largely outperforms the uncoded transmissions strategies and the classical IDNC scheme. © 2015 IEEE.
Statistical coding and decoding of heartbeat intervals.
Directory of Open Access Journals (Sweden)
Fausto Lucena
Full Text Available The heart integrates neuroregulatory messages into specific bands of frequency, such that the overall amplitude spectrum of the cardiac output reflects the variations of the autonomic nervous system. This modulatory mechanism seems to be well adjusted to the unpredictability of the cardiac demand, maintaining a proper cardiac regulation. A longstanding theory holds that biological organisms facing an ever-changing environment are likely to evolve adaptive mechanisms to extract essential features in order to adjust their behavior. The key question, however, has been to understand how the neural circuitry self-organizes these feature detectors to select behaviorally relevant information. Previous studies in computational perception suggest that a neural population enhances information that is important for survival by minimizing the statistical redundancy of the stimuli. Herein we investigate whether the cardiac system makes use of a redundancy reduction strategy to regulate the cardiac rhythm. Based on a network of neural filters optimized to code heartbeat intervals, we learn a population code that maximizes the information across the neural ensemble. The emerging population code displays filter tuning proprieties whose characteristics explain diverse aspects of the autonomic cardiac regulation, such as the compromise between fast and slow cardiac responses. We show that the filters yield responses that are quantitatively similar to observed heart rate responses during direct sympathetic or parasympathetic nerve stimulation. Our findings suggest that the heart decodes autonomic stimuli according to information theory principles analogous to how perceptual cues are encoded by sensory systems.
A four-dimensional virtual hand brain-machine interface using active dimension selection.
Rouse, Adam G
2016-06-01
Brain-machine interfaces (BMI) traditionally rely on a fixed, linear transformation from neural signals to an output state-space. In this study, the assumption that a BMI must control a fixed, orthogonal basis set was challenged and a novel active dimension selection (ADS) decoder was explored. ADS utilizes a two stage decoder by using neural signals to both (i) select an active dimension being controlled and (ii) control the velocity along the selected dimension. ADS decoding was tested in a monkey using 16 single units from premotor and primary motor cortex to successfully control a virtual hand avatar to move to eight different postures. Following training with the ADS decoder to control 2, 3, and then 4 dimensions, each emulating a grasp shape of the hand, performance reached 93% correct with a bit rate of 2.4 bits s(-1) for eight targets. Selection of eight targets using ADS control was more efficient, as measured by bit rate, than either full four-dimensional control or computer assisted one-dimensional control. ADS decoding allows a user to quickly and efficiently select different hand postures. This novel decoding scheme represents a potential method to reduce the complexity of high-dimension BMI control of the hand.
DEFF Research Database (Denmark)
De Chiffre, Leonardo
This document is used in connection with a laboratory exercise of 3 hours duration as a part of the course GEOMETRICAL METROLOGY AND MACHINE TESTING. The exercise includes a series of tests carried out by the student on a conventional and a numerically controled lathe, respectively. This document...
Machine rates for selected forest harvesting machines
R.W. Brinker; J. Kinard; Robert Rummer; B. Lanford
2002-01-01
Very little new literature has been published on the subject of machine rates and machine cost analysis since 1989 when the Alabama Agricultural Experiment Station Circular 296, Machine Rates for Selected Forest Harvesting Machines, was originally published. Many machines discussed in the original publication have undergone substantial changes in various aspects, not...
Directory of Open Access Journals (Sweden)
J Matthew Mahoney
Full Text Available Hippocampal neural systems consolidate multiple complex behaviors into memory. However, the temporal structure of neural firing supporting complex memory consolidation is unknown. Replay of hippocampal place cells during sleep supports the view that a simple repetitive behavior modifies sleep firing dynamics, but does not explain how multiple episodes could be integrated into associative networks for recollection during future cognition. Here we decode sequential firing structure within spike avalanches of all pyramidal cells recorded in sleeping rats after running in a circular track. We find that short sequences that combine into multiple long sequences capture the majority of the sequential structure during sleep, including replay of hippocampal place cells. The ensemble, however, is not optimized for maximally producing the behavior-enriched episode. Thus behavioral programming of sequential correlations occurs at the level of short-range interactions, not whole behavioral sequences and these short sequences are assembled into a large and complex milieu that could support complex memory consolidation.
Remarks on sequential designs in risk assessment
International Nuclear Information System (INIS)
Seidenfeld, T.
1982-01-01
The special merits of sequential designs are reviewed in light of particular challenges that attend risk assessment for human population. The kinds of ''statistical inference'' are distinguished and the problem of design which is pursued is the clash between Neyman-Pearson and Bayesian programs of sequential design. The value of sequential designs is discussed and the Neyman-Pearson vs. Bayesian sequential designs are probed in particular. Finally, warnings with sequential designs are considered, especially in relation to utilitarianism
Mapping visual stimuli to perceptual decisions via sparse decoding of mesoscopic neural activity.
Sajda, Paul
2010-01-01
In this talk I will describe our work investigating sparse decoding of neural activity, given a realistic mapping of the visual scene to neuronal spike trains generated by a model of primary visual cortex (V1). We use a linear decoder which imposes sparsity via an L1 norm. The decoder can be viewed as a decoding neuron (linear summation followed by a sigmoidal nonlinearity) in which there are relatively few non-zero synaptic weights. We find: (1) the best decoding performance is for a representation that is sparse in both space and time, (2) decoding of a temporal code results in better performance than a rate code and is also a better fit to the psychophysical data, (3) the number of neurons required for decoding increases monotonically as signal-to-noise in the stimulus decreases, with as little as 1% of the neurons required for decoding at the highest signal-to-noise levels, and (4) sparse decoding results in a more accurate decoding of the stimulus and is a better fit to psychophysical performance than a distributed decoding, for example one imposed by an L2 norm. We conclude that sparse coding is well-justified from a decoding perspective in that it results in a minimum number of neurons and maximum accuracy when sparse representations can be decoded from the neural dynamics.
Gross, Charles A
2006-01-01
BASIC ELECTROMAGNETIC CONCEPTSBasic Magnetic ConceptsMagnetically Linear Systems: Magnetic CircuitsVoltage, Current, and Magnetic Field InteractionsMagnetic Properties of MaterialsNonlinear Magnetic Circuit AnalysisPermanent MagnetsSuperconducting MagnetsThe Fundamental Translational EM MachineThe Fundamental Rotational EM MachineMultiwinding EM SystemsLeakage FluxThe Concept of Ratings in EM SystemsSummaryProblemsTRANSFORMERSThe Ideal n-Winding TransformerTransformer Ratings and Per-Unit ScalingThe Nonideal Three-Winding TransformerThe Nonideal Two-Winding TransformerTransformer Efficiency and Voltage RegulationPractical ConsiderationsThe AutotransformerOperation of Transformers in Three-Phase EnvironmentsSequence Circuit Models for Three-Phase Transformer AnalysisHarmonics in TransformersSummaryProblemsBASIC MECHANICAL CONSIDERATIONSSome General PerspectivesEfficiencyLoad Torque-Speed CharacteristicsMass Polar Moment of InertiaGearingOperating ModesTranslational SystemsA Comprehensive Example: The ElevatorP...
International Nuclear Information System (INIS)
Medlin, J.B.
1976-01-01
A charging machine for loading fuel slugs into the process tubes of a nuclear reactor includes a tubular housing connected to the process tube, a charging trough connected to the other end of the tubular housing, a device for loading the charging trough with a group of fuel slugs, means for equalizing the coolant pressure in the charging trough with the pressure in the process tubes, means for pushing the group of fuel slugs into the process tube and a latch and a seal engaging the last object in the group of fuel slugs to prevent the fuel slugs from being ejected from the process tube when the pusher is removed and to prevent pressure liquid from entering the charging machine. 3 claims, 11 drawing figures
Robust pattern decoding in shape-coded structured light
Tang, Suming; Zhang, Xu; Song, Zhan; Song, Lifang; Zeng, Hai
2017-09-01
Decoding is a challenging and complex problem in a coded structured light system. In this paper, a robust pattern decoding method is proposed for the shape-coded structured light in which the pattern is designed as grid shape with embedded geometrical shapes. In our decoding method, advancements are made at three steps. First, a multi-template feature detection algorithm is introduced to detect the feature point which is the intersection of each two orthogonal grid-lines. Second, pattern element identification is modelled as a supervised classification problem and the deep neural network technique is applied for the accurate classification of pattern elements. Before that, a training dataset is established, which contains a mass of pattern elements with various blurring and distortions. Third, an error correction mechanism based on epipolar constraint, coplanarity constraint and topological constraint is presented to reduce the false matches. In the experiments, several complex objects including human hand are chosen to test the accuracy and robustness of the proposed method. The experimental results show that our decoding method not only has high decoding accuracy, but also owns strong robustness to surface color and complex textures.
Optimal and efficient decoding of concatenated quantum block codes
International Nuclear Information System (INIS)
Poulin, David
2006-01-01
We consider the problem of optimally decoding a quantum error correction code--that is, to find the optimal recovery procedure given the outcomes of partial ''check'' measurements on the system. In general, this problem is NP hard. However, we demonstrate that for concatenated block codes, the optimal decoding can be efficiently computed using a message-passing algorithm. We compare the performance of the message-passing algorithm to that of the widespread blockwise hard decoding technique. Our Monte Carlo results using the five-qubit and Steane's code on a depolarizing channel demonstrate significant advantages of the message-passing algorithms in two respects: (i) Optimal decoding increases by as much as 94% the error threshold below which the error correction procedure can be used to reliably send information over a noisy channel; and (ii) for noise levels below these thresholds, the probability of error after optimal decoding is suppressed at a significantly higher rate, leading to a substantial reduction of the error correction overhead
Distributed coding/decoding complexity in video sensor networks.
Cordeiro, Paulo J; Assunção, Pedro
2012-01-01
Video Sensor Networks (VSNs) are recent communication infrastructures used to capture and transmit dense visual information from an application context. In such large scale environments which include video coding, transmission and display/storage, there are several open problems to overcome in practical implementations. This paper addresses the most relevant challenges posed by VSNs, namely stringent bandwidth usage and processing time/power constraints. In particular, the paper proposes a novel VSN architecture where large sets of visual sensors with embedded processors are used for compression and transmission of coded streams to gateways, which in turn transrate the incoming streams and adapt them to the variable complexity requirements of both the sensor encoders and end-user decoder terminals. Such gateways provide real-time transcoding functionalities for bandwidth adaptation and coding/decoding complexity distribution by transferring the most complex video encoding/decoding tasks to the transcoding gateway at the expense of a limited increase in bit rate. Then, a method to reduce the decoding complexity, suitable for system-on-chip implementation, is proposed to operate at the transcoding gateway whenever decoders with constrained resources are targeted. The results show that the proposed method achieves good performance and its inclusion into the VSN infrastructure provides an additional level of complexity control functionality.
International Nuclear Information System (INIS)
Matos, João T.V.; Duarte, Regina M.B.O.; Lopes, Sónia P.; Silva, Artur M.S.; Duarte, Armando C.
2017-01-01
Organic Aerosols (OAs) are typically defined as highly complex matrices whose composition changes in time and space. Focusing on time vector, this work uses two-dimensional nuclear magnetic resonance (2D NMR) techniques to examine the structural features of water-soluble (WSOM) and alkaline-soluble organic matter (ASOM) sequentially extracted from fine atmospheric aerosols collected in an urban setting during cold and warm seasons. This study reveals molecular signatures not previously decoded in NMR-related studies of OAs as meaningful source markers. Although the ASOM is less hydrophilic and structurally diverse than its WSOM counterpart, both fractions feature a core with heteroatom-rich branched aliphatics from both primary (natural and anthropogenic) and secondary origin, aromatic secondary organics originated from anthropogenic aromatic precursors, as well as primary saccharides and amino sugar derivatives from biogenic emissions. These common structures represent those 2D NMR spectral signatures that are present in both seasons and can thus be seen as an “annual background” profile of the structural composition of OAs at the urban location. Lignin-derived structures, nitroaromatics, disaccharides, and anhydrosaccharides signatures were also identified in the WSOM samples only from periods identified as smoke impacted, which reflects the influence of biomass-burning sources. The NMR dataset on the H–C molecules backbone was also used to propose a semi-quantitative structural model of urban WSOM, which will aid efforts for more realistic studies relating the chemical properties of OAs with their atmospheric behavior. - Highlights: • 2D NMR spectroscopy was used to decode urban organic aerosols. • Water and alkaline soluble components of urban organic aerosols have been compared. • Persistence of urban organic aerosols composition across different seasons. • Annual background profile of the structural features of urban organic aerosols. • Semi
Amos, Martyn
2014-01-01
Silicon chips are out. Today's scientists are using real, wet, squishy, living biology to build the next generation of computers. Cells, gels and DNA strands are the 'wetware' of the twenty-first century. Much smaller and more intelligent, these organic computers open up revolutionary possibilities. Tracing the history of computing and revealing a brave new world to come, Genesis Machines describes how this new technology will change the way we think not just about computers - but about life itself.
A path-level exact parallelization strategy for sequential simulation
Peredo, Oscar F.; Baeza, Daniel; Ortiz, Julián M.; Herrero, José R.
2018-01-01
Sequential Simulation is a well known method in geostatistical modelling. Following the Bayesian approach for simulation of conditionally dependent random events, Sequential Indicator Simulation (SIS) method draws simulated values for K categories (categorical case) or classes defined by K different thresholds (continuous case). Similarly, Sequential Gaussian Simulation (SGS) method draws simulated values from a multivariate Gaussian field. In this work, a path-level approach to parallelize SIS and SGS methods is presented. A first stage of re-arrangement of the simulation path is performed, followed by a second stage of parallel simulation for non-conflicting nodes. A key advantage of the proposed parallelization method is to generate identical realizations as with the original non-parallelized methods. Case studies are presented using two sequential simulation codes from GSLIB: SISIM and SGSIM. Execution time and speedup results are shown for large-scale domains, with many categories and maximum kriging neighbours in each case, achieving high speedup results in the best scenarios using 16 threads of execution in a single machine.
Sequential versus simultaneous market delineation
DEFF Research Database (Denmark)
Haldrup, Niels; Møllgaard, Peter; Kastberg Nielsen, Claus
2005-01-01
and geographical markets. Using a unique data setfor prices of Norwegian and Scottish salmon, we propose a methodologyfor simultaneous market delineation and we demonstrate that comparedto a sequential approach conclusions will be reversed.JEL: C3, K21, L41, Q22Keywords: Relevant market, econometric delineation......Delineation of the relevant market forms a pivotal part of most antitrustcases. The standard approach is sequential. First the product marketis delineated, then the geographical market is defined. Demand andsupply substitution in both the product dimension and the geographicaldimension...
Directory of Open Access Journals (Sweden)
Konstantin D. Bergmeister
2017-07-01
Full Text Available Modern robotic hands/upper limbs may replace multiple degrees of freedom of extremity function. However, their intuitive use requires a high number of control signals, which current man-machine interfaces do not provide. Here, we discuss a broadband control interface that combines targeted muscle reinnervation, implantable multichannel electromyographic sensors, and advanced decoding to address the increasing capabilities of modern robotic limbs. With targeted muscle reinnervation, nerves that have lost their targets due to an amputation are surgically transferred to residual stump muscles to increase the number of intuitive prosthetic control signals. This surgery re-establishes a nerve-muscle connection that is used for sensing nerve activity with myoelectric interfaces. Moreover, the nerve transfer determines neurophysiological effects, such as muscular hyper-reinnervation and cortical reafferentation that can be exploited by the myoelectric interface. Modern implantable multichannel EMG sensors provide signals from which it is possible to disentangle the behavior of single motor neurons. Recent studies have shown that the neural drive to muscles can be decoded from these signals and thereby the user's intention can be reliably estimated. By combining these concepts in chronic implants and embedded electronics, we believe that it is in principle possible to establish a broadband man-machine interface, with specific applications in prosthesis control. This perspective illustrates this concept, based on combining advanced surgical techniques with recording hardware and processing algorithms. Here we describe the scientific evidence for this concept, current state of investigations, challenges, and alternative approaches to improve current prosthetic interfaces.
Zafar, Raheel; Kamel, Nidal; Naufal, Mohamad; Malik, Aamir Saeed; Dass, Sarat C; Ahmad, Rana Fayyaz; Abdullah, Jafri M; Reza, Faruque
2017-01-01
Decoding of human brain activity has always been a primary goal in neuroscience especially with functional magnetic resonance imaging (fMRI) data. In recent years, Convolutional neural network (CNN) has become a popular method for the extraction of features due to its higher accuracy, however it needs a lot of computation and training data. In this study, an algorithm is developed using Multivariate pattern analysis (MVPA) and modified CNN to decode the behavior of brain for different images with limited data set. Selection of significant features is an important part of fMRI data analysis, since it reduces the computational burden and improves the prediction performance; significant features are selected using t-test. MVPA uses machine learning algorithms to classify different brain states and helps in prediction during the task. General linear model (GLM) is used to find the unknown parameters of every individual voxel and the classification is done using multi-class support vector machine (SVM). MVPA-CNN based proposed algorithm is compared with region of interest (ROI) based method and MVPA based estimated values. The proposed method showed better overall accuracy (68.6%) compared to ROI (61.88%) and estimation values (64.17%).
Analysis of Minimal LDPC Decoder System on a Chip Implementation
Directory of Open Access Journals (Sweden)
T. Palenik
2015-09-01
Full Text Available This paper presents a practical method of potential replacement of several different Quasi-Cyclic Low-Density Parity-Check (QC-LDPC codes with one, with the intention of saving as much memory as required to implement the LDPC encoder and decoder in a memory-constrained System on a Chip (SoC. The presented method requires only a very small modification of the existing encoder and decoder, making it suitable for utilization in a Software Defined Radio (SDR platform. Besides the analysis of the effects of necessary variable-node value fixation during the Belief Propagation (BP decoding algorithm, practical standard-defined code parameters are scrutinized in order to evaluate the feasibility of the proposed LDPC setup simplification. Finally, the error performance of the modified system structure is evaluated and compared with the original system structure by means of simulation.
Analysis and Design of Binary Message-Passing Decoders
DEFF Research Database (Denmark)
Lechner, Gottfried; Pedersen, Troels; Kramer, Gerhard
2012-01-01
Binary message-passing decoders for low-density parity-check (LDPC) codes are studied by using extrinsic information transfer (EXIT) charts. The channel delivers hard or soft decisions and the variable node decoder performs all computations in the L-value domain. A hard decision channel results...... message-passing decoders. Finally, it is shown that errors on cycles consisting only of degree two and three variable nodes cannot be corrected and a necessary and sufficient condition for the existence of a cycle-free subgraph is derived....... in the well-know Gallager B algorithm, and increasing the output alphabet from hard decisions to two bits yields a gain of more than 1.0 dB in the required signal to noise ratio when using optimized codes. The code optimization requires adapting the mixing property of EXIT functions to the case of binary...
Evaluation Using Sequential Trials Methods.
Cohen, Mark E.; Ralls, Stephen A.
1986-01-01
Although dental school faculty as well as practitioners are interested in evaluating products and procedures used in clinical practice, research design and statistical analysis can sometimes pose problems. Sequential trials methods provide an analytical structure that is both easy to use and statistically valid. (Author/MLW)
Attack Trees with Sequential Conjunction
Jhawar, Ravi; Kordy, Barbara; Mauw, Sjouke; Radomirović, Sasa; Trujillo-Rasua, Rolando
2015-01-01
We provide the first formal foundation of SAND attack trees which are a popular extension of the well-known attack trees. The SAND at- tack tree formalism increases the expressivity of attack trees by intro- ducing the sequential conjunctive operator SAND. This operator enables the modeling of
Error-correction coding and decoding bounds, codes, decoders, analysis and applications
Tomlinson, Martin; Ambroze, Marcel A; Ahmed, Mohammed; Jibril, Mubarak
2017-01-01
This book discusses both the theory and practical applications of self-correcting data, commonly known as error-correcting codes. The applications included demonstrate the importance of these codes in a wide range of everyday technologies, from smartphones to secure communications and transactions. Written in a readily understandable style, the book presents the authors’ twenty-five years of research organized into five parts: Part I is concerned with the theoretical performance attainable by using error correcting codes to achieve communications efficiency in digital communications systems. Part II explores the construction of error-correcting codes and explains the different families of codes and how they are designed. Techniques are described for producing the very best codes. Part III addresses the analysis of low-density parity-check (LDPC) codes, primarily to calculate their stopping sets and low-weight codeword spectrum which determines the performance of these codes. Part IV deals with decoders desi...
The fast decoding of Reed-Solomon codes using Fermat theoretic transforms and continued fractions
Reed, I. S.; Scholtz, R. A.; Welch, L. R.; Truong, T. K.
1978-01-01
It is shown that Reed-Solomon (RS) codes can be decoded by using a fast Fourier transform (FFT) algorithm over finite fields GF(F sub n), where F sub n is a Fermat prime, and continued fractions. This new transform decoding method is simpler than the standard method for RS codes. The computing time of this new decoding algorithm in software can be faster than the standard decoding method for RS codes.
Efficient decoding of random errors for quantum expander codes
Fawzi , Omar; Grospellier , Antoine; Leverrier , Anthony
2017-01-01
We show that quantum expander codes, a constant-rate family of quantum LDPC codes, with the quasi-linear time decoding algorithm of Leverrier, Tillich and Z\\'emor can correct a constant fraction of random errors with very high probability. This is the first construction of a constant-rate quantum LDPC code with an efficient decoding algorithm that can correct a linear number of random errors with a negligible failure probability. Finding codes with these properties is also motivated by Gottes...
Min-Max decoding for non binary LDPC codes
Savin, Valentin
2008-01-01
Iterative decoding of non-binary LDPC codes is currently performed using either the Sum-Product or the Min-Sum algorithms or slightly different versions of them. In this paper, several low-complexity quasi-optimal iterative algorithms are proposed for decoding non-binary codes. The Min-Max algorithm is one of them and it has the benefit of two possible LLR domain implementations: a standard implementation, whose complexity scales as the square of the Galois field's cardinality and a reduced c...
Decoding ensemble activity from neurophysiological recordings in the temporal cortex.
Kreiman, Gabriel
2011-01-01
We study subjects with pharmacologically intractable epilepsy who undergo semi-chronic implantation of electrodes for clinical purposes. We record physiological activity from tens to more than one hundred electrodes implanted in different parts of neocortex. These recordings provide higher spatial and temporal resolution than non-invasive measures of human brain activity. Here we discuss our efforts to develop hardware and algorithms to interact with the human brain by decoding ensemble activity in single trials. We focus our discussion on decoding visual information during a variety of visual object recognition tasks but the same technologies and algorithms can also be directly applied to other cognitive phenomena.
Linear-time general decoding algorithm for the surface code
Darmawan, Andrew S.; Poulin, David
2018-05-01
A quantum error correcting protocol can be substantially improved by taking into account features of the physical noise process. We present an efficient decoder for the surface code which can account for general noise features, including coherences and correlations. We demonstrate that the decoder significantly outperforms the conventional matching algorithm on a variety of noise models, including non-Pauli noise and spatially correlated noise. The algorithm is based on an approximate calculation of the logical channel using a tensor-network description of the noisy state.
A New profiling and pipelining approach for HEVC Decoder on ZedBoard Platform
Directory of Open Access Journals (Sweden)
Habib Smei
2017-10-01
Full Text Available New multimedia applications such as mobile video, high-quality Internet video or digital television requires high-performance encoding of video signals to meet technical constraints such as runtime, bandwidth or latency. Video coding standard h.265 HEVC (High Efficiency Video Coding was developed by JCT-VC to replace the MPEG-2, MPEG-4 and h.264 codecs and to respond to these new functional constraints. Currently, there are several implementations of this standard. Some implementations are based on software acceleration techniques; Others, on techniques of purely hardware acceleration and some others combine the two techniques. In software implementations, several techniques are used in order to decrease the video coding and decoding time. We quote data parallelism, tasks parallelism and combined solutions. In the other hand, In order to fulfill the computational demands of the new standard, HEVC includes several coding tools that allow dividing each picture into several partitions that can be processed in parallel, without degrading neither the quality nor the bitrate. In this paper, we adapt one of these approaches, the Tile coding tool to propose a pipeline execution approach of the HEVC / h265 decoder application in its version HM Test model. This approach is based on a fine profiling by using code injection techniques supported by standard profiling tools such as Gprof and Valgrind. Profiling allowed us to divide functions into four groups according to three criteria: the first criterion is based on the minimization of communication between the different functions groups in order to have minimal intergroup communication and maximum intragroup communication. The second criterion is the load balancing between processors. The third criterion is the parallelism between functions. Experiments carried out in this paper are based on the Zedboard platform, which integrates a chip Zynq xilinx with a dual core ARM A9. We start with a purely
Alsolami, Fawaz
2013-01-01
This paper is devoted to the study of algorithms for sequential optimization of approximate inhibitory rules relative to the length, coverage and number of misclassifications. Theses algorithms are based on extensions of dynamic programming approach. The results of experiments for decision tables from UCI Machine Learning Repository are discussed. © 2013 Springer-Verlag.
Hofmann, Jennifer
2014-01-01
Joyful laughter is the only laughter type that has received sufficient validation in terms of morphology (i.e., face, voice). Still, it is unclear whether joyful laughter involves one prototypical facial-morphological configuration (Duchenne Display and mouth opening) to be decoded as such, or whether qualitatively distinct facial markers occur at different stages of laughter intensity. It was proposed that intense laughter goes along with eyebrow-lowering frowning, but in decoding studies of pictures, these “frowns” were associated with perceived maliciousness rather than higher intensity. Thus, two studies were conducted to investigate the influence of the presentation mode (static, dynamic) and eyebrow-lowering frowning on the perception of laughter animations of different intensity. In Study 1, participants (N = 110) were randomly assigned to two presentation modes (static pictures vs. dynamic videos) to watch animations of Duchenne laughter and laughter with added eyebrow-lowering frowning. Ratings on the intensity, valence, and contagiousness of the laughter were completed. In Study 2, participants (N = 55) saw both animation types in both presentation modes sequentially. Results confirmed that the static presentation lead to eyebrow-lowering frowning in intense laughter being perceived as more malicious, less intense, less benevolent, and less contagious compared to the dynamic presentation. This was replicated for maliciousness in Study 2, although participants could potentially infer the “frown” as a natural element of the laugh, as they had seen the video and the picture. Thus, a dynamic presentation is necessary for detecting graduating intensity markers in the joyfully laughing face. While this study focused on the decoding, future studies should investigate the encoding of frowning in laughter. This is important, as tools assessing facially expressed joy might need to account for laughter intensity markers that differ from the Duchenne Display
DEFF Research Database (Denmark)
Photography not only represents space. Space is produced photographically. Since its inception in the 19th century, photography has brought to light a vast array of represented subjects. Always situated in some spatial order, photographic representations have been operatively underpinned by social...... to the enterprises of the medium. This is the subject of Representational Machines: How photography enlists the workings of institutional technologies in search of establishing new iconic and social spaces. Together, the contributions to this edited volume span historical epochs, social environments, technological...... possibilities, and genre distinctions. Presenting several distinct ways of producing space photographically, this book opens a new and important field of inquiry for photography research....
International Nuclear Information System (INIS)
Astill, M.; Sunderland, A.; Waine, M.G.
1980-01-01
A shear machine for irradiated nuclear fuel elements has a replaceable shear assembly comprising a fuel element support block, a shear blade support and a clamp assembly which hold the fuel element to be sheared in contact with the support block. A first clamp member contacts the fuel element remote from the shear blade and a second clamp member contacts the fuel element adjacent the shear blade and is advanced towards the support block during shearing to compensate for any compression of the fuel element caused by the shear blade (U.K.)
Directory of Open Access Journals (Sweden)
David G. Daut
2007-03-01
Full Text Available A joint source-channel decoding method is designed to accelerate the iterative log-domain sum-product decoding procedure of LDPC codes as well as to improve the reconstructed image quality. Error resilience modes are used in the JPEG2000 source codec making it possible to provide useful source decoded information to the channel decoder. After each iteration, a tentative decoding is made and the channel decoded bits are then sent to the JPEG2000 decoder. The positions of bits belonging to error-free coding passes are then fed back to the channel decoder. The log-likelihood ratios (LLRs of these bits are then modified by a weighting factor for the next iteration. By observing the statistics of the decoding procedure, the weighting factor is designed as a function of the channel condition. Results show that the proposed joint decoding methods can greatly reduce the number of iterations, and thereby reduce the decoding delay considerably. At the same time, this method always outperforms the nonsource controlled decoding method by up to 3 dB in terms of PSNR.
Directory of Open Access Journals (Sweden)
Liu Weiliang
2007-01-01
Full Text Available A joint source-channel decoding method is designed to accelerate the iterative log-domain sum-product decoding procedure of LDPC codes as well as to improve the reconstructed image quality. Error resilience modes are used in the JPEG2000 source codec making it possible to provide useful source decoded information to the channel decoder. After each iteration, a tentative decoding is made and the channel decoded bits are then sent to the JPEG2000 decoder. The positions of bits belonging to error-free coding passes are then fed back to the channel decoder. The log-likelihood ratios (LLRs of these bits are then modified by a weighting factor for the next iteration. By observing the statistics of the decoding procedure, the weighting factor is designed as a function of the channel condition. Results show that the proposed joint decoding methods can greatly reduce the number of iterations, and thereby reduce the decoding delay considerably. At the same time, this method always outperforms the nonsource controlled decoding method by up to 3 dB in terms of PSNR.
Construction and decoding of matrix-product codes from nested codes
DEFF Research Database (Denmark)
Hernando, Fernando; Lally, Kristine; Ruano, Diego
2009-01-01
We consider matrix-product codes [C1 ... Cs] · A, where C1, ..., Cs are nested linear codes and matrix A has full rank. We compute their minimum distance and provide a decoding algorithm when A is a non-singular by columns matrix. The decoding algorithm decodes up to half of the minimum distance....
Adaptive decoding of MPEG-4 sprites for memory-constrained embedded systems
Pastrnak, M.; Farin, D.S.; With, de P.H.N.; Cardinal, J.; Cerf, N.; Delgrnage, O.
2005-01-01
Background sprite decoding is an essential part of object-based video coding.The composition and rendering of a final scene involves the placing of individual video objects in a predefined way superimposed on the decoded background image. The MPEG-4 standard includes the decoding algorithm for
International Nuclear Information System (INIS)
Gijeon media editorial department
1977-10-01
This book is divided into three parts. The first part deals with electricity machine, which can taints from generator to motor, motor a power source of machine tool, electricity machine for machine tool such as switch in main circuit, automatic machine, a knife switch and pushing button, snap switch, protection device, timer, solenoid, and rectifier. The second part handles wiring diagram. This concludes basic electricity circuit of machine tool, electricity wiring diagram in your machine like milling machine, planer and grinding machine. The third part introduces fault diagnosis of machine, which gives the practical solution according to fault diagnosis and the diagnostic method with voltage and resistance measurement by tester.
Environmentally Friendly Machining
Dixit, U S; Davim, J Paulo
2012-01-01
Environment-Friendly Machining provides an in-depth overview of environmentally-friendly machining processes, covering numerous different types of machining in order to identify which practice is the most environmentally sustainable. The book discusses three systems at length: machining with minimal cutting fluid, air-cooled machining and dry machining. Also covered is a way to conserve energy during machining processes, along with useful data and detailed descriptions for developing and utilizing the most efficient modern machining tools. Researchers and engineers looking for sustainable machining solutions will find Environment-Friendly Machining to be a useful volume.
Schmidt, R
2014-01-01
The protection of accelerator equipment is as old as accelerator technology and was for many years related to high-power equipment. Examples are the protection of powering equipment from overheating (magnets, power converters, high-current cables), of superconducting magnets from damage after a quench and of klystrons. The protection of equipment from beam accidents is more recent. It is related to the increasing beam power of high-power proton accelerators such as ISIS, SNS, ESS and the PSI cyclotron, to the emission of synchrotron light by electron–positron accelerators and FELs, and to the increase of energy stored in the beam (in particular for hadron colliders such as LHC). Designing a machine protection system requires an excellent understanding of accelerator physics and operation to anticipate possible failures that could lead to damage. Machine protection includes beam and equipment monitoring, a system to safely stop beam operation (e.g. dumping the beam or stopping the beam at low energy) and an ...
Multi-agent sequential hypothesis testing
Kim, Kwang-Ki K.; Shamma, Jeff S.
2014-01-01
incorporate costs of taking private/public measurements, costs of time-difference and disagreement in actions of agents, and costs of false declaration/choices in the sequential hypothesis testing. The corresponding sequential decision processes have well
Decoding sound level in the marmoset primary auditory cortex.
Sun, Wensheng; Marongelli, Ellisha N; Watkins, Paul V; Barbour, Dennis L
2017-10-01
Neurons that respond favorably to a particular sound level have been observed throughout the central auditory system, becoming steadily more common at higher processing areas. One theory about the role of these level-tuned or nonmonotonic neurons is the level-invariant encoding of sounds. To investigate this theory, we simulated various subpopulations of neurons by drawing from real primary auditory cortex (A1) neuron responses and surveyed their performance in forming different sound level representations. Pure nonmonotonic subpopulations did not provide the best level-invariant decoding; instead, mixtures of monotonic and nonmonotonic neurons provided the most accurate decoding. For level-fidelity decoding, the inclusion of nonmonotonic neurons slightly improved or did not change decoding accuracy until they constituted a high proportion. These results indicate that nonmonotonic neurons fill an encoding role complementary to, rather than alternate to, monotonic neurons. NEW & NOTEWORTHY Neurons with nonmonotonic rate-level functions are unique to the central auditory system. These level-tuned neurons have been proposed to account for invariant sound perception across sound levels. Through systematic simulations based on real neuron responses, this study shows that neuron populations perform sound encoding optimally when containing both monotonic and nonmonotonic neurons. The results indicate that instead of working independently, nonmonotonic neurons complement the function of monotonic neurons in different sound-encoding contexts. Copyright © 2017 the American Physiological Society.
Complete ML Decoding orf the (73,45) PG Code
DEFF Research Database (Denmark)
Justesen, Jørn; Høholdt, Tom; Hjaltason, Johan
2005-01-01
Our recent proof of the completeness of decoding by list bit flipping is reviewed. The proof is based on an enumeration of all cosets of low weight in terms of their minimum weight and syndrome weight. By using a geometric description of the error patterns we characterize all remaining cosets....
Decoding Representations: How Children with Autism Understand Drawings
Allen, Melissa L.
2009-01-01
Young typically developing children can reason about abstract depictions if they know the intention of the artist. Children with autism spectrum disorder (ASD), who are notably impaired in social, "intention monitoring" domains, may have great difficulty in decoding vague representations. In Experiment 1, children with ASD are unable to use…
A quantum algorithm for Viterbi decoding of classical convolutional codes
Grice, Jon R.; Meyer, David A.
2015-07-01
We present a quantum Viterbi algorithm (QVA) with better than classical performance under certain conditions. In this paper, the proposed algorithm is applied to decoding classical convolutional codes, for instance, large constraint length and short decode frames . Other applications of the classical Viterbi algorithm where is large (e.g., speech processing) could experience significant speedup with the QVA. The QVA exploits the fact that the decoding trellis is similar to the butterfly diagram of the fast Fourier transform, with its corresponding fast quantum algorithm. The tensor-product structure of the butterfly diagram corresponds to a quantum superposition that we show can be efficiently prepared. The quantum speedup is possible because the performance of the QVA depends on the fanout (number of possible transitions from any given state in the hidden Markov model) which is in general much less than . The QVA constructs a superposition of states which correspond to all legal paths through the decoding lattice, with phase as a function of the probability of the path being taken given received data. A specialized amplitude amplification procedure is applied one or more times to recover a superposition where the most probable path has a high probability of being measured.
The Fluid Reading Primer: Animated Decoding Support for Emergent Readers.
Zellweger, Polle T.; Mackinlay, Jock D.
A prototype application called the Fluid Reading Primer was developed to help emergent readers with the process of decoding written words into their spoken forms. The Fluid Reading Primer is part of a larger research project called Fluid Documents, which is exploring the use of interactive animation of typography to show additional information in…
Adaptive Combined Source and Channel Decoding with Modulation ...
African Journals Online (AJOL)
In this paper, an adaptive system employing combined source and channel decoding with modulation is proposed for slow Rayleigh fading channels. Huffman code is used as the source code and Convolutional code is used for error control. The adaptive scheme employs a family of Convolutional codes of different rates ...
Peeling Decoding of LDPC Codes with Applications in Compressed Sensing
Directory of Open Access Journals (Sweden)
Weijun Zeng
2016-01-01
Full Text Available We present a new approach for the analysis of iterative peeling decoding recovery algorithms in the context of Low-Density Parity-Check (LDPC codes and compressed sensing. The iterative recovery algorithm is particularly interesting for its low measurement cost and low computational complexity. The asymptotic analysis can track the evolution of the fraction of unrecovered signal elements in each iteration, which is similar to the well-known density evolution analysis in the context of LDPC decoding algorithm. Our analysis shows that there exists a threshold on the density factor; if under this threshold, the recovery algorithm is successful; otherwise it will fail. Simulation results are also provided for verifying the agreement between the proposed asymptotic analysis and recovery algorithm. Compared with existing works of peeling decoding algorithm, focusing on the failure probability of the recovery algorithm, our proposed approach gives accurate evolution of performance with different parameters of measurement matrices and is easy to implement. We also show that the peeling decoding algorithm performs better than other schemes based on LDPC codes.
High-throughput GPU-based LDPC decoding
Chang, Yang-Lang; Chang, Cheng-Chun; Huang, Min-Yu; Huang, Bormin
2010-08-01
Low-density parity-check (LDPC) code is a linear block code known to approach the Shannon limit via the iterative sum-product algorithm. LDPC codes have been adopted in most current communication systems such as DVB-S2, WiMAX, WI-FI and 10GBASE-T. LDPC for the needs of reliable and flexible communication links for a wide variety of communication standards and configurations have inspired the demand for high-performance and flexibility computing. Accordingly, finding a fast and reconfigurable developing platform for designing the high-throughput LDPC decoder has become important especially for rapidly changing communication standards and configurations. In this paper, a new graphic-processing-unit (GPU) LDPC decoding platform with the asynchronous data transfer is proposed to realize this practical implementation. Experimental results showed that the proposed GPU-based decoder achieved 271x speedup compared to its CPU-based counterpart. It can serve as a high-throughput LDPC decoder.
Real Time Decoding of Color Symbol for Optical Positioning System
Directory of Open Access Journals (Sweden)
Abdul Waheed Malik
2015-01-01
Full Text Available This paper presents the design and real-time decoding of a color symbol that can be used as a reference marker for optical navigation. The designed symbol has a circular shape and is printed on paper using two distinct colors. This pair of colors is selected based on the highest achievable signal to noise ratio. The symbol is designed to carry eight bit information. Real time decoding of this symbol is performed using a heterogeneous combination of Field Programmable Gate Array (FPGA and a microcontroller. An image sensor having a resolution of 1600 by 1200 pixels is used to capture images of symbols in complex backgrounds. Dynamic image segmentation, component labeling and feature extraction was performed on the FPGA. The region of interest was further computed from the extracted features. Feature data belonging to the symbol was sent from the FPGA to the microcontroller. Image processing tasks are partitioned between the FPGA and microcontroller based on data intensity. Experiments were performed to verify the rotational independence of the symbols. The maximum distance between camera and symbol allowing for correct detection and decoding was analyzed. Experiments were also performed to analyze the number of generated image components and sub-pixel precision versus different light sources and intensities. The proposed hardware architecture can process up to 55 frames per second for accurate detection and decoding of symbols at two Megapixels resolution. The power consumption of the complete system is 342mw.
Fast decoding of codes from algebraic plane curves
DEFF Research Database (Denmark)
Justesen, Jørn; Larsen, Knud J.; Jensen, Helge Elbrønd
1992-01-01
Improvement to an earlier decoding algorithm for codes from algebraic geometry is presented. For codes from an arbitrary regular plane curve the authors correct up to d*/2-m2 /8+m/4-9/8 errors, where d* is the designed distance of the code and m is the degree of the curve. The complexity of finding...
Name that tune: decoding music from the listening brain.
Schaefer, R.S.; Farquhar, J.D.R.; Blokland, Y.M.; Sadakata, M.; Desain, P.W.M.
2011-01-01
In the current study we use electroencephalography (EEG) to detect heard music from the brain signal, hypothesizing that the time structure in music makes it especially suitable for decoding perception from EEG signals. While excluding music with vocals, we classified the perception of seven
Name that tune: Decoding music from the listening brain
Schaefer, R.S.; Farquhar, J.D.R.; Blokland, Y.M.; Sadakata, M.; Desain, P.W.M.
2011-01-01
In the current study we use electroencephalography (EEG) to detect heard music from the brain signal, hypothesizing that the time structure in music makes it especially suitable for decoding perception from EEG signals. While excluding music with vocals, we classified the perception of seven
O2-GIDNC: Beyond instantly decodable network coding
Aboutorab, Neda; Sorour, Sameh; Sadeghi, Parastoo
2013-01-01
In this paper, we are concerned with extending the graph representation of generalized instantly decodable network coding (GIDNC) to a more general opportunistic network coding (ONC) scenario, referred to as order-2 GIDNC (O2-GIDNC). In the O2-GIDNC
EEG source imaging assists decoding in a face recognition task
DEFF Research Database (Denmark)
Andersen, Rasmus S.; Eliasen, Anders U.; Pedersen, Nicolai
2017-01-01
of face recognition. This task concerns the differentiation of brain responses to images of faces and scrambled faces and poses a rather difficult decoding problem at the single trial level. We implement the pipeline using spatially focused features and show that this approach is challenged and source...
LDPC-based iterative joint source-channel decoding for JPEG2000.
Pu, Lingling; Wu, Zhenyu; Bilgin, Ali; Marcellin, Michael W; Vasic, Bane
2007-02-01
A framework is proposed for iterative joint source-channel decoding of JPEG2000 codestreams. At the encoder, JPEG2000 is used to perform source coding with certain error-resilience (ER) modes, and LDPC codes are used to perform channel coding. During decoding, the source decoder uses the ER modes to identify corrupt sections of the codestream and provides this information to the channel decoder. Decoding is carried out jointly in an iterative fashion. Experimental results indicate that the proposed method requires fewer iterations and improves overall system performance.
Robustness of the Sequential Lineup Advantage
Gronlund, Scott D.; Carlson, Curt A.; Dailey, Sarah B.; Goodsell, Charles A.
2009-01-01
A growing movement in the United States and around the world involves promoting the advantages of conducting an eyewitness lineup in a sequential manner. We conducted a large study (N = 2,529) that included 24 comparisons of sequential versus simultaneous lineups. A liberal statistical criterion revealed only 2 significant sequential lineup…
Sequential Probability Ration Tests : Conservative and Robust
Kleijnen, J.P.C.; Shi, Wen
2017-01-01
In practice, most computers generate simulation outputs sequentially, so it is attractive to analyze these outputs through sequential statistical methods such as sequential probability ratio tests (SPRTs). We investigate several SPRTs for choosing between two hypothesized values for the mean output
Random sequential adsorption of cubes
Cieśla, Michał; Kubala, Piotr
2018-01-01
Random packings built of cubes are studied numerically using a random sequential adsorption algorithm. To compare the obtained results with previous reports, three different models of cube orientation sampling were used. Also, three different cube-cube intersection algorithms were tested to find the most efficient one. The study focuses on the mean saturated packing fraction as well as kinetics of packing growth. Microstructural properties of packings were analyzed using density autocorrelation function.
Analysis of machining and machine tools
Liang, Steven Y
2016-01-01
This book delivers the fundamental science and mechanics of machining and machine tools by presenting systematic and quantitative knowledge in the form of process mechanics and physics. It gives readers a solid command of machining science and engineering, and familiarizes them with the geometry and functionality requirements of creating parts and components in today’s markets. The authors address traditional machining topics, such as: single and multiple point cutting processes grinding components accuracy and metrology shear stress in cutting cutting temperature and analysis chatter They also address non-traditional machining, such as: electrical discharge machining electrochemical machining laser and electron beam machining A chapter on biomedical machining is also included. This book is appropriate for advanced undergraduate and graduate mechani cal engineering students, manufacturing engineers, and researchers. Each chapter contains examples, exercises and their solutions, and homework problems that re...
Multi-Class Motor Imagery EEG Decoding for Brain-Computer Interfaces
Wang, Deng; Miao, Duoqian; Blohm, Gunnar
2012-01-01
Recent studies show that scalp electroencephalography (EEG) as a non-invasive interface has great potential for brain-computer interfaces (BCIs). However, one factor that has limited practical applications for EEG-based BCI so far is the difficulty to decode brain signals in a reliable and efficient way. This paper proposes a new robust processing framework for decoding of multi-class motor imagery (MI) that is based on five main processing steps. (i) Raw EEG segmentation without the need of visual artifact inspection. (ii) Considering that EEG recordings are often contaminated not just by electrooculography (EOG) but also other types of artifacts, we propose to first implement an automatic artifact correction method that combines regression analysis with independent component analysis for recovering the original source signals. (iii) The significant difference between frequency components based on event-related (de-) synchronization and sample entropy is then used to find non-contiguous discriminating rhythms. After spectral filtering using the discriminating rhythms, a channel selection algorithm is used to select only relevant channels. (iv) Feature vectors are extracted based on the inter-class diversity and time-varying dynamic characteristics of the signals. (v) Finally, a support vector machine is employed for four-class classification. We tested our proposed algorithm on experimental data that was obtained from dataset 2a of BCI competition IV (2008). The overall four-class kappa values (between 0.41 and 0.80) were comparable to other models but without requiring any artifact-contaminated trial removal. The performance showed that multi-class MI tasks can be reliably discriminated using artifact-contaminated EEG recordings from a few channels. This may be a promising avenue for online robust EEG-based BCI applications. PMID:23087607
Astrand, Elaine
2018-06-01
Working memory (WM), crucial for successful behavioral performance in most of our everyday activities, holds a central role in goal-directed behavior. As task demands increase, inducing higher WM load, maintaining successful behavioral performance requires the brain to work at the higher end of its capacity. Because it is depending on both external and internal factors, individual WM load likely varies in a continuous fashion. The feasibility to extract such a continuous measure in time that correlates to behavioral performance during a working memory task remains unsolved. Multivariate pattern decoding was used to test whether a decoder constructed from two discrete levels of WM load can generalize to produce a continuous measure that predicts task performance. Specifically, a linear regression with L2-regularization was chosen with input features from EEG oscillatory activity recorded from healthy participants while performing the n-back task, [Formula: see text]. The feasibility to extract a continuous time-resolved measure that correlates positively to trial-by-trial working memory task performance is demonstrated (r = 0.47, p performance before action (r = 0.49, p < 0.05). We show that the extracted continuous measure enables to study the temporal dynamics of the complex activation pattern of WM encoding during the n-back task. Specifically, temporally precise contributions of different spectral features are observed which extends previous findings of traditional univariate approaches. These results constitute an important contribution towards a wide range of applications in the field of cognitive brain-machine interfaces. Monitoring mental processes related to attention and WM load to reduce the risk of committing errors in high-risk environments could potentially prevent many devastating consequences or using the continuous measure as neurofeedback opens up new possibilities to develop novel rehabilitation techniques for
International Nuclear Information System (INIS)
Schmidt, R
2014-01-01
The protection of accelerator equipment is as old as accelerator technology and was for many years related to high-power equipment. Examples are the protection of powering equipment from overheating (magnets, power converters, high-current cables), of superconducting magnets from damage after a quench and of klystrons. The protection of equipment from beam accidents is more recent. It is related to the increasing beam power of high-power proton accelerators such as ISIS, SNS, ESS and the PSI cyclotron, to the emission of synchrotron light by electron–positron accelerators and FELs, and to the increase of energy stored in the beam (in particular for hadron colliders such as LHC). Designing a machine protection system requires an excellent understanding of accelerator physics and operation to anticipate possible failures that could lead to damage. Machine protection includes beam and equipment monitoring, a system to safely stop beam operation (e.g. dumping the beam or stopping the beam at low energy) and an interlock system providing the glue between these systems. The most recent accelerator, the LHC, will operate with about 3 × 10 14 protons per beam, corresponding to an energy stored in each beam of 360 MJ. This energy can cause massive damage to accelerator equipment in case of uncontrolled beam loss, and a single accident damaging vital parts of the accelerator could interrupt operation for years. This article provides an overview of the requirements for protection of accelerator equipment and introduces the various protection systems. Examples are mainly from LHC, SNS and ESS
Multi-stage decoding for multi-level block modulation codes
Lin, Shu
1991-01-01
In this paper, we investigate various types of multi-stage decoding for multi-level block modulation codes, in which the decoding of a component code at each stage can be either soft-decision or hard-decision, maximum likelihood or bounded-distance. Error performance of codes is analyzed for a memoryless additive channel based on various types of multi-stage decoding, and upper bounds on the probability of an incorrect decoding are derived. Based on our study and computation results, we find that, if component codes of a multi-level modulation code and types of decoding at various stages are chosen properly, high spectral efficiency and large coding gain can be achieved with reduced decoding complexity. In particular, we find that the difference in performance between the suboptimum multi-stage soft-decision maximum likelihood decoding of a modulation code and the single-stage optimum decoding of the overall code is very small: only a fraction of dB loss in SNR at the probability of an incorrect decoding for a block of 10(exp -6). Multi-stage decoding of multi-level modulation codes really offers a way to achieve the best of three worlds, bandwidth efficiency, coding gain, and decoding complexity.
Real-time SHVC software decoding with multi-threaded parallel processing
Gudumasu, Srinivas; He, Yuwen; Ye, Yan; He, Yong; Ryu, Eun-Seok; Dong, Jie; Xiu, Xiaoyu
2014-09-01
This paper proposes a parallel decoding framework for scalable HEVC (SHVC). Various optimization technologies are implemented on the basis of SHVC reference software SHM-2.0 to achieve real-time decoding speed for the two layer spatial scalability configuration. SHVC decoder complexity is analyzed with profiling information. The decoding process at each layer and the up-sampling process are designed in parallel and scheduled by a high level application task manager. Within each layer, multi-threaded decoding is applied to accelerate the layer decoding speed. Entropy decoding, reconstruction, and in-loop processing are pipeline designed with multiple threads based on groups of coding tree units (CTU). A group of CTUs is treated as a processing unit in each pipeline stage to achieve a better trade-off between parallelism and synchronization. Motion compensation, inverse quantization, and inverse transform modules are further optimized with SSE4 SIMD instructions. Simulations on a desktop with an Intel i7 processor 2600 running at 3.4 GHz show that the parallel SHVC software decoder is able to decode 1080p spatial 2x at up to 60 fps (frames per second) and 1080p spatial 1.5x at up to 50 fps for those bitstreams generated with SHVC common test conditions in the JCT-VC standardization group. The decoding performance at various bitrates with different optimization technologies and different numbers of threads are compared in terms of decoding speed and resource usage, including processor and memory.
Low Complexity Approach for High Throughput Belief-Propagation based Decoding of LDPC Codes
Directory of Open Access Journals (Sweden)
BOT, A.
2013-11-01
Full Text Available The paper proposes a low complexity belief propagation (BP based decoding algorithm for LDPC codes. In spite of the iterative nature of the decoding process, the proposed algorithm provides both reduced complexity and increased BER performances as compared with the classic min-sum (MS algorithm, generally used for hardware implementations. Linear approximations of check-nodes update function are used in order to reduce the complexity of the BP algorithm. Considering this decoding approach, an FPGA based hardware architecture is proposed for implementing the decoding algorithm, aiming to increase the decoder throughput. FPGA technology was chosen for the LDPC decoder implementation, due to its parallel computation and reconfiguration capabilities. The obtained results show improvements regarding decoding throughput and BER performances compared with state-of-the-art approaches.
Low Power LDPC Code Decoder Architecture Based on Intermediate Message Compression Technique
Shimizu, Kazunori; Togawa, Nozomu; Ikenaga, Takeshi; Goto, Satoshi
Reducing the power dissipation for LDPC code decoder is a major challenging task to apply it to the practical digital communication systems. In this paper, we propose a low power LDPC code decoder architecture based on an intermediate message-compression technique which features as follows: (i) An intermediate message compression technique enables the decoder to reduce the required memory capacity and write power dissipation. (ii) A clock gated shift register based intermediate message memory architecture enables the decoder to decompress the compressed messages in a single clock cycle while reducing the read power dissipation. The combination of the above two techniques enables the decoder to reduce the power dissipation while keeping the decoding throughput. The simulation results show that the proposed architecture improves the power efficiency up to 52% and 18% compared to that of the decoder based on the overlapped schedule and the rapid convergence schedule without the proposed techniques respectively.
Design of FBG En/decoders in Coherent 2-D Time-polarization OCDMA Systems
Hou, Fen-fei; Yang, Ming
2012-12-01
A novel fiber Bragg grating (FBG)-based en/decoder for the two-dimensional (2-D) time-spreading and polarization multiplexer optical coding is proposed. Compared with other 2-D en/decoders, the proposed en/decoding for an optical code-division multiple-access (OCDMA) system uses a single phase-encoded FBG and coherent en/decoding. Furthermore, combined with reconstruction-equivalent-chirp technology, such en/decoders can be realized with a conventional simple fabrication setup. Experimental results of such en/decoders and the corresponding system test at a data rate of 5 Gbit/s demonstrate that this kind of 2-D FBG-based en/decoders could improve the performances of OCDMA systems.
Energy Technology Data Exchange (ETDEWEB)
NONE
1979-04-15
This book gives descriptions of machine terms which includes machine design, drawing, the method of machine, machine tools, machine materials, automobile, measuring and controlling, electricity, basic of electron, information technology, quality assurance, Auto CAD and FA terms and important formula of mechanical engineering.
Optimal interference code based on machine learning
Qian, Ye; Chen, Qian; Hu, Xiaobo; Cao, Ercong; Qian, Weixian; Gu, Guohua
2016-10-01
In this paper, we analyze the characteristics of pseudo-random code, by the case of m sequence. Depending on the description of coding theory, we introduce the jamming methods. We simulate the interference effect or probability model by the means of MATLAB to consolidate. In accordance with the length of decoding time the adversary spends, we find out the optimal formula and optimal coefficients based on machine learning, then we get the new optimal interference code. First, when it comes to the phase of recognition, this study judges the effect of interference by the way of simulating the length of time over the decoding period of laser seeker. Then, we use laser active deception jamming simulate interference process in the tracking phase in the next block. In this study we choose the method of laser active deception jamming. In order to improve the performance of the interference, this paper simulates the model by MATLAB software. We find out the least number of pulse intervals which must be received, then we can make the conclusion that the precise interval number of the laser pointer for m sequence encoding. In order to find the shortest space, we make the choice of the greatest common divisor method. Then, combining with the coding regularity that has been found before, we restore pulse interval of pseudo-random code, which has been already received. Finally, we can control the time period of laser interference, get the optimal interference code, and also increase the probability of interference as well.
Decoding the genome with an integrative analysis tool: combinatorial CRM Decoder.
Kang, Keunsoo; Kim, Joomyeong; Chung, Jae Hoon; Lee, Daeyoup
2011-09-01
The identification of genome-wide cis-regulatory modules (CRMs) and characterization of their associated epigenetic features are fundamental steps toward the understanding of gene regulatory networks. Although integrative analysis of available genome-wide information can provide new biological insights, the lack of novel methodologies has become a major bottleneck. Here, we present a comprehensive analysis tool called combinatorial CRM decoder (CCD), which utilizes the publicly available information to identify and characterize genome-wide CRMs in a species of interest. CCD first defines a set of the epigenetic features which is significantly associated with a set of known CRMs as a code called 'trace code', and subsequently uses the trace code to pinpoint putative CRMs throughout the genome. Using 61 genome-wide data sets obtained from 17 independent mouse studies, CCD successfully catalogued ∼12 600 CRMs (five distinct classes) including polycomb repressive complex 2 target sites as well as imprinting control regions. Interestingly, we discovered that ∼4% of the identified CRMs belong to at least two different classes named 'multi-functional CRM', suggesting their functional importance for regulating spatiotemporal gene expression. From these examples, we show that CCD can be applied to any potential genome-wide datasets and therefore will shed light on unveiling genome-wide CRMs in various species.
Sequential Change-Point Detection via Online Convex Optimization
Directory of Open Access Journals (Sweden)
Yang Cao
2018-02-01
Full Text Available Sequential change-point detection when the distribution parameters are unknown is a fundamental problem in statistics and machine learning. When the post-change parameters are unknown, we consider a set of detection procedures based on sequential likelihood ratios with non-anticipating estimators constructed using online convex optimization algorithms such as online mirror descent, which provides a more versatile approach to tackling complex situations where recursive maximum likelihood estimators cannot be found. When the underlying distributions belong to a exponential family and the estimators satisfy the logarithm regret property, we show that this approach is nearly second-order asymptotically optimal. This means that the upper bound for the false alarm rate of the algorithm (measured by the average-run-length meets the lower bound asymptotically up to a log-log factor when the threshold tends to infinity. Our proof is achieved by making a connection between sequential change-point and online convex optimization and leveraging the logarithmic regret bound property of online mirror descent algorithm. Numerical and real data examples validate our theory.
Directory of Open Access Journals (Sweden)
James Godley
2011-10-01
Full Text Available Entry into the crypt William Burroughs shared with his mother opened and shut around a failed re-enactment of William Tell’s shot through the prop placed upon a loved one’s head. The accidental killing of his wife Joan completed the installation of the addictation machine that spun melancholia as manic dissemination. An early encryptment to which was added the audio portion of abuse deposited an undeliverable message in WB. Wil- liam could never tell, although his corpus bears the in- scription of this impossibility as another form of pos- sibility. James Godley is currently a doctoral candidate in Eng- lish at SUNY Buffalo, where he studies psychoanalysis, Continental philosophy, and nineteenth-century litera- ture and poetry (British and American. His work on the concept of mourning and “the dead” in Freudian and Lacanian approaches to psychoanalytic thought and in Gothic literature has also spawned an essay on zombie porn. Since entering the Academy of Fine Arts Karlsruhe in 2007, Valentin Hennig has studied in the classes of Sil- via Bächli, Claudio Moser, and Corinne Wasmuht. In 2010 he spent a semester at the Dresden Academy of Fine Arts. His work has been shown in group exhibi- tions in Freiburg and Karlsruhe.
Rowe, Robert
2002-05-01
The training of musicians begins by teaching basic musical concepts, a collection of knowledge commonly known as musicianship. Computer programs designed to implement musical skills (e.g., to make sense of what they hear, perform music expressively, or compose convincing pieces) can similarly benefit from access to a fundamental level of musicianship. Recent research in music cognition, artificial intelligence, and music theory has produced a repertoire of techniques that can make the behavior of computer programs more musical. Many of these were presented in a recently published book/CD-ROM entitled Machine Musicianship. For use in interactive music systems, we are interested in those which are fast enough to run in real time and that need only make reference to the material as it appears in sequence. This talk will review several applications that are able to identify the tonal center of musical material during performance. Beyond this specific task, the design of real-time algorithmic listening through the concurrent operation of several connected analyzers is examined. The presentation includes discussion of a library of C++ objects that can be combined to perform interactive listening and a demonstration of their capability.
EEG-based decoding of error-related brain activity in a real-world driving task
Zhang, H.; Chavarriaga, R.; Khaliliardali, Z.; Gheorghe, L.; Iturrate, I.; Millán, J. d. R.
2015-12-01
Objectives. Recent studies have started to explore the implementation of brain-computer interfaces (BCI) as part of driving assistant systems. The current study presents an EEG-based BCI that decodes error-related brain activity. Such information can be used, e.g., to predict driver’s intended turning direction before reaching road intersections. Approach. We executed experiments in a car simulator (N = 22) and a real car (N = 8). While subject was driving, a directional cue was shown before reaching an intersection, and we classified the presence or not of an error-related potentials from EEG to infer whether the cued direction coincided with the subject’s intention. In this protocol, the directional cue can correspond to an estimation of the driving direction provided by a driving assistance system. We analyzed ERPs elicited during normal driving and evaluated the classification performance in both offline and online tests. Results. An average classification accuracy of 0.698 ± 0.065 was obtained in offline experiments in the car simulator, while tests in the real car yielded a performance of 0.682 ± 0.059. The results were significantly higher than chance level for all cases. Online experiments led to equivalent performances in both simulated and real car driving experiments. These results support the feasibility of decoding these signals to help estimating whether the driver’s intention coincides with the advice provided by the driving assistant in a real car. Significance. The study demonstrates a BCI system in real-world driving, extending the work from previous simulated studies. As far as we know, this is the first online study in real car decoding driver’s error-related brain activity. Given the encouraging results, the paradigm could be further improved by using more sophisticated machine learning approaches and possibly be combined with applications in intelligent vehicles.
Real-time fMRI pattern decoding and neurofeedback using FRIEND: an FSL-integrated BCI toolbox.
Sato, João R; Basilio, Rodrigo; Paiva, Fernando F; Garrido, Griselda J; Bramati, Ivanei E; Bado, Patricia; Tovar-Moll, Fernanda; Zahn, Roland; Moll, Jorge
2013-01-01
The demonstration that humans can learn to modulate their own brain activity based on feedback of neurophysiological signals opened up exciting opportunities for fundamental and applied neuroscience. Although EEG-based neurofeedback has been long employed both in experimental and clinical investigation, functional MRI (fMRI)-based neurofeedback emerged as a promising method, given its superior spatial resolution and ability to gauge deep cortical and subcortical brain regions. In combination with improved computational approaches, such as pattern recognition analysis (e.g., Support Vector Machines, SVM), fMRI neurofeedback and brain decoding represent key innovations in the field of neuromodulation and functional plasticity. Expansion in this field and its applications critically depend on the existence of freely available, integrated and user-friendly tools for the neuroimaging research community. Here, we introduce FRIEND, a graphic-oriented user-friendly interface package for fMRI neurofeedback and real-time multivoxel pattern decoding. The package integrates routines for image preprocessing in real-time, ROI-based feedback (single-ROI BOLD level and functional connectivity) and brain decoding-based feedback using SVM. FRIEND delivers an intuitive graphic interface with flexible processing pipelines involving optimized procedures embedding widely validated packages, such as FSL and libSVM. In addition, a user-defined visual neurofeedback module allows users to easily design and run fMRI neurofeedback experiments using ROI-based or multivariate classification approaches. FRIEND is open-source and free for non-commercial use. Processing tutorials and extensive documentation are available.
Real-time fMRI pattern decoding and neurofeedback using FRIEND: an FSL-integrated BCI toolbox.
Directory of Open Access Journals (Sweden)
João R Sato
Full Text Available The demonstration that humans can learn to modulate their own brain activity based on feedback of neurophysiological signals opened up exciting opportunities for fundamental and applied neuroscience. Although EEG-based neurofeedback has been long employed both in experimental and clinical investigation, functional MRI (fMRI-based neurofeedback emerged as a promising method, given its superior spatial resolution and ability to gauge deep cortical and subcortical brain regions. In combination with improved computational approaches, such as pattern recognition analysis (e.g., Support Vector Machines, SVM, fMRI neurofeedback and brain decoding represent key innovations in the field of neuromodulation and functional plasticity. Expansion in this field and its applications critically depend on the existence of freely available, integrated and user-friendly tools for the neuroimaging research community. Here, we introduce FRIEND, a graphic-oriented user-friendly interface package for fMRI neurofeedback and real-time multivoxel pattern decoding. The package integrates routines for image preprocessing in real-time, ROI-based feedback (single-ROI BOLD level and functional connectivity and brain decoding-based feedback using SVM. FRIEND delivers an intuitive graphic interface with flexible processing pipelines involving optimized procedures embedding widely validated packages, such as FSL and libSVM. In addition, a user-defined visual neurofeedback module allows users to easily design and run fMRI neurofeedback experiments using ROI-based or multivariate classification approaches. FRIEND is open-source and free for non-commercial use. Processing tutorials and extensive documentation are available.
Real-Time fMRI Pattern Decoding and Neurofeedback Using FRIEND: An FSL-Integrated BCI Toolbox
Sato, João R.; Basilio, Rodrigo; Paiva, Fernando F.; Garrido, Griselda J.; Bramati, Ivanei E.; Bado, Patricia; Tovar-Moll, Fernanda; Zahn, Roland; Moll, Jorge
2013-01-01
The demonstration that humans can learn to modulate their own brain activity based on feedback of neurophysiological signals opened up exciting opportunities for fundamental and applied neuroscience. Although EEG-based neurofeedback has been long employed both in experimental and clinical investigation, functional MRI (fMRI)-based neurofeedback emerged as a promising method, given its superior spatial resolution and ability to gauge deep cortical and subcortical brain regions. In combination with improved computational approaches, such as pattern recognition analysis (e.g., Support Vector Machines, SVM), fMRI neurofeedback and brain decoding represent key innovations in the field of neuromodulation and functional plasticity. Expansion in this field and its applications critically depend on the existence of freely available, integrated and user-friendly tools for the neuroimaging research community. Here, we introduce FRIEND, a graphic-oriented user-friendly interface package for fMRI neurofeedback and real-time multivoxel pattern decoding. The package integrates routines for image preprocessing in real-time, ROI-based feedback (single-ROI BOLD level and functional connectivity) and brain decoding-based feedback using SVM. FRIEND delivers an intuitive graphic interface with flexible processing pipelines involving optimized procedures embedding widely validated packages, such as FSL and libSVM. In addition, a user-defined visual neurofeedback module allows users to easily design and run fMRI neurofeedback experiments using ROI-based or multivariate classification approaches. FRIEND is open-source and free for non-commercial use. Processing tutorials and extensive documentation are available. PMID:24312569
Comparing and Optimising Parallel Haskell Implementations for Multicore Machines
DEFF Research Database (Denmark)
Berthold, Jost; Marlow, Simon; Hammond, Kevin
2009-01-01
In this paper, we investigate the differences and tradeoffs imposed by two parallel Haskell dialects running on multicore machines. GpH and Eden are both constructed using the highly-optimising sequential GHC compiler, and share thread scheduling, and other elements, from a common code base. The ...
Sheikh, Alireza; Amat, Alexandre Graell i.; Liva, Gianluigi
2017-12-01
We analyze the achievable information rates (AIRs) for coded modulation schemes with QAM constellations with both bit-wise and symbol-wise decoders, corresponding to the case where a binary code is used in combination with a higher-order modulation using the bit-interleaved coded modulation (BICM) paradigm and to the case where a nonbinary code over a field matched to the constellation size is used, respectively. In particular, we consider hard decision decoding, which is the preferable option for fiber-optic communication systems where decoding complexity is a concern. Recently, Liga \\emph{et al.} analyzed the AIRs for bit-wise and symbol-wise decoders considering what the authors called \\emph{hard decision decoder} which, however, exploits \\emph{soft information} of the transition probabilities of discrete-input discrete-output channel resulting from the hard detection. As such, the complexity of the decoder is essentially the same as the complexity of a soft decision decoder. In this paper, we analyze instead the AIRs for the standard hard decision decoder, commonly used in practice, where the decoding is based on the Hamming distance metric. We show that if standard hard decision decoding is used, bit-wise decoders yield significantly higher AIRs than symbol-wise decoders. As a result, contrary to the conclusion by Liga \\emph{et al.}, binary decoders together with the BICM paradigm are preferable for spectrally-efficient fiber-optic systems. We also design binary and nonbinary staircase codes and show that, in agreement with the AIRs, binary codes yield better performance.
STACK DECODING OF LINEAR BLOCK CODES FOR DISCRETE MEMORYLESS CHANNEL USING TREE DIAGRAM
Directory of Open Access Journals (Sweden)
H. Prashantha Kumar
2012-03-01
Full Text Available The boundaries between block and convolutional codes have become diffused after recent advances in the understanding of the trellis structure of block codes and the tail-biting structure of some convolutional codes. Therefore, decoding algorithms traditionally proposed for decoding convolutional codes have been applied for decoding certain classes of block codes. This paper presents the decoding of block codes using tree structure. Many good block codes are presently known. Several of them have been used in applications ranging from deep space communication to error control in storage systems. But the primary difficulty with applying Viterbi or BCJR algorithms to decode of block codes is that, even though they are optimum decoding methods, the promised bit error rates are not achieved in practice at data rates close to capacity. This is because the decoding effort is fixed and grows with block length, and thus only short block length codes can be used. Therefore, an important practical question is whether a suboptimal realizable soft decision decoding method can be found for block codes. A noteworthy result which provides a partial answer to this question is described in the following sections. This result of near optimum decoding will be used as motivation for the investigation of different soft decision decoding methods for linear block codes which can lead to the development of efficient decoding algorithms. The code tree can be treated as an expanded version of the trellis, where every path is totally distinct from every other path. We have derived the tree structure for (8, 4 and (16, 11 extended Hamming codes and have succeeded in implementing the soft decision stack algorithm to decode them. For the discrete memoryless channel, gains in excess of 1.5dB at a bit error rate of 10-5 with respect to conventional hard decision decoding are demonstrated for these codes.
Directory of Open Access Journals (Sweden)
Wodziński Marek
2017-06-01
Full Text Available This paper presents an alternative approach to the sequential data classification, based on traditional machine learning algorithms (neural networks, principal component analysis, multivariate Gaussian anomaly detector and finding the shortest path in a directed acyclic graph, using A* algorithm with a regression-based heuristic. Palm gestures were used as an example of the sequential data and a quadrocopter was the controlled object. The study includes creation of a conceptual model and practical construction of a system using the GPU to ensure the realtime operation. The results present the classification accuracy of chosen gestures and comparison of the computation time between the CPU- and GPU-based solutions.
Peter, Beate
2018-01-01
In a companion study, adults with dyslexia and adults with a probable history of childhood apraxia of speech showed evidence of difficulty with processing sequential information during nonword repetition, multisyllabic real word repetition and nonword decoding. Results suggested that some errors arose in visual encoding during nonword reading, all levels of processing but especially short-term memory storage/retrieval during nonword repetition, and motor planning and programming during complex real word repetition. To further investigate the role of short-term memory, a participant with short-term memory impairment (MI) was recruited. MI was confirmed with poor performance during a sentence repetition and three nonword repetition tasks, all of which have a high short-term memory load, whereas typical performance was observed during tests of reading, spelling, and static verbal knowledge, all with low short-term memory loads. Experimental results show error-free performance during multisyllabic real word repetition but high counts of sequence errors, especially migrations and assimilations, during nonword repetition, supporting short-term memory as a locus of sequential processing deficit during nonword repetition. Results are also consistent with the hypothesis that during complex real word repetition, short-term memory is bypassed as the word is recognized and retrieved from long-term memory prior to producing the word.
Sequential series for nuclear reactions
International Nuclear Information System (INIS)
Izumo, Ko
1975-01-01
A new time-dependent treatment of nuclear reactions is given, in which the wave function of compound nucleus is expanded by a sequential series of the reaction processes. The wave functions of the sequential series form another complete set of compound nucleus at the limit Δt→0. It is pointed out that the wave function is characterized by the quantities: the number of degrees of freedom of motion n, the period of the motion (Poincare cycle) tsub(n), the delay time t sub(nμ) and the relaxation time tausub(n) to the equilibrium of compound nucleus, instead of the usual quantum number lambda, the energy eigenvalue Esub(lambda) and the total width GAMMAsub(lambda) of resonance levels, respectively. The transition matrix elements and the yields of nuclear reactions also become the functions of time given by the Fourier transform of the usual ones. The Poincare cycles of compound nuclei are compared with the observed correlations among resonance levels, which are about 10 -17 --10 -16 sec for medium and heavy nuclei and about 10 -20 sec for the intermediate resonances. (auth.)
Decoding thalamic afferent input using microcircuit spiking activity.
Sederberg, Audrey J; Palmer, Stephanie E; MacLean, Jason N
2015-04-01
A behavioral response appropriate to a sensory stimulus depends on the collective activity of thousands of interconnected neurons. The majority of cortical connections arise from neighboring neurons, and thus understanding the cortical code requires characterizing information representation at the scale of the cortical microcircuit. Using two-photon calcium imaging, we densely sampled the thalamically evoked response of hundreds of neurons spanning multiple layers and columns in thalamocortical slices of mouse somatosensory cortex. We then used a biologically plausible decoder to characterize the representation of two distinct thalamic inputs, at the level of the microcircuit, to reveal those aspects of the activity pattern that are likely relevant to downstream neurons. Our data suggest a sparse code, distributed across lamina, in which a small population of cells carries stimulus-relevant information. Furthermore, we find that, within this subset of neurons, decoder performance improves when noise correlations are taken into account. Copyright © 2015 the American Physiological Society.
Codes on the Klein quartic, ideals, and decoding
DEFF Research Database (Denmark)
Hansen, Johan P.
1987-01-01
descriptions as left ideals in the group-algebra GF(2^{3})[G]. This description allows for easy decoding. For instance, in the case of the single error correcting code of length21and dimension16with minimal distance3. decoding is obtained by multiplication with an idempotent in the group algebra.......A sequence of codes with particular symmetries and with large rates compared to their minimal distances is constructed over the field GF(2^{3}). In the sequence there is, for instance, a code of length 21 and dimension10with minimal distance9, and a code of length21and dimension16with minimal...... distance3. The codes are constructed from algebraic geometry using the dictionary between coding theory and algebraic curves over finite fields established by Goppa. The curve used in the present work is the Klein quartic. This curve has the maximal number of rational points over GF(2^{3})allowed by Serre...
Soft decoding a self-dual (48, 24; 12) code
Solomon, G.
1993-01-01
A self-dual (48,24;12) code comes from restricting a binary cyclic (63,18;36) code to a 6 x 7 matrix, adding an eighth all-zero column, and then adjoining six dimensions to this extended 6 x 8 matrix. These six dimensions are generated by linear combinations of row permutations of a 6 x 8 matrix of weight 12, whose sums of rows and columns add to one. A soft decoding using these properties and approximating maximum likelihood is presented here. This is preliminary to a possible soft decoding of the box (72,36;15) code that promises a 7.7-dB theoretical coding under maximum likelihood.
DECODING OF ACADEMIC CONTENT BY THE 1st GRADE STUDENTS
Directory of Open Access Journals (Sweden)
Kamil Błaszczyński
2017-07-01
Full Text Available In the paper a comparative study conducted on the 1st grade students of sociology and pedagogy is discussed. The study was focused on the language skills of students. The most important skills tested were the abilities to decode academic content. The study shows that the students have very poor language skills in decoding the academic content on every level of its complexity. They also have noticeable problems with the definition of basic academic terms. The significance of the obtained results are high because of the innovative topic and character of the study, which was the first such study conducted on students of a Polish university. Results are also valuable for academic teachers who are interested in such problems as effective communication with students.
Decoding Signal Processing at the Single-Cell Level
Energy Technology Data Exchange (ETDEWEB)
Wiley, H. Steven
2017-12-01
The ability of cells to detect and decode information about their extracellular environment is critical to generating an appropriate response. In multicellular organisms, cells must decode dozens of signals from their neighbors and extracellular matrix to maintain tissue homeostasis while still responding to environmental stressors. How cells detect and process information from their surroundings through a surprisingly limited number of signal transduction pathways is one of the most important question in biology. Despite many decades of research, many of the fundamental principles that underlie cell signal processing remain obscure. However, in this issue of Cell Systems, Gillies et al present compelling evidence that the early response gene circuit can act as a linear signal integrator, thus providing significant insight into how cells handle fluctuating signals and noise in their environment.
Reaction Decoder Tool (RDT): extracting features from chemical reactions.
Rahman, Syed Asad; Torrance, Gilliean; Baldacci, Lorenzo; Martínez Cuesta, Sergio; Fenninger, Franz; Gopal, Nimish; Choudhary, Saket; May, John W; Holliday, Gemma L; Steinbeck, Christoph; Thornton, Janet M
2016-07-01
Extracting chemical features like Atom-Atom Mapping (AAM), Bond Changes (BCs) and Reaction Centres from biochemical reactions helps us understand the chemical composition of enzymatic reactions. Reaction Decoder is a robust command line tool, which performs this task with high accuracy. It supports standard chemical input/output exchange formats i.e. RXN/SMILES, computes AAM, highlights BCs and creates images of the mapped reaction. This aids in the analysis of metabolic pathways and the ability to perform comparative studies of chemical reactions based on these features. This software is implemented in Java, supported on Windows, Linux and Mac OSX, and freely available at https://github.com/asad/ReactionDecoder : asad@ebi.ac.uk or s9asad@gmail.com. © The Author 2016. Published by Oxford University Press.
Fast decoder for local quantum codes using Groebner basis
Haah, Jeongwan
2013-03-01
Based on arXiv:1204.1063. A local translation-invariant quantum code has a description in terms of Laurent polynomials. As an application of this observation, we present a fast decoding algorithm for translation-invariant local quantum codes in any spatial dimensions using the straightforward division algorithm for multivariate polynomials. The running time is O (n log n) on average, or O (n2 log n) on worst cases, where n is the number of physical qubits. The algorithm improves a subroutine of the renormalization-group decoder by Bravyi and Haah (arXiv:1112.3252) in the translation-invariant case. This work is supported in part by the Insitute for Quantum Information and Matter, an NSF Physics Frontier Center, and the Korea Foundation for Advanced Studies.
[Efficacy of decoding training for children with difficulty reading hiragana].
Uchiyama, Hitoshi; Tanaka, Daisuke; Seki, Ayumi; Wakamiya, Eiji; Hirasawa, Noriko; Iketani, Naotake; Kato, Ken; Koeda, Tatsuya
2013-05-01
The present study aimed to clarify the efficacy of decoding training focusing on the correspondence between written symbols and their readings for children with difficulty reading hiragana (Japanese syllabary). Thirty-five children with difficulty reading hiragana were selected from among 367 first-grade elementary school students using a reading aloud test and were then divided into intervention (n=15) and control (n=20) groups. The intervention comprised 5 minutes of decoding training each day for a period of 3 weeks using an original program on a personal computer. Reading time and number of reading errors in the reading aloud test were compared between the groups. The intervention group showed a significant shortening of reading time (F(1,33)=5.40, phiragana.
Iterative demodulation and decoding of coded non-square QAM
Li, L.; Divsalar, D.; Dolinar, S.
2003-01-01
Simulation results show that, with iterative demodulation and decoding, coded NS-8QAM performs 0.5 dB better than standard 8QAM and 0.7 dB better than 8PSK at BER= 10(sup -5), when the FEC code is the (15, 11) Hamming code concatenated with a rate-1 accumulator code, while coded NS-32QAM performs 0.25 dB better than standard 32QAM.
Design and Implementation of Viterbi Decoder Using VHDL
Thakur, Akash; Chattopadhyay, Manju K.
2018-03-01
A digital design conversion of Viterbi decoder for ½ rate convolutional encoder with constraint length k = 3 is presented in this paper. The design is coded with the help of VHDL, simulated and synthesized using XILINX ISE 14.7. Synthesis results show a maximum frequency of operation for the design is 100.725 MHz. The requirement of memory is less as compared to conventional method.
Maximum likelihood convolutional decoding (MCD) performance due to system losses
Webster, L.
1976-01-01
A model for predicting the computational performance of a maximum likelihood convolutional decoder (MCD) operating in a noisy carrier reference environment is described. This model is used to develop a subroutine that will be utilized by the Telemetry Analysis Program to compute the MCD bit error rate. When this computational model is averaged over noisy reference phase errors using a high-rate interpolation scheme, the results are found to agree quite favorably with experimental measurements.
Decoding Gimmicks of Financial Shenanigans in Telecom Sector in India
Sandeep GOEL
2013-01-01
Major corporate financial shenanigans get away in the name of creative accounting. But, they need to be studied for lessons learned and strategies to avoid or reduce the incidence of such frauds in the future. It is essential for shareholders, particularly the common man who does not have any access to the company except reported financial numbers. This paper aims to decode the level of financial shenanigans practices in corporate enterprises in telecom sector in India. The reason being is th...
Fast Transform Decoding Of Nonsystematic Reed-Solomon Codes
Truong, Trieu-Kie; Cheung, Kar-Ming; Shiozaki, A.; Reed, Irving S.
1992-01-01
Fast, efficient Fermat number transform used to compute F'(x) analogous to computation of syndrome in conventional decoding scheme. Eliminates polynomial multiplications and reduces number of multiplications in reconstruction of F'(x) to n log (n). Euclidean algorithm used to evaluate F(x) directly, without going through intermediate steps of solving error-locator and error-evaluator polynomials. Algorithm suitable for implementation in very-large-scale integrated circuits.
Efficient algorithms for maximum likelihood decoding in the surface code
Bravyi, Sergey; Suchara, Martin; Vargo, Alexander
2014-09-01
We describe two implementations of the optimal error correction algorithm known as the maximum likelihood decoder (MLD) for the two-dimensional surface code with a noiseless syndrome extraction. First, we show how to implement MLD exactly in time O (n2), where n is the number of code qubits. Our implementation uses a reduction from MLD to simulation of matchgate quantum circuits. This reduction however requires a special noise model with independent bit-flip and phase-flip errors. Secondly, we show how to implement MLD approximately for more general noise models using matrix product states (MPS). Our implementation has running time O (nχ3), where χ is a parameter that controls the approximation precision. The key step of our algorithm, borrowed from the density matrix renormalization-group method, is a subroutine for contracting a tensor network on the two-dimensional grid. The subroutine uses MPS with a bond dimension χ to approximate the sequence of tensors arising in the course of contraction. We benchmark the MPS-based decoder against the standard minimum weight matching decoder observing a significant reduction of the logical error probability for χ ≥4.
Biological 2-Input Decoder Circuit in Human Cells
2015-01-01
Decoders are combinational circuits that convert information from n inputs to a maximum of 2n outputs. This operation is of major importance in computing systems yet it is vastly underexplored in synthetic biology. Here, we present a synthetic gene network architecture that operates as a biological decoder in human cells, converting 2 inputs to 4 outputs. As a proof-of-principle, we use small molecules to emulate the two inputs and fluorescent reporters as the corresponding four outputs. The experiments are performed using transient transfections in human kidney embryonic cells and the characterization by fluorescence microscopy and flow cytometry. We show a clear separation between the ON and OFF mean fluorescent intensity states. Additionally, we adopt the integrated mean fluorescence intensity for the characterization of the circuit and show that this metric is more robust to transfection conditions when compared to the mean fluorescent intensity. To conclude, we present the first implementation of a genetic decoder. This combinational system can be valuable toward engineering higher-order circuits as well as accommodate a multiplexed interface with endogenous cellular functions. PMID:24694115
An Area-Efficient Reconfigurable LDPC Decoder with Conflict Resolution
Zhou, Changsheng; Huang, Yuebin; Huang, Shuangqu; Chen, Yun; Zeng, Xiaoyang
Based on Turbo-Decoding Message-Passing (TDMP) and Normalized Min-Sum (NMS) algorithm, an area efficient LDPC decoder that supports both structured and unstructured LDPC codes is proposed in this paper. We introduce a solution to solve the memory access conflict problem caused by TDMP algorithm. We also arrange the main timing schedule carefully to handle the operations of our solution while avoiding much additional hardware consumption. To reduce the memory bits needed, the extrinsic message storing strategy is also optimized. Besides the extrinsic message recover and the accumulate operation are merged together. To verify our architecture, a LDPC decoder that supports both China Multimedia Mobile Broadcasting (CMMB) and Digital Terrestrial/ Television Multimedia Broadcasting (DTMB) standards is developed using SMIC 0.13µm standard CMOS process. The core area is 4.75mm2 and the maximum operating clock frequency is 200MHz. The estimated power consumption is 48.4mW at 25MHz for CMMB and 130.9mW at 50MHz for DTMB with 5 iterations and 1.2V supply.
Biological 2-input decoder circuit in human cells.
Guinn, Michael; Bleris, Leonidas
2014-08-15
Decoders are combinational circuits that convert information from n inputs to a maximum of 2(n) outputs. This operation is of major importance in computing systems yet it is vastly underexplored in synthetic biology. Here, we present a synthetic gene network architecture that operates as a biological decoder in human cells, converting 2 inputs to 4 outputs. As a proof-of-principle, we use small molecules to emulate the two inputs and fluorescent reporters as the corresponding four outputs. The experiments are performed using transient transfections in human kidney embryonic cells and the characterization by fluorescence microscopy and flow cytometry. We show a clear separation between the ON and OFF mean fluorescent intensity states. Additionally, we adopt the integrated mean fluorescence intensity for the characterization of the circuit and show that this metric is more robust to transfection conditions when compared to the mean fluorescent intensity. To conclude, we present the first implementation of a genetic decoder. This combinational system can be valuable toward engineering higher-order circuits as well as accommodate a multiplexed interface with endogenous cellular functions.
Exploring the sequential lineup advantage using WITNESS.
Goodsell, Charles A; Gronlund, Scott D; Carlson, Curt A
2010-12-01
Advocates claim that the sequential lineup is an improvement over simultaneous lineup procedures, but no formal (quantitatively specified) explanation exists for why it is better. The computational model WITNESS (Clark, Appl Cogn Psychol 17:629-654, 2003) was used to develop theoretical explanations for the sequential lineup advantage. In its current form, WITNESS produced a sequential advantage only by pairing conservative sequential choosing with liberal simultaneous choosing. However, this combination failed to approximate four extant experiments that exhibited large sequential advantages. Two of these experiments became the focus of our efforts because the data were uncontaminated by likely suspect position effects. Decision-based and memory-based modifications to WITNESS approximated the data and produced a sequential advantage. The next step is to evaluate the proposed explanations and modify public policy recommendations accordingly.
Sequential lineup presentation: Patterns and policy
Lindsay, R C L; Mansour, Jamal K; Beaudry, J L; Leach, A-M; Bertrand, M I
2009-01-01
Sequential lineups were offered as an alternative to the traditional simultaneous lineup. Sequential lineups reduce incorrect lineup selections; however, the accompanying loss of correct identifications has resulted in controversy regarding adoption of the technique. We discuss the procedure and research relevant to (1) the pattern of results found using sequential versus simultaneous lineups; (2) reasons (theory) for differences in witness responses; (3) two methodological issues; and (4) im...
International Nuclear Information System (INIS)
Barbier, M.M.
1981-01-01
An attempt was made to find existing machines that have been upgraded and that could be used for large-scale decontamination operations outdoors. Such machines are in the building industry, the mining industry, and the road construction industry. The road construction industry has yielded the machines in this presentation. A review is given of operations that can be done with the machines available
Dunn, James
This guide, the second in a series of five machine shop curriculum manuals, was designed for use in machine shop courses in Oklahoma. The purpose of the manual is to equip students with basic knowledge and skills that will enable them to enter the machine trade at the machine-operator level. The curriculum is designed so that it can be used in…
Superconducting rotating machines
International Nuclear Information System (INIS)
Smith, J.L. Jr.; Kirtley, J.L. Jr.; Thullen, P.
1975-01-01
The opportunities and limitations of the applications of superconductors in rotating electric machines are given. The relevant properties of superconductors and the fundamental requirements for rotating electric machines are discussed. The current state-of-the-art of superconducting machines is reviewed. Key problems, future developments and the long range potential of superconducting machines are assessed
The basis of orientation decoding in human primary visual cortex: fine- or coarse-scale biases?
Maloney, Ryan T
2015-01-01
Orientation signals in human primary visual cortex (V1) can be reliably decoded from the multivariate pattern of activity as measured with functional magnetic resonance imaging (fMRI). The precise underlying source of these decoded signals (whether by orientation biases at a fine or coarse scale in cortex) remains a matter of some controversy, however. Freeman and colleagues (J Neurosci 33: 19695-19703, 2013) recently showed that the accuracy of decoding of spiral patterns in V1 can be predicted by a voxel's preferred spatial position (the population receptive field) and its coarse orientation preference, suggesting that coarse-scale biases are sufficient for orientation decoding. Whether they are also necessary for decoding remains an open question, and one with implications for the broader interpretation of multivariate decoding results in fMRI studies. Copyright © 2015 the American Physiological Society.
Emotion Decoding and Incidental Processing Fluency as Antecedents of Attitude Certainty.
Petrocelli, John V; Whitmire, Melanie B
2017-07-01
Previous research demonstrates that attitude certainty influences the degree to which an attitude changes in response to persuasive appeals. In the current research, decoding emotions from facial expressions and incidental processing fluency, during attitude formation, are examined as antecedents of both attitude certainty and attitude change. In Experiment 1, participants who decoded anger or happiness during attitude formation expressed their greater attitude certainty, and showed more resistance to persuasion than participants who decoded sadness. By manipulating the emotion decoded, the diagnosticity of processing fluency experienced during emotion decoding, and the gaze direction of the social targets, Experiment 2 suggests that the link between emotion decoding and attitude certainty results from incidental processing fluency. Experiment 3 demonstrated that fluency in processing irrelevant stimuli influences attitude certainty, which in turn influences resistance to persuasion. Implications for appraisal-based accounts of attitude formation and attitude change are discussed.
The Bacterial Sequential Markov Coalescent.
De Maio, Nicola; Wilson, Daniel J
2017-05-01
Bacteria can exchange and acquire new genetic material from other organisms directly and via the environment. This process, known as bacterial recombination, has a strong impact on the evolution of bacteria, for example, leading to the spread of antibiotic resistance across clades and species, and to the avoidance of clonal interference. Recombination hinders phylogenetic and transmission inference because it creates patterns of substitutions (homoplasies) inconsistent with the hypothesis of a single evolutionary tree. Bacterial recombination is typically modeled as statistically akin to gene conversion in eukaryotes, i.e. , using the coalescent with gene conversion (CGC). However, this model can be very computationally demanding as it needs to account for the correlations of evolutionary histories of even distant loci. So, with the increasing popularity of whole genome sequencing, the need has emerged for a faster approach to model and simulate bacterial genome evolution. We present a new model that approximates the coalescent with gene conversion: the bacterial sequential Markov coalescent (BSMC). Our approach is based on a similar idea to the sequential Markov coalescent (SMC)-an approximation of the coalescent with crossover recombination. However, bacterial recombination poses hurdles to a sequential Markov approximation, as it leads to strong correlations and linkage disequilibrium across very distant sites in the genome. Our BSMC overcomes these difficulties, and shows a considerable reduction in computational demand compared to the exact CGC, and very similar patterns in simulated data. We implemented our BSMC model within new simulation software FastSimBac. In addition to the decreased computational demand compared to previous bacterial genome evolution simulators, FastSimBac provides more general options for evolutionary scenarios, allowing population structure with migration, speciation, population size changes, and recombination hotspots. FastSimBac is
Biased lineups: sequential presentation reduces the problem.
Lindsay, R C; Lea, J A; Nosworthy, G J; Fulford, J A; Hector, J; LeVan, V; Seabrook, C
1991-12-01
Biased lineups have been shown to increase significantly false, but not correct, identification rates (Lindsay, Wallbridge, & Drennan, 1987; Lindsay & Wells, 1980; Malpass & Devine, 1981). Lindsay and Wells (1985) found that sequential lineup presentation reduced false identification rates, presumably by reducing reliance on relative judgment processes. Five staged-crime experiments were conducted to examine the effect of lineup biases and sequential presentation on eyewitness recognition accuracy. Sequential lineup presentation significantly reduced false identification rates from fair lineups as well as from lineups biased with regard to foil similarity, instructions, or witness attire, and from lineups biased in all of these ways. The results support recommendations that police present lineups sequentially.
Coding/decoding two-dimensional images with orbital angular momentum of light.
Chu, Jiaqi; Li, Xuefeng; Smithwick, Quinn; Chu, Daping
2016-04-01
We investigate encoding and decoding of two-dimensional information using the orbital angular momentum (OAM) of light. Spiral phase plates and phase-only spatial light modulators are used in encoding and decoding of OAM states, respectively. We show that off-axis points and spatial variables encoded with a given OAM state can be recovered through decoding with the corresponding complimentary OAM state.
A Low-Complexity Joint Detection-Decoding Algorithm for Nonbinary LDPC-Coded Modulation Systems
Wang, Xuepeng; Bai, Baoming; Ma, Xiao
2010-01-01
In this paper, we present a low-complexity joint detection-decoding algorithm for nonbinary LDPC codedmodulation systems. The algorithm combines hard-decision decoding using the message-passing strategy with the signal detector in an iterative manner. It requires low computational complexity, offers good system performance and has a fast rate of decoding convergence. Compared to the q-ary sum-product algorithm (QSPA), it provides an attractive candidate for practical applications of q-ary LDP...
Immediate Sequential Bilateral Cataract Surgery
DEFF Research Database (Denmark)
Kessel, Line; Andresen, Jens; Erngaard, Ditte
2015-01-01
The aim of the present systematic review was to examine the benefits and harms associated with immediate sequential bilateral cataract surgery (ISBCS) with specific emphasis on the rate of complications, postoperative anisometropia, and subjective visual function in order to formulate evidence......-based national Danish guidelines for cataract surgery. A systematic literature review in PubMed, Embase, and Cochrane central databases identified three randomized controlled trials that compared outcome in patients randomized to ISBCS or bilateral cataract surgery on two different dates. Meta-analyses were...... performed using the Cochrane Review Manager software. The quality of the evidence was assessed using the GRADE method (Grading of Recommendation, Assessment, Development, and Evaluation). We did not find any difference in the risk of complications or visual outcome in patients randomized to ISBCS or surgery...
Random and cooperative sequential adsorption
Evans, J. W.
1993-10-01
Irreversible random sequential adsorption (RSA) on lattices, and continuum "car parking" analogues, have long received attention as models for reactions on polymer chains, chemisorption on single-crystal surfaces, adsorption in colloidal systems, and solid state transformations. Cooperative generalizations of these models (CSA) are sometimes more appropriate, and can exhibit richer kinetics and spatial structure, e.g., autocatalysis and clustering. The distribution of filled or transformed sites in RSA and CSA is not described by an equilibrium Gibbs measure. This is the case even for the saturation "jammed" state of models where the lattice or space cannot fill completely. However exact analysis is often possible in one dimension, and a variety of powerful analytic methods have been developed for higher dimensional models. Here we review the detailed understanding of asymptotic kinetics, spatial correlations, percolative structure, etc., which is emerging for these far-from-equilibrium processes.
Decoding using back-project algorithm from coded image in ICF
International Nuclear Information System (INIS)
Jiang shaoen; Liu Zhongli; Zheng Zhijian; Tang Daoyuan
1999-01-01
The principle of the coded imaging and its decoding in inertial confinement fusion is described simply. The authors take ring aperture microscope for example and use back-project (BP) algorithm to decode the coded image. The decoding program has been performed for numerical simulation. Simulations of two models are made, and the results show that the accuracy of BP algorithm is high and effect of reconstruction is good. Thus, it indicates that BP algorithm is applicable to decoding for coded image in ICF experiments
Analysis of Iterated Hard Decision Decoding of Product Codes with Reed-Solomon Component Codes
DEFF Research Database (Denmark)
Justesen, Jørn; Høholdt, Tom
2007-01-01
Products of Reed-Solomon codes are important in applications because they offer a combination of large blocks, low decoding complexity, and good performance. A recent result on random graphs can be used to show that with high probability a large number of errors can be corrected by iterating...... minimum distance decoding. We present an analysis related to density evolution which gives the exact asymptotic value of the decoding threshold and also provides a closed form approximation to the distribution of errors in each step of the decoding of finite length codes....
VLSI Architectures for Sliding-Window-Based Space-Time Turbo Trellis Code Decoders
Directory of Open Access Journals (Sweden)
Georgios Passas
2012-01-01
Full Text Available The VLSI implementation of SISO-MAP decoders used for traditional iterative turbo coding has been investigated in the literature. In this paper, a complete architectural model of a space-time turbo code receiver that includes elementary decoders is presented. These architectures are based on newly proposed building blocks such as a recursive add-compare-select-offset (ACSO unit, A-, B-, Γ-, and LLR output calculation modules. Measurements of complexity and decoding delay of several sliding-window-technique-based MAP decoder architectures and a proposed parameter set lead to defining equations and comparison between those architectures.
A new LDPC decoding scheme for PDM-8QAM BICM coherent optical communication system
Liu, Yi; Zhang, Wen-bo; Xi, Li-xia; Tang, Xian-feng; Zhang, Xiao-guang
2015-11-01
A new log-likelihood ratio (LLR) message estimation method is proposed for polarization-division multiplexing eight quadrature amplitude modulation (PDM-8QAM) bit-interleaved coded modulation (BICM) optical communication system. The formulation of the posterior probability is theoretically analyzed, and the way to reduce the pre-decoding bit error rate ( BER) of the low density parity check (LDPC) decoder for PDM-8QAM constellations is presented. Simulation results show that it outperforms the traditional scheme, i.e., the new post-decoding BER is decreased down to 50% of that of the traditional post-decoding algorithm.
Multiple-Symbol Noncoherent Decoding of Uncoded and Convolutionally Codes Continous Phase Modulation
Divsalar, D.; Raphaeli, D.
2000-01-01
Recently, a method for combined noncoherent detection and decoding of trellis-codes (noncoherent coded modulation) has been proposed, which can practically approach the performance of coherent detection.
Firing rate estimation using infinite mixture models and its application to neural decoding.
Shibue, Ryohei; Komaki, Fumiyasu
2017-11-01
Neural decoding is a framework for reconstructing external stimuli from spike trains recorded by various neural recordings. Kloosterman et al. proposed a new decoding method using marked point processes (Kloosterman F, Layton SP, Chen Z, Wilson MA. J Neurophysiol 111: 217-227, 2014). This method does not require spike sorting and thereby improves decoding accuracy dramatically. In this method, they used kernel density estimation to estimate intensity functions of marked point processes. However, the use of kernel density estimation causes problems such as low decoding accuracy and high computational costs. To overcome these problems, we propose a new decoding method using infinite mixture models to estimate intensity. The proposed method improves decoding performance in terms of accuracy and computational speed. We apply the proposed method to simulation and experimental data to verify its performance. NEW & NOTEWORTHY We propose a new neural decoding method using infinite mixture models and nonparametric Bayesian statistics. The proposed method improves decoding performance in terms of accuracy and computation speed. We have successfully applied the proposed method to position decoding from spike trains recorded in a rat hippocampus. Copyright © 2017 the American Physiological Society.
Parallel iterative decoding of transform domain Wyner-Ziv video using cross bitplane correlation
DEFF Research Database (Denmark)
Luong, Huynh Van; Huang, Xin; Forchhammer, Søren
2011-01-01
decoding scheme is proposed to improve the coding efficiency of TDWZ video codecs. The proposed parallel iterative LDPC decoding scheme is able to utilize cross bitplane correlation during decoding, by iteratively refining the soft-input, updating a modeled noise distribution and thereafter enhancing......In recent years, Transform Domain Wyner-Ziv (TDWZ) video coding has been proposed as an efficient Distributed Video Coding (DVC) solution, which fully or partly exploits the source statistics at the decoder to reduce the computational burden at the encoder. In this paper, a parallel iterative LDPC...
Directory of Open Access Journals (Sweden)
Frank Bremmer
2016-08-01
Full Text Available Primates perform saccadic eye movements in order to bring the image of an interesting target onto the fovea. Compared to stationary targets, saccades towards moving targets are computationally more demanding since the oculomotor system must use speed and direction information about the target as well as knowledge about its own processing latency to program an adequate, predictive saccade vector. In monkeys, different brain regions have been implicated in the control of voluntary saccades, among them the lateral intraparietal area (LIP. Here we asked, if activity in area LIP reflects the distance between fovea and saccade target, or the amplitude of an upcoming saccade, or both. We recorded single unit activity in area LIP of two macaque monkeys. First, we determined for each neuron its preferred saccade direction. Then, monkeys performed visually guided saccades along the preferred direction towards either stationary or moving targets in pseudo-randomized order. LIP population activity allowed to decode both, the distance between fovea and saccade target as well as the size of an upcoming saccade. Previous work has shown comparable results for saccade direction (Graf and Andersen, 2014a, b. Hence, LIP population activity allows to predict any two-dimensional saccade vector. Functional equivalents of macaque area LIP have been identified in humans. Accordingly, our results provide further support for the concept of activity from area LIP as neural basis for the control of an oculomotor brain-machine interface.
Bremmer, Frank; Kaminiarz, Andre; Klingenhoefer, Steffen; Churan, Jan
2016-01-01
Primates perform saccadic eye movements in order to bring the image of an interesting target onto the fovea. Compared to stationary targets, saccades toward moving targets are computationally more demanding since the oculomotor system must use speed and direction information about the target as well as knowledge about its own processing latency to program an adequate, predictive saccade vector. In monkeys, different brain regions have been implicated in the control of voluntary saccades, among them the lateral intraparietal area (LIP). Here we asked, if activity in area LIP reflects the distance between fovea and saccade target, or the amplitude of an upcoming saccade, or both. We recorded single unit activity in area LIP of two macaque monkeys. First, we determined for each neuron its preferred saccade direction. Then, monkeys performed visually guided saccades along the preferred direction toward either stationary or moving targets in pseudo-randomized order. LIP population activity allowed to decode both, the distance between fovea and saccade target as well as the size of an upcoming saccade. Previous work has shown comparable results for saccade direction (Graf and Andersen, 2014a,b). Hence, LIP population activity allows to predict any two-dimensional saccade vector. Functional equivalents of macaque area LIP have been identified in humans. Accordingly, our results provide further support for the concept of activity from area LIP as neural basis for the control of an oculomotor brain-machine interface. PMID:27630547
A Symbiotic Brain-Machine Interface through Value-Based Decision Making
Mahmoudi, Babak; Sanchez, Justin C.
2011-01-01
Background In the development of Brain Machine Interfaces (BMIs), there is a great need to enable users to interact with changing environments during the activities of daily life. It is expected that the number and scope of the learning tasks encountered during interaction with the environment as well as the pattern of brain activity will vary over time. These conditions, in addition to neural reorganization, pose a challenge to decoding neural commands for BMIs. We have developed a new BMI framework in which a computational agent symbiotically decoded users' intended actions by utilizing both motor commands and goal information directly from the brain through a continuous Perception-Action-Reward Cycle (PARC). Methodology The control architecture designed was based on Actor-Critic learning, which is a PARC-based reinforcement learning method. Our neurophysiology studies in rat models suggested that Nucleus Accumbens (NAcc) contained a rich representation of goal information in terms of predicting the probability of earning reward and it could be translated into an evaluative feedback for adaptation of the decoder with high precision. Simulated neural control experiments showed that the system was able to maintain high performance in decoding neural motor commands during novel tasks or in the presence of reorganization in the neural input. We then implanted a dual micro-wire array in the primary motor cortex (M1) and the NAcc of rat brain and implemented a full closed-loop system in which robot actions were decoded from the single unit activity in M1 based on an evaluative feedback that was estimated from NAcc. Conclusions Our results suggest that adapting the BMI decoder with an evaluative feedback that is directly extracted from the brain is a possible solution to the problem of operating BMIs in changing environments with dynamic neural signals. During closed-loop control, the agent was able to solve a reaching task by capturing the action and reward
A symbiotic brain-machine interface through value-based decision making.
Directory of Open Access Journals (Sweden)
Babak Mahmoudi
Full Text Available BACKGROUND: In the development of Brain Machine Interfaces (BMIs, there is a great need to enable users to interact with changing environments during the activities of daily life. It is expected that the number and scope of the learning tasks encountered during interaction with the environment as well as the pattern of brain activity will vary over time. These conditions, in addition to neural reorganization, pose a challenge to decoding neural commands for BMIs. We have developed a new BMI framework in which a computational agent symbiotically decoded users' intended actions by utilizing both motor commands and goal information directly from the brain through a continuous Perception-Action-Reward Cycle (PARC. METHODOLOGY: The control architecture designed was based on Actor-Critic learning, which is a PARC-based reinforcement learning method. Our neurophysiology studies in rat models suggested that Nucleus Accumbens (NAcc contained a rich representation of goal information in terms of predicting the probability of earning reward and it could be translated into an evaluative feedback for adaptation of the decoder with high precision. Simulated neural control experiments showed that the system was able to maintain high performance in decoding neural motor commands during novel tasks or in the presence of reorganization in the neural input. We then implanted a dual micro-wire array in the primary motor cortex (M1 and the NAcc of rat brain and implemented a full closed-loop system in which robot actions were decoded from the single unit activity in M1 based on an evaluative feedback that was estimated from NAcc. CONCLUSIONS: Our results suggest that adapting the BMI decoder with an evaluative feedback that is directly extracted from the brain is a possible solution to the problem of operating BMIs in changing environments with dynamic neural signals. During closed-loop control, the agent was able to solve a reaching task by capturing the action and
Saproo, Sameer; Shih, Victor; Jangraw, David C.; Sajda, Paul
2016-12-01
Objective. We investigated the neural correlates of workload buildup in a fine visuomotor task called the boundary avoidance task (BAT). The BAT has been known to induce naturally occurring failures of human-machine coupling in high performance aircraft that can potentially lead to a crash—these failures are termed pilot induced oscillations (PIOs). Approach. We recorded EEG and pupillometry data from human subjects engaged in a flight BAT simulated within a virtual 3D environment. Main results. We find that workload buildup in a BAT can be successfully decoded from oscillatory features in the electroencephalogram (EEG). Information in delta, theta, alpha, beta, and gamma spectral bands of the EEG all contribute to successful decoding, however gamma band activity with a lateralized somatosensory topography has the highest contribution, while theta band activity with a fronto-central topography has the most robust contribution in terms of real-world usability. We show that the output of the spectral decoder can be used to predict PIO susceptibility. We also find that workload buildup in the task induces pupil dilation, the magnitude of which is significantly correlated with the magnitude of the decoded EEG signals. These results suggest that PIOs may result from the dysregulation of cortical networks such as the locus coeruleus (LC)—anterior cingulate cortex (ACC) circuit. Significance. Our findings may generalize to similar control failures in other cases of tight man-machine coupling where gains and latencies in the control system must be inferred and compensated for by the human operators. A closed-loop intervention using neurophysiological decoding of workload buildup that targets the LC-ACC circuit may positively impact operator performance in such situations.
Stereodivergent synthesis with a programmable molecular machine
Kassem, Salma; Lee, Alan T. L.; Leigh, David A.; Marcos, Vanesa; Palmer, Leoni I.; Pisano, Simone
2017-09-01
It has been convincingly argued that molecular machines that manipulate individual atoms, or highly reactive clusters of atoms, with Ångström precision are unlikely to be realized. However, biological molecular machines routinely position rather less reactive substrates in order to direct chemical reaction sequences, from sequence-specific synthesis by the ribosome to polyketide synthases, where tethered molecules are passed from active site to active site in multi-enzyme complexes. Artificial molecular machines have been developed for tasks that include sequence-specific oligomer synthesis and the switching of product chirality, a photo-responsive host molecule has been described that is able to mechanically twist a bound molecular guest, and molecular fragments have been selectively transported in either direction between sites on a molecular platform through a ratchet mechanism. Here we detail an artificial molecular machine that moves a substrate between different activating sites to achieve different product outcomes from chemical synthesis. This molecular robot can be programmed to stereoselectively produce, in a sequential one-pot operation, an excess of any one of four possible diastereoisomers from the addition of a thiol and an alkene to an α,β-unsaturated aldehyde in a tandem reaction process. The stereodivergent synthesis includes diastereoisomers that cannot be selectively synthesized through conventional iminium-enamine organocatalysis. We anticipate that future generations of programmable molecular machines may have significant roles in chemical synthesis and molecular manufacturing.
Trial Sequential Methods for Meta-Analysis
Kulinskaya, Elena; Wood, John
2014-01-01
Statistical methods for sequential meta-analysis have applications also for the design of new trials. Existing methods are based on group sequential methods developed for single trials and start with the calculation of a required information size. This works satisfactorily within the framework of fixed effects meta-analysis, but conceptual…
Sequential lineup laps and eyewitness accuracy.
Steblay, Nancy K; Dietrich, Hannah L; Ryan, Shannon L; Raczynski, Jeanette L; James, Kali A
2011-08-01
Police practice of double-blind sequential lineups prompts a question about the efficacy of repeated viewings (laps) of the sequential lineup. Two laboratory experiments confirmed the presence of a sequential lap effect: an increase in witness lineup picks from first to second lap, when the culprit was a stranger. The second lap produced more errors than correct identifications. In Experiment 2, lineup diagnosticity was significantly higher for sequential lineup procedures that employed a single versus double laps. Witnesses who elected to view a second lap made significantly more errors than witnesses who chose to stop after one lap or those who were required to view two laps. Witnesses with prior exposure to the culprit did not exhibit a sequential lap effect.
Multi-agent sequential hypothesis testing
Kim, Kwang-Ki K.
2014-12-15
This paper considers multi-agent sequential hypothesis testing and presents a framework for strategic learning in sequential games with explicit consideration of both temporal and spatial coordination. The associated Bayes risk functions explicitly incorporate costs of taking private/public measurements, costs of time-difference and disagreement in actions of agents, and costs of false declaration/choices in the sequential hypothesis testing. The corresponding sequential decision processes have well-defined value functions with respect to (a) the belief states for the case of conditional independent private noisy measurements that are also assumed to be independent identically distributed over time, and (b) the information states for the case of correlated private noisy measurements. A sequential investment game of strategic coordination and delay is also discussed as an application of the proposed strategic learning rules.
Sequential Product of Quantum Effects: An Overview
Gudder, Stan
2010-12-01
This article presents an overview for the theory of sequential products of quantum effects. We first summarize some of the highlights of this relatively recent field of investigation and then provide some new results. We begin by discussing sequential effect algebras which are effect algebras endowed with a sequential product satisfying certain basic conditions. We then consider sequential products of (discrete) quantum measurements. We next treat transition effect matrices (TEMs) and their associated sequential product. A TEM is a matrix whose entries are effects and whose rows form quantum measurements. We show that TEMs can be employed for the study of quantum Markov chains. Finally, we prove some new results concerning TEMs and vector densities.
Koenigsberger, F
1970-01-01
Machine Tool Structures, Volume 1 deals with fundamental theories and calculation methods for machine tool structures. Experimental investigations into stiffness are discussed, along with the application of the results to the design of machine tool structures. Topics covered range from static and dynamic stiffness to chatter in metal cutting, stability in machine tools, and deformations of machine tool structures. This volume is divided into three sections and opens with a discussion on stiffness specifications and the effect of stiffness on the behavior of the machine under forced vibration c
Machine Learning for Neuroimaging with Scikit-Learn
Directory of Open Access Journals (Sweden)
Alexandre eAbraham
2014-02-01
Full Text Available Statistical machine learning methods are increasingly used for neuroimaging data analysis. Their main virtue is their ability to model high-dimensional datasets, e.g. multivariate analysis of activation images or resting-state time series. Supervised learning is typically used in decoding or encoding settings to relate brain images to behavioral or clinical observations, while unsupervised learning can uncover hidden structures in sets of images (e.g. resting state functional MRI or find sub-populations in large cohorts. By considering different functional neuroimaging applications, we illustrate how scikit-learn, a Python machine learning library, can be used to perform some key analysis steps. Scikit-learn contains a very large set of statistical learning algorithms, both supervised and unsupervised, and its application to neuroimaging data provides a versatile tool to study the brain.
Machine learning for neuroimaging with scikit-learn.
Abraham, Alexandre; Pedregosa, Fabian; Eickenberg, Michael; Gervais, Philippe; Mueller, Andreas; Kossaifi, Jean; Gramfort, Alexandre; Thirion, Bertrand; Varoquaux, Gaël
2014-01-01
Statistical machine learning methods are increasingly used for neuroimaging data analysis. Their main virtue is their ability to model high-dimensional datasets, e.g., multivariate analysis of activation images or resting-state time series. Supervised learning is typically used in decoding or encoding settings to relate brain images to behavioral or clinical observations, while unsupervised learning can uncover hidden structures in sets of images (e.g., resting state functional MRI) or find sub-populations in large cohorts. By considering different functional neuroimaging applications, we illustrate how scikit-learn, a Python machine learning library, can be used to perform some key analysis steps. Scikit-learn contains a very large set of statistical learning algorithms, both supervised and unsupervised, and its application to neuroimaging data provides a versatile tool to study the brain.
Matos, João T V; Duarte, Regina M B O; Lopes, Sónia P; Silva, Artur M S; Duarte, Armando C
2017-12-01
Organic Aerosols (OAs) are typically defined as highly complex matrices whose composition changes in time and space. Focusing on time vector, this work uses two-dimensional nuclear magnetic resonance (2D NMR) techniques to examine the structural features of water-soluble (WSOM) and alkaline-soluble organic matter (ASOM) sequentially extracted from fine atmospheric aerosols collected in an urban setting during cold and warm seasons. This study reveals molecular signatures not previously decoded in NMR-related studies of OAs as meaningful source markers. Although the ASOM is less hydrophilic and structurally diverse than its WSOM counterpart, both fractions feature a core with heteroatom-rich branched aliphatics from both primary (natural and anthropogenic) and secondary origin, aromatic secondary organics originated from anthropogenic aromatic precursors, as well as primary saccharides and amino sugar derivatives from biogenic emissions. These common structures represent those 2D NMR spectral signatures that are present in both seasons and can thus be seen as an "annual background" profile of the structural composition of OAs at the urban location. Lignin-derived structures, nitroaromatics, disaccharides, and anhydrosaccharides signatures were also identified in the WSOM samples only from periods identified as smoke impacted, which reflects the influence of biomass-burning sources. The NMR dataset on the H-C molecules backbone was also used to propose a semi-quantitative structural model of urban WSOM, which will aid efforts for more realistic studies relating the chemical properties of OAs with their atmospheric behavior. Copyright © 2017 Elsevier Ltd. All rights reserved.
Multilevel sequential Monte Carlo samplers
Beskos, Alexandros; Jasra, Ajay; Law, Kody; Tempone, Raul; Zhou, Yan
2016-01-01
In this article we consider the approximation of expectations w.r.t. probability distributions associated to the solution of partial differential equations (PDEs); this scenario appears routinely in Bayesian inverse problems. In practice, one often has to solve the associated PDE numerically, using, for instance finite element methods which depend on the step-size level . hL. In addition, the expectation cannot be computed analytically and one often resorts to Monte Carlo methods. In the context of this problem, it is known that the introduction of the multilevel Monte Carlo (MLMC) method can reduce the amount of computational effort to estimate expectations, for a given level of error. This is achieved via a telescoping identity associated to a Monte Carlo approximation of a sequence of probability distributions with discretization levels . âˆž>h0>h1â‹¯>hL. In many practical problems of interest, one cannot achieve an i.i.d. sampling of the associated sequence and a sequential Monte Carlo (SMC) version of the MLMC method is introduced to deal with this problem. It is shown that under appropriate assumptions, the attractive property of a reduction of the amount of computational effort to estimate expectations, for a given level of error, can be maintained within the SMC context. That is, relative to exact sampling and Monte Carlo for the distribution at the finest level . hL. The approach is numerically illustrated on a Bayesian inverse problem. Â© 2016 Elsevier B.V.
Multilevel sequential Monte Carlo samplers
Beskos, Alexandros
2016-08-29
In this article we consider the approximation of expectations w.r.t. probability distributions associated to the solution of partial differential equations (PDEs); this scenario appears routinely in Bayesian inverse problems. In practice, one often has to solve the associated PDE numerically, using, for instance finite element methods which depend on the step-size level . hL. In addition, the expectation cannot be computed analytically and one often resorts to Monte Carlo methods. In the context of this problem, it is known that the introduction of the multilevel Monte Carlo (MLMC) method can reduce the amount of computational effort to estimate expectations, for a given level of error. This is achieved via a telescoping identity associated to a Monte Carlo approximation of a sequence of probability distributions with discretization levels . âˆž>h0>h1â‹¯>hL. In many practical problems of interest, one cannot achieve an i.i.d. sampling of the associated sequence and a sequential Monte Carlo (SMC) version of the MLMC method is introduced to deal with this problem. It is shown that under appropriate assumptions, the attractive property of a reduction of the amount of computational effort to estimate expectations, for a given level of error, can be maintained within the SMC context. That is, relative to exact sampling and Monte Carlo for the distribution at the finest level . hL. The approach is numerically illustrated on a Bayesian inverse problem. Â© 2016 Elsevier B.V.
Sequential Scintigraphy in Renal Transplantation
Energy Technology Data Exchange (ETDEWEB)
Winkel, K. zum; Harbst, H.; Schenck, P.; Franz, H. E.; Ritz, E.; Roehl, L.; Ziegler, M.; Ammann, W.; Maier-Borst, W. [Institut Fuer Nuklearmedizin, Deutsches Krebsforschungszentrum, Heidelberg, Federal Republic of Germany (Germany)
1969-05-15
Based on experience gained from more than 1600 patients with proved or suspected kidney diseases and on results on extended studies with dogs, sequential scintigraphy was performed after renal transplantation in dogs. After intravenous injection of 500 {mu}Ci. {sup 131}I-Hippuran scintiphotos were taken during the first minute with an exposure time of 15 sec each and thereafter with an exposure of 2 min up to at least 16 min.. Several examinations were evaluated digitally. 26 examinations were performed on 11 dogs with homotransplanted kidneys. Immediately after transplantation the renal function was almost normal arid the bladder was filled in due time. At the beginning of rejection the initial uptake of radioactive Hippuran was reduced. The intrarenal transport became delayed; probably the renal extraction rate decreased. Corresponding to the development of an oedema in the transplant the uptake area increased in size. In cases of thrombosis of the main artery there was no evidence of any uptake of radioactivity in the transplant. Similar results were obtained in 41 examinations on 15 persons. Patients with postoperative anuria due to acute tubular necrosis showed still some uptake of radioactivity contrary to those with thrombosis of the renal artery, where no uptake was found. In cases of rejection the most frequent signs were a reduced initial uptake and a delayed intrarenal transport of radioactive Hippuran. Infarction could be detected by a reduced uptake in distinct areas of the transplant. (author)
Sequential provisional implant prosthodontics therapy.
Zinner, Ira D; Markovits, Stanley; Jansen, Curtis E; Reid, Patrick E; Schnader, Yale E; Shapiro, Herbert J
2012-01-01
The fabrication and long-term use of first- and second-stage provisional implant prostheses is critical to create a favorable prognosis for function and esthetics of a fixed-implant supported prosthesis. The fixed metal and acrylic resin cemented first-stage prosthesis, as reviewed in Part I, is needed for prevention of adjacent and opposing tooth movement, pressure on the implant site as well as protection to avoid micromovement of the freshly placed implant body. The second-stage prosthesis, reviewed in Part II, should be used following implant uncovering and abutment installation. The patient wears this provisional prosthesis until maturation of the bone and healing of soft tissues. The second-stage provisional prosthesis is also a fail-safe mechanism for possible early implant failures and also can be used with late failures and/or for the necessity to repair the definitive prosthesis. In addition, the screw-retained provisional prosthesis is used if and when an implant requires removal or other implants are to be placed as in a sequential approach. The creation and use of both first- and second-stage provisional prostheses involve a restorative dentist, dental technician, surgeon, and patient to work as a team. If the dentist alone cannot do diagnosis and treatment planning, surgery, and laboratory techniques, he or she needs help by employing the expertise of a surgeon and a laboratory technician. This team approach is essential for optimum results.
Astrand, Elaine
2018-06-01
Objective. Working memory (WM), crucial for successful behavioral performance in most of our everyday activities, holds a central role in goal-directed behavior. As task demands increase, inducing higher WM load, maintaining successful behavioral performance requires the brain to work at the higher end of its capacity. Because it is depending on both external and internal factors, individual WM load likely varies in a continuous fashion. The feasibility to extract such a continuous measure in time that correlates to behavioral performance during a working memory task remains unsolved. Approach. Multivariate pattern decoding was used to test whether a decoder constructed from two discrete levels of WM load can generalize to produce a continuous measure that predicts task performance. Specifically, a linear regression with L2-regularization was chosen with input features from EEG oscillatory activity recorded from healthy participants while performing the n-back task, n\\in [1,2] . Main results. The feasibility to extract a continuous time-resolved measure that correlates positively to trial-by-trial working memory task performance is demonstrated (r = 0.47, p < 0.05). It is furthermore shown that this measure allows to predict task performance before action (r = 0.49, p < 0.05). We show that the extracted continuous measure enables to study the temporal dynamics of the complex activation pattern of WM encoding during the n-back task. Specifically, temporally precise contributions of different spectral features are observed which extends previous findings of traditional univariate approaches. Significance. These results constitute an important contribution towards a wide range of applications in the field of cognitive brain–machine interfaces. Monitoring mental processes related to attention and WM load to reduce the risk of committing errors in high-risk environments could potentially prevent many devastating consequences or
Research on coding and decoding method for digital levels
Energy Technology Data Exchange (ETDEWEB)
Tu Lifen; Zhong Sidong
2011-01-20
A new coding and decoding method for digital levels is proposed. It is based on an area-array CCD sensor and adopts mixed coding technology. By taking advantage of redundant information in a digital image signal, the contradiction that the field of view and image resolution restrict each other in a digital level measurement is overcome, and the geodetic leveling becomes easier. The experimental results demonstrate that the uncertainty of measurement is 1mm when the measuring range is between 2m and 100m, which can meet practical needs.
Research on coding and decoding method for digital levels.
Tu, Li-fen; Zhong, Si-dong
2011-01-20
A new coding and decoding method for digital levels is proposed. It is based on an area-array CCD sensor and adopts mixed coding technology. By taking advantage of redundant information in a digital image signal, the contradiction that the field of view and image resolution restrict each other in a digital level measurement is overcome, and the geodetic leveling becomes easier. The experimental results demonstrate that the uncertainty of measurement is 1 mm when the measuring range is between 2 m and 100 m, which can meet practical needs.
Central Decoding for Multiple Description Codes based on Domain Partitioning
Directory of Open Access Journals (Sweden)
M. Spiertz
2006-01-01
Full Text Available Multiple Description Codes (MDC can be used to trade redundancy against packet loss resistance for transmitting data over lossy diversity networks. In this work we focus on MD transform coding based on domain partitioning. Compared to Vaishampayan’s quantizer based MDC, domain based MD coding is a simple approach for generating different descriptions, by using different quantizers for each description. Commonly, only the highest rate quantizer is used for reconstruction. In this paper we investigate the benefit of using the lower rate quantizers to enhance the reconstruction quality at decoder side. The comparison is done on artificial source data and on image data.
An LDPC decoder architecture for wireless sensor network applications.
Biroli, Andrea Dario Giancarlo; Martina, Maurizio; Masera, Guido
2012-01-01
The pervasive use of wireless sensors in a growing spectrum of human activities reinforces the need for devices with low energy dissipation. In this work, coded communication between a couple of wireless sensor devices is considered as a method to reduce the dissipated energy per transmitted bit with respect to uncoded communication. Different Low Density Parity Check (LDPC) codes are considered to this purpose and post layout results are shown for a low-area low-energy decoder, which offers percentage energy savings with respect to the uncoded solution in the range of 40%-80%, depending on considered environment, distance and bit error rate.
Optimized iterative decoding method for TPC coded CPM
Ma, Yanmin; Lai, Penghui; Wang, Shilian; Xie, Shunqin; Zhang, Wei
2018-05-01
Turbo Product Code (TPC) coded Continuous Phase Modulation (CPM) system (TPC-CPM) has been widely used in aeronautical telemetry and satellite communication. This paper mainly investigates the improvement and optimization on the TPC-CPM system. We first add the interleaver and deinterleaver to the TPC-CPM system, and then establish an iterative system to iteratively decode. However, the improved system has a poor convergence ability. To overcome this issue, we use the Extrinsic Information Transfer (EXIT) analysis to find the optimal factors for the system. The experiments show our method is efficient to improve the convergence performance.
Synthesizer for decoding a coded short wave length irradiation
International Nuclear Information System (INIS)
1976-01-01
The system uses point irradiation source, typically an X-ray emitter, which illuminates a three dimensional object consisting of a set of parallel planes, each of which acts as a source of coded information. The secondary source images are superimposed on a common flat screen. The decoding system comprises an imput light-screen detector, a picture screen amplifier, a beam deflector, on output picture screen, an optical focussing unit including three lenses, a masking unit, an output light screen detector and a video signal reproduction unit of cathode ray tube from, or similar, to create a three dimensional image of the object. (G.C.)
New decoding methods of interleaved burst error-correcting codes
Nakano, Y.; Kasahara, M.; Namekawa, T.
1983-04-01
A probabilistic method of single burst error correction, using the syndrome correlation of subcodes which constitute the interleaved code, is presented. This method makes it possible to realize a high capability of burst error correction with less decoding delay. By generalizing this method it is possible to obtain probabilistic method of multiple (m-fold) burst error correction. After estimating the burst error positions using syndrome correlation of subcodes which are interleaved m-fold burst error detecting codes, this second method corrects erasure errors in each subcode and m-fold burst errors. The performance of these two methods is analyzed via computer simulation, and their effectiveness is demonstrated.
An LDPC Decoder Architecture for Wireless Sensor Network Applications
Giancarlo Biroli, Andrea Dario; Martina, Maurizio; Masera, Guido
2012-01-01
The pervasive use of wireless sensors in a growing spectrum of human activities reinforces the need for devices with low energy dissipation. In this work, coded communication between a couple of wireless sensor devices is considered as a method to reduce the dissipated energy per transmitted bit with respect to uncoded communication. Different Low Density Parity Check (LDPC) codes are considered to this purpose and post layout results are shown for a low-area low-energy decoder, which offers percentage energy savings with respect to the uncoded solution in the range of 40%–80%, depending on considered environment, distance and bit error rate. PMID:22438724
Video semaphore decoding for free-space optical communication
Last, Matthew; Fisher, Brian; Ezekwe, Chinwuba; Hubert, Sean M.; Patel, Sheetal; Hollar, Seth; Leibowitz, Brian S.; Pister, Kristofer S. J.
2001-04-01
Using teal-time image processing we have demonstrated a low bit-rate free-space optical communication system at a range of more than 20km with an average optical transmission power of less than 2mW. The transmitter is an autonomous one cubic inch microprocessor-controlled sensor node with a laser diode output. The receiver is a standard CCD camera with a 1-inch aperture lens, and both hardware and software implementations of the video semaphore decoding algorithm. With this system sensor data can be reliably transmitted 21 km form San Francisco to Berkeley.
Simulation of the color vision: decoding quantum-electric transduction
Directory of Open Access Journals (Sweden)
Élgion Lúcio da Silva Loreto
2008-08-01
Full Text Available We propose an experimental simulation, using accessible and low cost materials, on the biophysical mechanism of the color vision in accordance with the Young-Helmholtz s Trichromatic Theory, approaching mainly the coding and decoding process of electric signs that arrive to the cerebral cortex. The stimulus that unchains this process is given through transformation of the quantized energy of a light photon that takes place in the photocells of the retina of the human eye. The construction of a simple system of collection and analysis of data, using a multimeter, filters, LDR and LEDs allows us to establish connections between the visual system and the simulation model.
A Novel Modified Algorithm with Reduced Complexity LDPC Code Decoder
Directory of Open Access Journals (Sweden)
Song Yang
2014-10-01
Full Text Available A novel efficient decoding algorithm reduced the sum-product algorithm (SPA Complexity with LPDC code is proposed. Base on the hyperbolic tangent rule, modified the Check node update with two horizontal process, which have similar calculation, Motivated by the finding that sun- min (MS algorithm reduce the complexity reducing the approximation error in the horizontal process, simplify the information weight small part. Compared with the exiting approximations, the proposed method is less computational complexity than SPA algorithm. Simulation results show that the author algorithm can achieve performance very close SPA.
Abediseid, Walid
2012-01-01
complexity of sphere decoding for the quasi- static, lattice space-time (LAST) coded MIMO channel. Specifically, we drive an upper bound of the tail distribution of the decoder's computational complexity. We show that when the computational complexity exceeds
Integrating robotic action with biologic perception: A brain-machine symbiosis theory
Mahmoudi, Babak
In patients with motor disability the natural cyclic flow of information between the brain and external environment is disrupted by their limb impairment. Brain-Machine Interfaces (BMIs) aim to provide new communication channels between the brain and environment by direct translation of brain's internal states into actions. For enabling the user in a wide range of daily life activities, the challenge is designing neural decoders that autonomously adapt to different tasks, environments, and to changes in the pattern of neural activity. In this dissertation, a novel decoding framework for BMIs is developed in which a computational agent autonomously learns how to translate neural states into action based on maximization of a measure of shared goal between user and the agent. Since the agent and brain share the same goal, a symbiotic relationship between them will evolve therefore this decoding paradigm is called a Brain-Machine Symbiosis (BMS) framework. A decoding agent was implemented within the BMS framework based on the Actor-Critic method of Reinforcement Learning. The rule of the Actor as a neural decoder was to find mapping between the neural representation of motor states in the primary motor cortex (MI) and robot actions in order to solve reaching tasks. The Actor learned the optimal control policy using an evaluative feedback that was estimated by the Critic directly from the user's neural activity of the Nucleus Accumbens (NAcc). Through a series of computational neuroscience studies in a cohort of rats it was demonstrated that NAcc could provide a useful evaluative feedback by predicting the increase or decrease in the probability of earning reward based on the environmental conditions. Using a closed-loop BMI simulator it was demonstrated the Actor-Critic decoding architecture was able to adapt to different tasks as well as changes in the pattern of neural activity. The custom design of a dual micro-wire array enabled simultaneous implantation of MI and
International Nuclear Information System (INIS)
Flinchem, J.
1980-01-01
This document contains procedures which apply to operations performed on individual P-1c machines in the Machine Interface Test System (MITS) at AiResearch Manufacturing Company's Torrance, California Facility
Directory of Open Access Journals (Sweden)
Jose M Carmena
2004-12-01
Full Text Available Dr. Octopus, the villain of the movie "Spiderman 2", is a fusion of man and machine. Neuroscientist Jose Carmena examines the facts behind this fictional account of a brain- machine interface
Tschätsch, Heinz
2010-01-01
Machining and cutting technologies are still crucial for many manufacturing processes. This reference presents all important machining processes in a comprehensive and coherent way. It includes many examples of concrete calculations, problems and solutions.
Jackson, Mark J
2011-01-01
Abrasive machining is key to obtaining the desired geometry and surface quality in manufacturing. This book discusses the fundamentals and advances in the abrasive machining processes. It provides a complete overview of developing areas in the field.
Pontier, Matthijs
2015-01-01
The essays in this book, written by researchers from both humanities and sciences, describe various theoretical and experimental approaches to adding medical ethics to a machine in medical settings. Medical machines are in close proximity with human beings, and getting closer: with patients who are in vulnerable states of health, who have disabilities of various kinds, with the very young or very old, and with medical professionals. In such contexts, machines are undertaking important medical tasks that require emotional sensitivity, knowledge of medical codes, human dignity, and privacy. As machine technology advances, ethical concerns become more urgent: should medical machines be programmed to follow a code of medical ethics? What theory or theories should constrain medical machine conduct? What design features are required? Should machines share responsibility with humans for the ethical consequences of medical actions? How ought clinical relationships involving machines to be modeled? Is a capacity for e...
Learning Orthographic Structure With Sequential Generative Neural Networks.
Testolin, Alberto; Stoianov, Ivilin; Sperduti, Alessandro; Zorzi, Marco
2016-04-01
Learning the structure of event sequences is a ubiquitous problem in cognition and particularly in language. One possible solution is to learn a probabilistic generative model of sequences that allows making predictions about upcoming events. Though appealing from a neurobiological standpoint, this approach is typically not pursued in connectionist modeling. Here, we investigated a sequential version of the restricted Boltzmann machine (RBM), a stochastic recurrent neural network that extracts high-order structure from sensory data through unsupervised generative learning and can encode contextual information in the form of internal, distributed representations. We assessed whether this type of network can extract the orthographic structure of English monosyllables by learning a generative model of the letter sequences forming a word training corpus. We show that the network learned an accurate probabilistic model of English graphotactics, which can be used to make predictions about the letter following a given context as well as to autonomously generate high-quality pseudowords. The model was compared to an extended version of simple recurrent networks, augmented with a stochastic process that allows autonomous generation of sequences, and to non-connectionist probabilistic models (n-grams and hidden Markov models). We conclude that sequential RBMs and stochastic simple recurrent networks are promising candidates for modeling cognition in the temporal domain. Copyright © 2015 Cognitive Science Society, Inc.
Decoding and finding the minimum distance with Gröbner bases : history and new insights
Bulygin, S.; Pellikaan, G.R.; Woungang, I.; Misra, S.; Misra, S.C.
2010-01-01
In this chapter, we discuss decoding techniques and finding the minimum distance of linear codes with the use of Grobner bases. First, we give a historical overview of decoding cyclic codes via solving systems polynominal equations over finite fields. In particular, we mention papers of Cooper,.
Video coding and decoding devices and methods preserving ppg relevant information
2013-01-01
The present invention relates to a video encoding device (10) for encoding video data and a corresponding video decoding device, wherein during decoding PPG relevant information shall be preserved. For this purpose the video coding device (10) comprises a first encoder (20) for encoding input video
A Fully Parallel VLSI-implementation of the Viterbi Decoding Algorithm
DEFF Research Database (Denmark)
Sparsø, Jens; Jørgensen, Henrik Nordtorp; Paaske, Erik
1989-01-01
In this paper we describe the implementation of a K = 7, R = 1/2 single-chip Viterbi decoder intended to operate at 10-20 Mbit/sec. We propose a general, regular and area efficient floor-plan that is also suitable for implementation of decoders for codes with different generator polynomials...
Multi-Trial Guruswami–Sudan Decoding for Generalised Reed–Solomon Codes
DEFF Research Database (Denmark)
Nielsen, Johan Sebastian Rosenkilde; Zeh, Alexander
2013-01-01
An iterated refinement procedure for the Guruswami–Sudan list decoding algorithm for Generalised Reed–Solomon codes based on Alekhnovich’s module minimisation is proposed. The method is parametrisable and allows variants of the usual list decoding approach. In particular, finding the list...
The Three Stages of Coding and Decoding in Listening Courses of College Japanese Specialty
Yang, Fang
2008-01-01
The main focus of research papers on listening teaching published in recent years is the theoretical meanings of decoding on the training of listening comprehension ability. Although in many research papers the bottom-up approach and top-down approach, information processing mode theory, are applied to illustrate decoding and to emphasize the…
A Parallel Decoding Algorithm for Short Polar Codes Based on Error Checking and Correcting
Pan, Xiaofei; Pan, Kegang; Ye, Zhan; Gong, Chao
2014-01-01
We propose a parallel decoding algorithm based on error checking and correcting to improve the performance of the short polar codes. In order to enhance the error-correcting capacity of the decoding algorithm, we first derive the error-checking equations generated on the basis of the frozen nodes, and then we introduce the method to check the errors in the input nodes of the decoder by the solutions of these equations. In order to further correct those checked errors, we adopt the method of modifying the probability messages of the error nodes with constant values according to the maximization principle. Due to the existence of multiple solutions of the error-checking equations, we formulate a CRC-aided optimization problem of finding the optimal solution with three different target functions, so as to improve the accuracy of error checking. Besides, in order to increase the throughput of decoding, we use a parallel method based on the decoding tree to calculate probability messages of all the nodes in the decoder. Numerical results show that the proposed decoding algorithm achieves better performance than that of some existing decoding algorithms with the same code length. PMID:25540813
Iterative channel decoding of FEC-based multiple-description codes.
Chang, Seok-Ho; Cosman, Pamela C; Milstein, Laurence B
2012-03-01
Multiple description coding has been receiving attention as a robust transmission framework for multimedia services. This paper studies the iterative decoding of FEC-based multiple description codes. The proposed decoding algorithms take advantage of the error detection capability of Reed-Solomon (RS) erasure codes. The information of correctly decoded RS codewords is exploited to enhance the error correction capability of the Viterbi algorithm at the next iteration of decoding. In the proposed algorithm, an intradescription interleaver is synergistically combined with the iterative decoder. The interleaver does not affect the performance of noniterative decoding but greatly enhances the performance when the system is iteratively decoded. We also address the optimal allocation of RS parity symbols for unequal error protection. For the optimal allocation in iterative decoding, we derive mathematical equations from which the probability distributions of description erasures can be generated in a simple way. The performance of the algorithm is evaluated over an orthogonal frequency-division multiplexing system. The results show that the performance of the multiple description codes is significantly enhanced.
Gupta, Neha; Parihar, Priyanka; Neema, Vaibhav
2018-04-01
Researchers have proposed many circuit techniques to reduce leakage power dissipation in memory cells. If we want to reduce the overall power in the memory system, we have to work on the input circuitry of memory architecture i.e. row and column decoder. In this research work, low leakage power with a high speed row and column decoder for memory array application is designed and four new techniques are proposed. In this work, the comparison of cluster DECODER, body bias DECODER, source bias DECODER, and source coupling DECODER are designed and analyzed for memory array application. Simulation is performed for the comparative analysis of different DECODER design parameters at 180 nm GPDK technology file using the CADENCE tool. Simulation results show that the proposed source bias DECODER circuit technique decreases the leakage current by 99.92% and static energy by 99.92% at a supply voltage of 1.2 V. The proposed circuit also improves dynamic power dissipation by 5.69%, dynamic PDP/EDP 65.03% and delay 57.25% at 1.2 V supply voltage.
The Contribution of Attentional Control and Working Memory to Reading Comprehension and Decoding
Arrington, C. Nikki; Kulesz, Paulina A.; Francis, David J.; Fletcher, Jack M.; Barnes, Marcia A.
2014-01-01
Little is known about how specific components of working memory, namely, attentional processes including response inhibition, sustained attention, and cognitive inhibition, are related to reading decoding and comprehension. The current study evaluated the relations of reading comprehension, decoding, working memory, and attentional control in…
Fast N-Gram Language Model Look-Ahead for Decoders With Static Pronunciation Prefix Trees
Huijbregts, M.A.H.; Ordelman, Roeland J.F.; de Jong, Franciska M.G.
2008-01-01
Decoders that make use of token-passing restrict their search space by various types of token pruning. With use of the Language Model Look-Ahead (LMLA) technique it is possible to increase the number of tokens that can be pruned without loss of decoding precision. Unfortunately, for token passing
Scaffolding Students’ Independent Decoding of Unfamiliar Text with a Prototype of an eBook-Feature
DEFF Research Database (Denmark)
Gissel, Stig Toke
2015-01-01
the relevant spelling patterns and in generalizing, in order to strengthen their decoding skills. The prototype was evaluated with Danish students in the second grade to see how and under what circumstances students can use the feature in ways that strengthen their decoding skills and support them in reading...
Hamilton, Stephen; Freed, Erin; Long, Debra L.
2016-01-01
The aim of this study was to examine predictions derived from a proposal about the relation between word-decoding skill and working memory capacity, called verbal efficiency theory. The theory states that poor word representations and slow decoding processes consume resources in working memory that would otherwise be used to execute high-level…
Horikawa, Tomoyasu; Kamitani, Yukiyasu
2017-01-01
Dreaming is generally thought to be generated by spontaneous brain activity during sleep with patterns common to waking experience. This view is supported by a recent study demonstrating that dreamed objects can be predicted from brain activity during sleep using statistical decoders trained with stimulus-induced brain activity. However, it remains unclear whether and how visual image features associated with dreamed objects are represented in the brain. In this study, we used a deep neural network (DNN) model for object recognition as a proxy for hierarchical visual feature representation, and DNN features for dreamed objects were analyzed with brain decoding of fMRI data collected during dreaming. The decoders were first trained with stimulus-induced brain activity labeled with the feature values of the stimulus image from multiple DNN layers. The decoders were then used to decode DNN features from the dream fMRI data, and the decoded features were compared with the averaged features of each object category calculated from a large-scale image database. We found that the feature values decoded from the dream fMRI data positively correlated with those associated with dreamed object categories at mid- to high-level DNN layers. Using the decoded features, the dreamed object category could be identified at above-chance levels by matching them to the averaged features for candidate categories. The results suggest that dreaming recruits hierarchical visual feature representations associated with objects, which may support phenomenal aspects of dream experience.
Decoding error-correcting codes with Gröbner bases
Bulygin, S.; Pellikaan, G.R.; Veldhuis, R.; Cronie, H.; Hoeksema, H.
2007-01-01
The decoding of arbitrary linear block codes is accomplished by solving a system of quadratic equations by means of Buchberger’s algorithm for finding a Gröbner basis. This generalizes the algorithm of Berlekamp-Massey for decoding Reed Solomon, Goppa and cyclic codes up to half the true minimum
Bounded distance decoding of linear error-correcting codes with Gröbner bases
Bulygin, S.; Pellikaan, G.R.
2009-01-01
The problem of bounded distance decoding of arbitrary linear codes using Gröbner bases is addressed. A new method is proposed, which is based on reducing an initial decoding problem to solving a certain system of polynomial equations over a finite field. The peculiarity of this system is that, when
A lossy graph model for delay reduction in generalized instantly decodable network coding
Douik, Ahmed S.; Sorour, Sameh; Al-Naffouri, Tareq Y.; Alouini, Mohamed-Slim
2014-01-01
, arising from lossy feedback events, when the expected decoding delay of XORing them among themselves or with other certain packets is lower than that expected when sending these packets separately. We compare the decoding delay performance of LG-IDNC and G
Error Recovery Properties and Soft Decoding of Quasi-Arithmetic Codes
Directory of Open Access Journals (Sweden)
Christine Guillemot
2007-08-01
Full Text Available This paper first introduces a new set of aggregated state models for soft-input decoding of quasi arithmetic (QA codes with a termination constraint. The decoding complexity with these models is linear with the sequence length. The aggregation parameter controls the tradeoff between decoding performance and complexity. It is shown that close-to-optimal decoding performance can be obtained with low values of the aggregation parameter, that is, with a complexity which is significantly reduced with respect to optimal QA bit/symbol models. The choice of the aggregation parameter depends on the synchronization recovery properties of the QA codes. This paper thus describes a method to estimate the probability mass function (PMF of the gain/loss of symbols following a single bit error (i.e., of the difference between the number of encoded and decoded symbols. The entropy of the gain/loss turns out to be the average amount of information conveyed by a length constraint on both the optimal and aggregated state models. This quantity allows us to choose the value of the aggregation parameter that will lead to close-to-optimal decoding performance. It is shown that the optimum position for the length constraint is not the last time instant of the decoding process. This observation leads to the introduction of a new technique for robust decoding of QA codes with redundancy which turns out to outperform techniques based on the concept of forbidden symbol.
Using convolutional decoding to improve time delay and phase estimation in digital communications
Ormesher, Richard C [Albuquerque, NM; Mason, John J [Albuquerque, NM
2010-01-26
The time delay and/or phase of a communication signal received by a digital communication receiver can be estimated based on a convolutional decoding operation that the communication receiver performs on the received communication signal. If the original transmitted communication signal has been spread according to a spreading operation, a corresponding despreading operation can be integrated into the convolutional decoding operation.
Padeliadu, Susana; Antoniou, Faye
2014-01-01
Experts widely consider decoding and fluency as the basis of reading comprehension, while at the same time consistently documenting problems in these areas as major characteristics of students with learning disabilities. However, scholars have developed most of the relevant research within phonologically deep languages, wherein decoding problems…
Tingerthal, John Steven
2013-01-01
Using case study methodology and autoethnographic methods, this study examines a process of curricular development known as "Decoding the Disciplines" (Decoding) by documenting the experience of its application in a construction engineering mechanics course. Motivated by the call to integrate what is known about teaching and learning…
Macpherson, A L
2010-01-01
A summary of the Machine Protection System of the LHC is given, with particular attention given to the outstanding issues to be addressed, rather than the successes of the machine protection system from the 2009 run. In particular, the issues of Safe Machine Parameter system, collimation and beam cleaning, the beam dump system and abort gap cleaning, injection and dump protection, and the overall machine protection program for the upcoming run are summarised.
International Nuclear Information System (INIS)
1990-06-01
This book has introduction of dictionary of machine terms, and a compilation committee and introductory remarks. It gives descriptions of the machine terms in alphabetical order from a to Z and also includes abbreviation of machine terms and symbol table, way to read mathematical symbols and abbreviation and terms of drawings.
Energy Technology Data Exchange (ETDEWEB)
Hugli, A
1984-01-01
The following questions are addressed: is there a difference between machines and men, between human communication and communication with machines. Will we ever reach the point when the dream of artificial intelligence becomes a reality. Will thinking machines be able to replace the human spirit in all its aspects. Social consequences and philosophical aspects are addressed. 8 references.
DEFF Research Database (Denmark)
Andersen, Henrik Reif; Mørk, Simon; Sørensen, Morten U.
1997-01-01
Turing showed the existence of a model universal for the set of Turing machines in the sense that given an encoding of any Turing machine asinput the universal Turing machine simulates it. We introduce the concept of universality for reactive systems and construct a CCS processuniversal...
HTS machine laboratory prototype
DEFF Research Database (Denmark)
machine. The machine comprises six stationary HTS field windings wound from both YBCO and BiSCOO tape operated at liquid nitrogen temperature and enclosed in a cryostat, and a three phase armature winding spinning at up to 300 rpm. This design has full functionality of HTS synchronous machines. The design...
Peacock, Marion E.
The programed instruction manual is designed to aid the student in learning the parts, uses, and operation of the sewing machine. Drawings of sewing machine parts are presented, and space is provided for the student's written responses. Following an introductory section identifying sewing machine parts, the manual deals with each part and its…