Dynamics of neural networks with continuous attractors
Fung, C. C. Alan; Wong, K. Y. Michael; Wu, Si
2008-10-01
We investigate the dynamics of continuous attractor neural networks (CANNs). Due to the translational invariance of their neuronal interactions, CANNs can hold a continuous family of stationary states. We systematically explore how their neutral stability facilitates the tracking performance of a CANN, which is believed to have wide applications in brain functions. We develop a perturbative approach that utilizes the dominant movement of the network stationary states in the state space. We quantify the distortions of the bump shape during tracking, and study their effects on the tracking performance. Results are obtained on the maximum speed for a moving stimulus to be trackable, and the reaction time to catch up an abrupt change in stimulus.
Context-dependent retrieval of information by neural-network dynamics with continuous attractors.
Tsuboshita, Yukihiro; Okamoto, Hiroshi
2007-08-01
Memory retrieval in neural networks has traditionally been described by dynamic systems with discrete attractors. However, recent neurophysiological findings of graded persistent activity suggest that memory retrieval in the brain is more likely to be described by dynamic systems with continuous attractors. To explore what sort of information processing is achieved by continuous-attractor dynamics, keyword extraction from documents by a network of bistable neurons, which gives robust continuous attractors, is examined. Given an associative network of terms, a continuous attractor led by propagation of neuronal activation in this network appears to represent keywords that express underlying meaning of a document encoded in the initial state of the network-activation pattern. A dominant hypothesis in cognitive psychology is that long-term memory is archived in the network structure, which resembles associative networks of terms. Our results suggest that keyword extraction by the neural-network dynamics with continuous attractors might symbolically represent context-dependent retrieval of short-term memory from long-term memory in the brain.
Accurate path integration in continuous attractor network models of grid cells.
Burak, Yoram; Fiete, Ila R
2009-02-01
Grid cells in the rat entorhinal cortex display strikingly regular firing responses to the animal's position in 2-D space and have been hypothesized to form the neural substrate for dead-reckoning. However, errors accumulate rapidly when velocity inputs are integrated in existing models of grid cell activity. To produce grid-cell-like responses, these models would require frequent resets triggered by external sensory cues. Such inadequacies, shared by various models, cast doubt on the dead-reckoning potential of the grid cell system. Here we focus on the question of accurate path integration, specifically in continuous attractor models of grid cell activity. We show, in contrast to previous models, that continuous attractor models can generate regular triangular grid responses, based on inputs that encode only the rat's velocity and heading direction. We consider the role of the network boundary in the integration performance of the network and show that both periodic and aperiodic networks are capable of accurate path integration, despite important differences in their attractor manifolds. We quantify the rate at which errors in the velocity integration accumulate as a function of network size and intrinsic noise within the network. With a plausible range of parameters and the inclusion of spike variability, our model networks can accurately integrate velocity inputs over a maximum of approximately 10-100 meters and approximately 1-10 minutes. These findings form a proof-of-concept that continuous attractor dynamics may underlie velocity integration in the dorsolateral medial entorhinal cortex. The simulations also generate pertinent upper bounds on the accuracy of integration that may be achieved by continuous attractor dynamics in the grid cell network. We suggest experiments to test the continuous attractor model and differentiate it from models in which single cells establish their responses independently of each other.
Attractors in complex networks
Rodrigues, Alexandre A. P.
2017-10-01
In the framework of the generalized Lotka-Volterra model, solutions representing multispecies sequential competition can be predictable with high probability. In this paper, we show that it occurs because the corresponding "heteroclinic channel" forms part of an attractor. We prove that, generically, in an attracting heteroclinic network involving a finite number of hyperbolic and non-resonant saddle-equilibria whose linearization has only real eigenvalues, the connections corresponding to the most positive expanding eigenvalues form part of an attractor (observable in numerical simulations).
Stringer, Simon M; Rolls, Edmund T
2006-12-01
A key issue is how networks in the brain learn to perform path integration, that is update a represented position using a velocity signal. Using head direction cells as an example, we show that a competitive network could self-organize to learn to respond to combinations of head direction and angular head rotation velocity. These combination cells can then be used to drive a continuous attractor network to the next head direction based on the incoming rotation signal. An associative synaptic modification rule with a short term memory trace enables preceding combination cell activity during training to be associated with the next position in the continuous attractor network. The network accounts for the presence of neurons found in the brain that respond to combinations of head direction and angular head rotation velocity. Analogous networks in the hippocampal system could self-organize to perform path integration of place and spatial view representations.
Finite connectivity attractor neural networks
International Nuclear Information System (INIS)
Wemmenhove, B; Coolen, A C C
2003-01-01
We study a family of diluted attractor neural networks with a finite average number of (symmetric) connections per neuron. As in finite connectivity spin glasses, their equilibrium properties are described by order parameter functions, for which we derive an integral equation in replica symmetric approximation. A bifurcation analysis of this equation reveals the locations of the paramagnetic to recall and paramagnetic to spin-glass transition lines in the phase diagram. The line separating the retrieval phase from the spin-glass phase is calculated at zero temperature. All phase transitions are found to be continuous
Attractor dynamics in local neuronal networks
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Jean-Philippe eThivierge
2014-03-01
Full Text Available Patterns of synaptic connectivity in various regions of the brain are characterized by the presence of synaptic motifs, defined as unidirectional and bidirectional synaptic contacts that follow a particular configuration and link together small groups of neurons. Recent computational work proposes that a relay network (two populations communicating via a third, relay population of neurons can generate precise patterns of neural synchronization. Here, we employ two distinct models of neuronal dynamics and show that simulated neural circuits designed in this way are caught in a global attractor of activity that prevents neurons from modulating their response on the basis of incoming stimuli. To circumvent the emergence of a fixed global attractor, we propose a mechanism of selective gain inhibition that promotes flexible responses to external stimuli. We suggest that local neuronal circuits may employ this mechanism to generate precise patterns of neural synchronization whose transient nature delimits the occurrence of a brief stimulus.
Google matrix, dynamical attractors, and Ulam networks.
Shepelyansky, D L; Zhirov, O V
2010-03-01
We study the properties of the Google matrix generated by a coarse-grained Perron-Frobenius operator of the Chirikov typical map with dissipation. The finite-size matrix approximant of this operator is constructed by the Ulam method. This method applied to the simple dynamical model generates directed Ulam networks with approximate scale-free scaling and characteristics being in certain features similar to those of the world wide web with approximate scale-free degree distributions as well as two characteristics similar to the web: a power-law decay in PageRank that mirrors the decay of PageRank on the world wide web and a sensitivity to the value alpha in PageRank. The simple dynamical attractors play here the role of popular websites with a strong concentration of PageRank. A variation in the Google parameter alpha or other parameters of the dynamical map can drive the PageRank of the Google matrix to a delocalized phase with a strange attractor where the Google search becomes inefficient.
Attractor neural networks with resource-efficient synaptic connectivity
Pehlevan, Cengiz; Sengupta, Anirvan
Memories are thought to be stored in the attractor states of recurrent neural networks. Here we explore how resource constraints interplay with memory storage function to shape synaptic connectivity of attractor networks. We propose that given a set of memories, in the form of population activity patterns, the neural circuit choses a synaptic connectivity configuration that minimizes a resource usage cost. We argue that the total synaptic weight (l1-norm) in the network measures the resource cost because synaptic weight is correlated with synaptic volume, which is a limited resource, and is proportional to neurotransmitter release and post-synaptic current, both of which cost energy. Using numerical simulations and replica theory, we characterize optimal connectivity profiles in resource-efficient attractor networks. Our theory explains several experimental observations on cortical connectivity profiles, 1) connectivity is sparse, because synapses are costly, 2) bidirectional connections are overrepresented and 3) are stronger, because attractor states need strong recurrence.
Hierarchical-control-based output synchronization of coexisting attractor networks
International Nuclear Information System (INIS)
Yun-Zhong, Song; Yi-Fa, Tang
2010-01-01
This paper introduces the concept of hierarchical-control-based output synchronization of coexisting attractor networks. Within the new framework, each dynamic node is made passive at first utilizing intra-control around its own arena. Then each dynamic node is viewed as one agent, and on account of that, the solution of output synchronization of coexisting attractor networks is transformed into a multi-agent consensus problem, which is made possible by virtue of local interaction between individual neighbours; this distributed working way of coordination is coined as inter-control, which is only specified by the topological structure of the network. Provided that the network is connected and balanced, the output synchronization would come true naturally via synergy between intra and inter-control actions, where the Tightness is proved theoretically via convex composite Lyapunov functions. For completeness, several illustrative examples are presented to further elucidate the novelty and efficacy of the proposed scheme. (general)
Boolean Factor Analysis by Attractor Neural Network
Czech Academy of Sciences Publication Activity Database
Frolov, A. A.; Húsek, Dušan; Muraviev, I. P.; Polyakov, P.Y.
2007-01-01
Roč. 18, č. 3 (2007), s. 698-707 ISSN 1045-9227 R&D Projects: GA AV ČR 1ET100300419; GA ČR GA201/05/0079 Institutional research plan: CEZ:AV0Z10300504 Keywords : recurrent neural network * Hopfield-like neural network * associative memory * unsupervised learning * neural network architecture * neural network application * statistics * Boolean factor analysis * dimensionality reduction * features clustering * concepts search * information retrieval Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 2.769, year: 2007
Reconstruction of the El Nino attractor with neural networks
International Nuclear Information System (INIS)
Grieger, B.; Latif, M.
1993-01-01
Based on a combined data set of sea surface temperature, zonal surface wind stress and upper ocean heat content the dynamics of the El Nino phenomenon is investigated. In a reduced phase space spanned by the first four EOFs two different stochastic models are estimated from the data. A nonlinear model represented by a simulated neural network is compared with a linear model obtained with the Principal Oscillation Pattern (POP) analysis. While the linear model is limited to damped oscillations onto a fix point attractor, the nonlinear model recovers a limit cycle attractor. This indicates that the real system is located above the bifurcation point in parameter space supporting self-sustained oscillations. The results are discussed with respect to consistency with current theory. (orig.)
Robustness of unstable attractors in arbitrarily sized pulse-coupled networks with delay
International Nuclear Information System (INIS)
Broer, Henk; Efstathiou, Konstantinos; Subramanian, Easwar
2008-01-01
We consider arbitrarily large networks of pulse-coupled oscillators with non-zero delay where the coupling is given by the Mirollo–Strogatz function. We prove that such systems have unstable attractors (saddle periodic orbits whose stable set has non-empty interior) in an open parameter region for three or more oscillators. The evolution operator of the system can be discontinuous and we propose an improved model with continuous evolution operator
Neural attractor network for application in visual field data classification
International Nuclear Information System (INIS)
Fink, Wolfgang
2004-01-01
The purpose was to introduce a novel method for computer-based classification of visual field data derived from perimetric examination, that may act as a ' counsellor', providing an independent 'second opinion' to the diagnosing physician. The classification system consists of a Hopfield-type neural attractor network that obtains its input data from perimetric examination results. An iterative relaxation process determines the states of the neurons dynamically. Therefore, even 'noisy' perimetric output, e.g., early stages of a disease, may eventually be classified correctly according to the predefined idealized visual field defect (scotoma) patterns, stored as attractors of the network, that are found with diseases of the eye, optic nerve and the central nervous system. Preliminary tests of the classification system on real visual field data derived from perimetric examinations have shown a classification success of over 80%. Some of the main advantages of the Hopfield-attractor-network-based approach over feed-forward type neural networks are: (1) network architecture is defined by the classification problem; (2) no training is required to determine the neural coupling strengths; (3) assignment of an auto-diagnosis confidence level is possible by means of an overlap parameter and the Hamming distance. In conclusion, the novel method for computer-based classification of visual field data, presented here, furnishes a valuable first overview and an independent 'second opinion' in judging perimetric examination results, pointing towards a final diagnosis by a physician. It should not be considered a substitute for the diagnosing physician. Thanks to the worldwide accessibility of the Internet, the classification system offers a promising perspective towards modern computer-assisted diagnosis in both medicine and tele-medicine, for example and in particular, with respect to non-ophthalmic clinics or in communities where perimetric expertise is not readily available
An Efficient Algorithm for Computing Attractors of Synchronous And Asynchronous Boolean Networks
Zheng, Desheng; Yang, Guowu; Li, Xiaoyu; Wang, Zhicai; Liu, Feng; He, Lei
2013-01-01
Biological networks, such as genetic regulatory networks, often contain positive and negative feedback loops that settle down to dynamically stable patterns. Identifying these patterns, the so-called attractors, can provide important insights for biologists to understand the molecular mechanisms underlying many coordinated cellular processes such as cellular division, differentiation, and homeostasis. Both synchronous and asynchronous Boolean networks have been used to simulate genetic regulatory networks and identify their attractors. The common methods of computing attractors are that start with a randomly selected initial state and finish with exhaustive search of the state space of a network. However, the time complexity of these methods grows exponentially with respect to the number and length of attractors. Here, we build two algorithms to achieve the computation of attractors in synchronous and asynchronous Boolean networks. For the synchronous scenario, combing with iterative methods and reduced order binary decision diagrams (ROBDD), we propose an improved algorithm to compute attractors. For another algorithm, the attractors of synchronous Boolean networks are utilized in asynchronous Boolean translation functions to derive attractors of asynchronous scenario. The proposed algorithms are implemented in a procedure called geneFAtt. Compared to existing tools such as genYsis, geneFAtt is significantly faster in computing attractors for empirical experimental systems. Availability The software package is available at https://sites.google.com/site/desheng619/download. PMID:23585840
Bump formation in a binary attractor neural network
International Nuclear Information System (INIS)
Koroutchev, Kostadin; Korutcheva, Elka
2006-01-01
The conditions for the formation of local bumps in the activity of binary attractor neural networks with spatially dependent connectivity are investigated. We show that these formations are observed when asymmetry between the activity during the retrieval and learning is imposed. An analytical approximation for the order parameters is derived. The corresponding phase diagram shows a relatively large and stable region where this effect is observed, although critical storage and information capacities drastically decrease inside that region. We demonstrate that the stability of the network, when starting from the bump formation, is larger than the stability when starting even from the whole pattern. Finally, we show a very good agreement between the analytical results and the simulations performed for different topologies of the network
Topology and computational performance of attractor neural networks
International Nuclear Information System (INIS)
McGraw, Patrick N.; Menzinger, Michael
2003-01-01
To explore the relation between network structure and function, we studied the computational performance of Hopfield-type attractor neural nets with regular lattice, random, small-world, and scale-free topologies. The random configuration is the most efficient for storage and retrieval of patterns by the network as a whole. However, in the scale-free case retrieval errors are not distributed uniformly among the nodes. The portion of a pattern encoded by the subset of highly connected nodes is more robust and efficiently recognized than the rest of the pattern. The scale-free network thus achieves a very strong partial recognition. The implications of these findings for brain function and social dynamics are suggestive
Detection of strong attractors in social media networks.
Qasem, Ziyaad; Jansen, Marc; Hecking, Tobias; Hoppe, H Ulrich
2016-01-01
Detection of influential actors in social media such as Twitter or Facebook plays an important role for improving the quality and efficiency of work and services in many fields such as education and marketing. The work described here aims to introduce a new approach that characterizes the influence of actors by the strength of attracting new active members into a networked community. We present a model of influence of an actor that is based on the attractiveness of the actor in terms of the number of other new actors with which he or she has established relations over time. We have used this concept and measure of influence to determine optimal seeds in a simulation of influence maximization using two empirically collected social networks for the underlying graphs. Our empirical results on the datasets demonstrate that our measure stands out as a useful measure to define the attractors comparing to the other influence measures.
Li, X Y; Yang, G W; Zheng, D S; Guo, W S; Hung, W N N
2015-04-28
Genetic regulatory networks are the key to understanding biochemical systems. One condition of the genetic regulatory network under different living environments can be modeled as a synchronous Boolean network. The attractors of these Boolean networks will help biologists to identify determinant and stable factors. Existing methods identify attractors based on a random initial state or the entire state simultaneously. They cannot identify the fixed length attractors directly. The complexity of including time increases exponentially with respect to the attractor number and length of attractors. This study used the bounded model checking to quickly locate fixed length attractors. Based on the SAT solver, we propose a new algorithm for efficiently computing the fixed length attractors, which is more suitable for large Boolean networks and numerous attractors' networks. After comparison using the tool BooleNet, empirical experiments involving biochemical systems demonstrated the feasibility and efficiency of our approach.
Attractor controllability of Boolean networks by flipping a subset of their nodes
Rafimanzelat, Mohammad Reza; Bahrami, Fariba
2018-04-01
The controllability analysis of Boolean networks (BNs), as models of biomolecular regulatory networks, has drawn the attention of researchers in recent years. In this paper, we aim at governing the steady-state behavior of BNs using an intervention method which can easily be applied to most real system, which can be modeled as BNs, particularly to biomolecular regulatory networks. To this end, we introduce the concept of attractor controllability of a BN by flipping a subset of its nodes, as the possibility of making a BN converge from any of its attractors to any other one, by one-time flipping members of a subset of BN nodes. Our approach is based on the algebraic state-space representation of BNs using semi-tensor product of matrices. After introducing some new matrix tools, we use them to derive necessary and sufficient conditions for the attractor controllability of BNs. A forward search algorithm is then suggested to identify the minimal perturbation set for attractor controllability of a BN. Next, a lower bound is derived for the cardinality of this set. Two new indices are also proposed for quantifying the attractor controllability of a BN and the influence of each network variable on the attractor controllability of the network and the relationship between them is revealed. Finally, we confirm the efficiency of the proposed approach by applying it to the BN models of some real biomolecular networks.
Sun, Mengyang; Cheng, Xianrui; Socolar, Joshua E S
2013-06-01
A common approach to the modeling of gene regulatory networks is to represent activating or repressing interactions using ordinary differential equations for target gene concentrations that include Hill function dependences on regulator gene concentrations. An alternative formulation represents the same interactions using Boolean logic with time delays associated with each network link. We consider the attractors that emerge from the two types of models in the case of a simple but nontrivial network: a figure-8 network with one positive and one negative feedback loop. We show that the different modeling approaches give rise to the same qualitative set of attractors with the exception of a possible fixed point in the ordinary differential equation model in which concentrations sit at intermediate values. The properties of the attractors are most easily understood from the Boolean perspective, suggesting that time-delay Boolean modeling is a useful tool for understanding the logic of regulatory networks.
Directory of Open Access Journals (Sweden)
Marcello eMulas
2016-02-01
Full Text Available After the discovery of grid cells, which are an essential component to understand how the mammalian brain encodes spatial information, three main classes of computational models were proposed in order to explain their working principles. Amongst them, the one based on continuous attractor networks (CAN, is promising in terms of biological plausibility and suitable for robotic applications. However, in its current formulation, it is unable to reproduce important electrophysiological findings and cannot be used to perform path integration for long periods of time. In fact, in absence of an appropriate resetting mechanism, the accumulation of errors overtime due to the noise intrinsic in velocity estimation and neural computation prevents CAN models to reproduce stable spatial grid patterns. In this paper, we propose an extension of the CAN model using Hebbian plasticity to anchor grid cell activity to environmental landmarks. To validate our approach we used as input to the neural simulations both artificial data and real data recorded from a robotic setup. The additional neural mechanism can not only anchor grid patterns to external sensory cues but also recall grid patterns generated in previously explored environments. These results might be instrumental for next generation bio-inspired robotic navigation algorithms that take advantage of neural computation in order to cope with complex and dynamic environments.
Roach, James; Sander, Leonard; Zochowski, Michal
Auto-associative memory is the ability to retrieve a pattern from a small fraction of the pattern and is an important function of neural networks. Within this context, memories that are stored within the synaptic strengths of networks act as dynamical attractors for network firing patterns. In networks with many encoded memories, some attractors will be stronger than others. This presents the problem of how networks switch between attractors depending on the situation. We suggest that regulation of neuronal spike-frequency adaptation (SFA) provides a universal mechanism for network-wide attractor selectivity. Here we demonstrate in a Hopfield type attractor network that neurons minimal SFA will reliably activate in the pattern corresponding to a local attractor and that a moderate increase in SFA leads to the network to converge to the strongest attractor state. Furthermore, we show that on long time scales SFA allows for temporal sequences of activation to emerge. Finally, using a model of cholinergic modulation within the cortex we argue that dynamic regulation of attractor preference by SFA could be critical for the role of acetylcholine in attention or for arousal states in general. This work was supported by: NSF Graduate Research Fellowship Program under Grant No. DGE 1256260 (JPR), NSF CMMI 1029388 (MRZ) and NSF PoLS 1058034 (MRZ & LMS).
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Wensheng Guo
Full Text Available In biological systems, the dynamic analysis method has gained increasing attention in the past decade. The Boolean network is the most common model of a genetic regulatory network. The interactions of activation and inhibition in the genetic regulatory network are modeled as a set of functions of the Boolean network, while the state transitions in the Boolean network reflect the dynamic property of a genetic regulatory network. A difficult problem for state transition analysis is the finding of attractors. In this paper, we modeled the genetic regulatory network as a Boolean network and proposed a solving algorithm to tackle the attractor finding problem. In the proposed algorithm, we partitioned the Boolean network into several blocks consisting of the strongly connected components according to their gradients, and defined the connection between blocks as decision node. Based on the solutions calculated on the decision nodes and using a satisfiability solving algorithm, we identified the attractors in the state transition graph of each block. The proposed algorithm is benchmarked on a variety of genetic regulatory networks. Compared with existing algorithms, it achieved similar performance on small test cases, and outperformed it on larger and more complex ones, which happens to be the trend of the modern genetic regulatory network. Furthermore, while the existing satisfiability-based algorithms cannot be parallelized due to their inherent algorithm design, the proposed algorithm exhibits a good scalability on parallel computing architectures.
Bistable Chimera Attractors on a Triangular Network of Oscillator Populations
DEFF Research Database (Denmark)
Martens, Erik Andreas
2010-01-01
. This triangular network is the simplest discretization of a continuous ring of oscillators. Yet it displays an unexpectedly different behavior: in contrast to the lone stable chimera observed in continuous rings of oscillators, we find that this system exhibits two coexisting stable chimeras. Both chimeras are......, as usual, born through a saddle-node bifurcation. As the coupling becomes increasingly local in nature they lose stability through a Hopf bifurcation, giving rise to breathing chimeras, which in turn get destroyed through a homoclinic bifurcation. Remarkably, one of the chimeras reemerges by a reversal...
Robustness of unstable attractors in arbitrarily sized pulse-coupled networks with delay
Broer, Hendrik; Efstathiou, Konstantinos; Subramanian, Easwar
We consider arbitrarily large networks of pulse-coupled oscillators with non-zero delay where the coupling is given by the Mirollo-Strogatz function. We prove that such systems have unstable attractors (saddle periodic orbits whose stable set has non-empty interior) in an open parameter region for
Lerner, Itamar; Bentin, Shlomo; Shriki, Oren
2012-01-01
Localist models of spreading activation (SA) and models assuming distributed representations offer very different takes on semantic priming, a widely investigated paradigm in word recognition and semantic memory research. In this study, we implemented SA in an attractor neural network model with distributed representations and created a unified…
From Cellular Attractor Selection to Adaptive Signal Control for Traffic Networks.
Tian, Daxin; Zhou, Jianshan; Sheng, Zhengguo; Wang, Yunpeng; Ma, Jianming
2016-03-14
The management of varying traffic flows essentially depends on signal controls at intersections. However, design an optimal control that considers the dynamic nature of a traffic network and coordinates all intersections simultaneously in a centralized manner is computationally challenging. Inspired by the stable gene expressions of Escherichia coli in response to environmental changes, we explore the robustness and adaptability performance of signalized intersections by incorporating a biological mechanism in their control policies, specifically, the evolution of each intersection is induced by the dynamics governing an adaptive attractor selection in cells. We employ a mathematical model to capture such biological attractor selection and derive a generic, adaptive and distributed control algorithm which is capable of dynamically adapting signal operations for the entire dynamical traffic network. We show that the proposed scheme based on attractor selection can not only promote the balance of traffic loads on each link of the network but also allows the global network to accommodate dynamical traffic demands. Our work demonstrates the potential of bio-inspired intelligence emerging from cells and provides a deep understanding of adaptive attractor selection-based control formation that is useful to support the designs of adaptive optimization and control in other domains.
An Attractor-Based Complexity Measurement for Boolean Recurrent Neural Networks
Cabessa, Jérémie; Villa, Alessandro E. P.
2014-01-01
We provide a novel refined attractor-based complexity measurement for Boolean recurrent neural networks that represents an assessment of their computational power in terms of the significance of their attractor dynamics. This complexity measurement is achieved by first proving a computational equivalence between Boolean recurrent neural networks and some specific class of -automata, and then translating the most refined classification of -automata to the Boolean neural network context. As a result, a hierarchical classification of Boolean neural networks based on their attractive dynamics is obtained, thus providing a novel refined attractor-based complexity measurement for Boolean recurrent neural networks. These results provide new theoretical insights to the computational and dynamical capabilities of neural networks according to their attractive potentialities. An application of our findings is illustrated by the analysis of the dynamics of a simplified model of the basal ganglia-thalamocortical network simulated by a Boolean recurrent neural network. This example shows the significance of measuring network complexity, and how our results bear new founding elements for the understanding of the complexity of real brain circuits. PMID:24727866
Noise in attractor networks in the brain produced by graded firing rate representations.
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Tristan J Webb
Full Text Available Representations in the cortex are often distributed with graded firing rates in the neuronal populations. The firing rate probability distribution of each neuron to a set of stimuli is often exponential or gamma. In processes in the brain, such as decision-making, that are influenced by the noise produced by the close to random spike timings of each neuron for a given mean rate, the noise with this graded type of representation may be larger than with the binary firing rate distribution that is usually investigated. In integrate-and-fire simulations of an attractor decision-making network, we show that the noise is indeed greater for a given sparseness of the representation for graded, exponential, than for binary firing rate distributions. The greater noise was measured by faster escaping times from the spontaneous firing rate state when the decision cues are applied, and this corresponds to faster decision or reaction times. The greater noise was also evident as less stability of the spontaneous firing state before the decision cues are applied. The implication is that spiking-related noise will continue to be a factor that influences processes such as decision-making, signal detection, short-term memory, and memory recall even with the quite large networks found in the cerebral cortex. In these networks there are several thousand recurrent collateral synapses onto each neuron. The greater noise with graded firing rate distributions has the advantage that it can increase the speed of operation of cortical circuitry.
Detecting small attractors of large Boolean networks by function-reduction-based strategy.
Zheng, Qiben; Shen, Liangzhong; Shang, Xuequn; Liu, Wenbin
2016-04-01
Boolean networks (BNs) are widely used to model gene regulatory networks and to design therapeutic intervention strategies to affect the long-term behaviour of systems. A central aim of Boolean-network analysis is to find attractors that correspond to various cellular states, such as cell types or the stage of cell differentiation. This problem is NP-hard and various algorithms have been used to tackle it with considerable success. The idea is that a singleton attractor corresponds to n consistent subsequences in the truth table. To find these subsequences, the authors gradually reduce the entire truth table of Boolean functions by extending a partial gene activity profile (GAP). Not only does this process delete inconsistent subsequences in truth tables, it also directly determines values for some nodes not extended, which means it can abandon the partial GAPs that cannot lead to an attractor as early as possible. The results of simulation show that the proposed algorithm can detect small attractors with length p = 4 in BNs of up to 200 nodes with average indegree K = 2.
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Paul eMiller
2013-05-01
Full Text Available Randomly connected recurrent networks of excitatory groups of neurons can possess a multitude of attractor states. When the internal excitatory synapses of these networks are depressing, the attractor states can be destabilized with increasing input. This leads to an itinerancy, where with either repeated transient stimuli, or increasing duration of a single stimulus, the network activity advances through sequences of attractor states. We find that the resulting network state, which persists beyond stimulus offset, can encode the number of stimuli presented via a distributed representation of neural activity with non-monotonic tuning curves for most neurons. Increased duration of a single stimulus is encoded via different distributed representations, so unlike an integrator, the network distinguishes separate successive presentations of a short stimulus from a single presentation of a longer stimulus with equal total duration. Moreover, different amplitudes of stimulus cause new, distinct activity patterns, such that changes in stimulus number, duration and amplitude can be distinguished from each other. These properties of the network depend on dynamic depressing synapses, as they disappear if synapses are static. Thus short-term synaptic depression allows a network to store separately the different dynamic properties of a spatially constant stimulus.
Generation of n x m-scroll attractors in a two-port RCL network with hysteresis circuits
International Nuclear Information System (INIS)
Yu Simin; Tang, Wallace K.S.
2009-01-01
In this paper, the generation of n x m-scroll attractors based on a two-port network is presented. The two-port network is built according to the RCL circuit suggested in the conventional Chua's circuit. By appending hysteresis voltage controlled devices on this two-port network, n-scroll and n x m-scroll attractors can be duly obtained both in simulations and experiments.
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Mark Niedringhaus
Full Text Available Collective rhythmic dynamics from neurons is vital for cognitive functions such as memory formation but how neurons self-organize to produce such activity is not well understood. Attractor-based computational models have been successfully implemented as a theoretical framework for memory storage in networks of neurons. Additionally, activity-dependent modification of synaptic transmission is thought to be the physiological basis of learning and memory. The goal of this study is to demonstrate that using a pharmacological treatment that has been shown to increase synaptic strength within in vitro networks of hippocampal neurons follows the dynamical postulates theorized by attractor models. We use a grid of extracellular electrodes to study changes in network activity after this perturbation and show that there is a persistent increase in overall spiking and bursting activity after treatment. This increase in activity appears to recruit more "errant" spikes into bursts. Phase plots indicate a conserved activity pattern suggesting that a synaptic potentiation perturbation to the attractor leaves it unchanged. Lastly, we construct a computational model to demonstrate that these synaptic perturbations can account for the dynamical changes seen within the network.
Navigating cancer network attractors for tumor-specific therapy
DEFF Research Database (Denmark)
Creixell, Pau; Schoof, Erwin; Erler, Janine Terra
2012-01-01
understanding of the processes by which genetic lesions perturb these networks and lead to disease phenotypes. Network biology will help circumvent fundamental obstacles in cancer treatment, such as drug resistance and metastasis, empowering personalized and tumor-specific cancer therapies....
A cortical attractor network with Martinotti cells driven by facilitating synapses.
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Pradeep Krishnamurthy
Full Text Available The population of pyramidal cells significantly outnumbers the inhibitory interneurons in the neocortex, while at the same time the diversity of interneuron types is much more pronounced. One acknowledged key role of inhibition is to control the rate and patterning of pyramidal cell firing via negative feedback, but most likely the diversity of inhibitory pathways is matched by a corresponding diversity of functional roles. An important distinguishing feature of cortical interneurons is the variability of the short-term plasticity properties of synapses received from pyramidal cells. The Martinotti cell type has recently come under scrutiny due to the distinctly facilitating nature of the synapses they receive from pyramidal cells. This distinguishes these neurons from basket cells and other inhibitory interneurons typically targeted by depressing synapses. A key aspect of the work reported here has been to pinpoint the role of this variability. We first set out to reproduce quantitatively based on in vitro data the di-synaptic inhibitory microcircuit connecting two pyramidal cells via one or a few Martinotti cells. In a second step, we embedded this microcircuit in a previously developed attractor memory network model of neocortical layers 2/3. This model network demonstrated that basket cells with their characteristic depressing synapses are the first to discharge when the network enters an attractor state and that Martinotti cells respond with a delay, thereby shifting the excitation-inhibition balance and acting to terminate the attractor state. A parameter sensitivity analysis suggested that Martinotti cells might, in fact, play a dominant role in setting the attractor dwell time and thus cortical speed of processing, with cellular adaptation and synaptic depression having a less prominent role than previously thought.
Statistical mechanics of attractor neural network models with synaptic depression
International Nuclear Information System (INIS)
Igarashi, Yasuhiko; Oizumi, Masafumi; Otsubo, Yosuke; Nagata, Kenji; Okada, Masato
2009-01-01
Synaptic depression is known to control gain for presynaptic inputs. Since cortical neurons receive thousands of presynaptic inputs, and their outputs are fed into thousands of other neurons, the synaptic depression should influence macroscopic properties of neural networks. We employ simple neural network models to explore the macroscopic effects of synaptic depression. Systems with the synaptic depression cannot be analyzed due to asymmetry of connections with the conventional equilibrium statistical-mechanical approach. Thus, we first propose a microscopic dynamical mean field theory. Next, we derive macroscopic steady state equations and discuss the stabilities of steady states for various types of neural network models.
Counting and classifying attractors in high dimensional dynamical systems.
Bagley, R J; Glass, L
1996-12-07
Randomly connected Boolean networks have been used as mathematical models of neural, genetic, and immune systems. A key quantity of such networks is the number of basins of attraction in the state space. The number of basins of attraction changes as a function of the size of the network, its connectivity and its transition rules. In discrete networks, a simple count of the number of attractors does not reveal the combinatorial structure of the attractors. These points are illustrated in a reexamination of dynamics in a class of random Boolean networks considered previously by Kauffman. We also consider comparisons between dynamics in discrete networks and continuous analogues. A continuous analogue of a discrete network may have a different number of attractors for many different reasons. Some attractors in discrete networks may be associated with unstable dynamics, and several different attractors in a discrete network may be associated with a single attractor in the continuous case. Special problems in determining attractors in continuous systems arise when there is aperiodic dynamics associated with quasiperiodicity of deterministic chaos.
Storage capacity of attractor neural networks with depressing synapses
International Nuclear Information System (INIS)
Torres, Joaquin J.; Pantic, Lovorka; Kappen, Hilbert J.
2002-01-01
We compute the capacity of a binary neural network with dynamic depressing synapses to store and retrieve an infinite number of patterns. We use a biologically motivated model of synaptic depression and a standard mean-field approach. We find that at T=0 the critical storage capacity decreases with the degree of the depression. We confirm the validity of our main mean-field results with numerical simulations
Szalay, Kristóf Z; Nussinov, Ruth; Csermely, Peter
2014-06-01
Conformational barcodes tag functional sites of proteins and are decoded by interacting molecules transmitting the incoming signal. Conformational barcodes are modified by all co-occurring allosteric events induced by post-translational modifications, pathogen, drug binding, etc. We argue that fuzziness (plasticity) of conformational barcodes may be increased by disordered protein structures, by integrative plasticity of multi-phosphorylation events, by increased intracellular water content (decreased molecular crowding) and by increased action of molecular chaperones. This leads to increased plasticity of signaling and cellular networks. Increased plasticity is both substantiated by and inducing an increased noise level. Using the versatile network dynamics tool, Turbine (www.turbine.linkgroup.hu), here we show that the 10 % noise level expected in cellular systems shifts a cancer-related signaling network of human cells from its proliferative attractors to its largest, apoptotic attractor representing their health-preserving response in the carcinogen containing and tumor suppressor deficient environment modeled in our study. Thus, fuzzy conformational barcodes may not only make the cellular system more plastic, and therefore more adaptable, but may also stabilize the complex system allowing better access to its largest attractor. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Effect of synapse dilution on the memory retrieval in structured attractor neural networks
Brunel, N.
1993-08-01
We investigate a simple model of structured attractor neural network (ANN). In this network a module codes for the category of the stored information, while another group of neurons codes for the remaining information. The probability distribution of stabilities of the patterns and the prototypes of the categories are calculated, for two different synaptic structures. The stability of the prototypes is shown to increase when the fraction of neurons coding for the category goes down. Then the effect of synapse destruction on the retrieval is studied in two opposite situations : first analytically in sparsely connected networks, then numerically in completely connected ones. In both cases the behaviour of the structured network and that of the usual homogeneous networks are compared. When lesions increase, two transitions are shown to appear in the behaviour of the structured network when one of the patterns is presented to the network. After the first transition the network recognizes the category of the pattern but not the individual pattern. After the second transition the network recognizes nothing. These effects are similar to syndromes caused by lesions in the central visual system, namely prosopagnosia and agnosia. In both types of networks (structured or homogeneous) the stability of the prototype is greater than the stability of individual patterns, however the first transition, for completely connected networks, occurs only when the network is structured.
Linear-control-based synchronization of coexisting attractor networks with time delays
International Nuclear Information System (INIS)
Yun-Zhong, Song
2010-01-01
This paper introduces the concept of linear-control-based synchronization of coexisting attractor networks with time delays. Within the new framework, closed loop control for each dynamic node is realized through linear state feedback around its own arena in a decentralized way, where the feedback matrix is determined through consideration of the coordination of the node dynamics, the inner connected matrix and the outer connected matrix. Unlike previously existing results, the feedback gain matrix here is decoupled from the inner matrix; this not only guarantees the flexible choice of the gain matrix, but also leaves much space for inner matrix configuration. Synchronization of coexisting attractor networks with time delays is made possible in virtue of local interaction, which works in a distributed way between individual neighbours, and the linear feedback control for each node. Provided that the network is connected and balanced, synchronization will come true naturally, where theoretical proof is given via a Lyapunov function. For completeness, several illustrative examples are presented to further elucidate the novelty and efficacy of the proposed scheme. (general)
Local community detection as pattern restoration by attractor dynamics of recurrent neural networks.
Okamoto, Hiroshi
2016-08-01
Densely connected parts in networks are referred to as "communities". Community structure is a hallmark of a variety of real-world networks. Individual communities in networks form functional modules of complex systems described by networks. Therefore, finding communities in networks is essential to approaching and understanding complex systems described by networks. In fact, network science has made a great deal of effort to develop effective and efficient methods for detecting communities in networks. Here we put forward a type of community detection, which has been little examined so far but will be practically useful. Suppose that we are given a set of source nodes that includes some (but not all) of "true" members of a particular community; suppose also that the set includes some nodes that are not the members of this community (i.e., "false" members of the community). We propose to detect the community from this "imperfect" and "inaccurate" set of source nodes using attractor dynamics of recurrent neural networks. Community detection by the proposed method can be viewed as restoration of the original pattern from a deteriorated pattern, which is analogous to cue-triggered recall of short-term memory in the brain. We demonstrate the effectiveness of the proposed method using synthetic networks and real social networks for which correct communities are known. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.
Benusková, L; Estok, S
1998-11-01
We propose an attractor neural network (ANN) model that performs rotation-invariant pattern recognition in such a way that it can account for a neural mechanism being involved in the image transformation accompanying the experience of mental rotation. We compared the performance of our ANN model with the results of the chronometric psychophysical experiments of Cooper and Shepard (Cooper L A and Shepard R N 1973 Visual Information Processing (New York: Academic) pp 204-7) on discrimination of alphanumeric characters presented in various angular departures from their canonical upright position. Comparing the times required for pattern retrieval in its canonical upright position with the reaction times of human subjects, we found agreement in that (i) retrieval times for clockwise and anticlockwise departures of the same angular magnitude (up to 180 degrees) were not different, (ii) retrieval times increased with departure from upright and (iii) increased more sharply as departure from upright approached 180 degrees. The rotation-invariant retrieval of the activity pattern has been accomplished by means of the modified algorithm of Dotsenko (Dotsenko V S 1988 J. Phys. A: Math. Gen. 21 L783-7) proposed for translation-, rotation- and size-invariant pattern recognition, which uses relaxation of neuronal firing thresholds to guide the evolution of the ANN in state space towards the desired memory attractor. The dynamics of neuronal relaxation has been modified for storage and retrieval of low-activity patterns and the original gradient optimization of threshold dynamics has been replaced with optimization by simulated annealing.
Unraveling chaotic attractors by complex networks and measurements of stock market complexity.
Cao, Hongduo; Li, Ying
2014-03-01
We present a novel method for measuring the complexity of a time series by unraveling a chaotic attractor modeled on complex networks. The complexity index R, which can potentially be exploited for prediction, has a similar meaning to the Kolmogorov complexity (calculated from the Lempel-Ziv complexity), and is an appropriate measure of a series' complexity. The proposed method is used to research the complexity of the world's major capital markets. None of these markets are completely random, and they have different degrees of complexity, both over the entire length of their time series and at a level of detail. However, developing markets differ significantly from mature markets. Specifically, the complexity of mature stock markets is stronger and more stable over time, whereas developing markets exhibit relatively low and unstable complexity over certain time periods, implying a stronger long-term price memory process.
Unraveling chaotic attractors by complex networks and measurements of stock market complexity
International Nuclear Information System (INIS)
Cao, Hongduo; Li, Ying
2014-01-01
We present a novel method for measuring the complexity of a time series by unraveling a chaotic attractor modeled on complex networks. The complexity index R, which can potentially be exploited for prediction, has a similar meaning to the Kolmogorov complexity (calculated from the Lempel–Ziv complexity), and is an appropriate measure of a series' complexity. The proposed method is used to research the complexity of the world's major capital markets. None of these markets are completely random, and they have different degrees of complexity, both over the entire length of their time series and at a level of detail. However, developing markets differ significantly from mature markets. Specifically, the complexity of mature stock markets is stronger and more stable over time, whereas developing markets exhibit relatively low and unstable complexity over certain time periods, implying a stronger long-term price memory process
Directory of Open Access Journals (Sweden)
Laura Dempere-Marco
Full Text Available The study of working memory capacity is of outmost importance in cognitive psychology as working memory is at the basis of general cognitive function. Although the working memory capacity limit has been thoroughly studied, its origin still remains a matter of strong debate. Only recently has the role of visual saliency in modulating working memory storage capacity been assessed experimentally and proved to provide valuable insights into working memory function. In the computational arena, attractor networks have successfully accounted for psychophysical and neurophysiological data in numerous working memory tasks given their ability to produce a sustained elevated firing rate during a delay period. Here we investigate the mechanisms underlying working memory capacity by means of a biophysically-realistic attractor network with spiking neurons while accounting for two recent experimental observations: 1 the presence of a visually salient item reduces the number of items that can be held in working memory, and 2 visually salient items are commonly kept in memory at the cost of not keeping as many non-salient items. Our model suggests that working memory capacity is determined by two fundamental processes: encoding of visual items into working memory and maintenance of the encoded items upon their removal from the visual display. While maintenance critically depends on the constraints that lateral inhibition imposes to the mnemonic activity, encoding is limited by the ability of the stimulated neural assemblies to reach a sufficiently high level of excitation, a process governed by the dynamics of competition and cooperation among neuronal pools. Encoding is therefore contingent upon the visual working memory task and has led us to introduce the concept of effective working memory capacity (eWMC in contrast to the maximal upper capacity limit only reached under ideal conditions.
Dempere-Marco, Laura; Melcher, David P; Deco, Gustavo
2012-01-01
The study of working memory capacity is of outmost importance in cognitive psychology as working memory is at the basis of general cognitive function. Although the working memory capacity limit has been thoroughly studied, its origin still remains a matter of strong debate. Only recently has the role of visual saliency in modulating working memory storage capacity been assessed experimentally and proved to provide valuable insights into working memory function. In the computational arena, attractor networks have successfully accounted for psychophysical and neurophysiological data in numerous working memory tasks given their ability to produce a sustained elevated firing rate during a delay period. Here we investigate the mechanisms underlying working memory capacity by means of a biophysically-realistic attractor network with spiking neurons while accounting for two recent experimental observations: 1) the presence of a visually salient item reduces the number of items that can be held in working memory, and 2) visually salient items are commonly kept in memory at the cost of not keeping as many non-salient items. Our model suggests that working memory capacity is determined by two fundamental processes: encoding of visual items into working memory and maintenance of the encoded items upon their removal from the visual display. While maintenance critically depends on the constraints that lateral inhibition imposes to the mnemonic activity, encoding is limited by the ability of the stimulated neural assemblies to reach a sufficiently high level of excitation, a process governed by the dynamics of competition and cooperation among neuronal pools. Encoding is therefore contingent upon the visual working memory task and has led us to introduce the concept of effective working memory capacity (eWMC) in contrast to the maximal upper capacity limit only reached under ideal conditions.
Dempere-Marco, Laura; Melcher, David P.; Deco, Gustavo
2012-01-01
The study of working memory capacity is of outmost importance in cognitive psychology as working memory is at the basis of general cognitive function. Although the working memory capacity limit has been thoroughly studied, its origin still remains a matter of strong debate. Only recently has the role of visual saliency in modulating working memory storage capacity been assessed experimentally and proved to provide valuable insights into working memory function. In the computational arena, attractor networks have successfully accounted for psychophysical and neurophysiological data in numerous working memory tasks given their ability to produce a sustained elevated firing rate during a delay period. Here we investigate the mechanisms underlying working memory capacity by means of a biophysically-realistic attractor network with spiking neurons while accounting for two recent experimental observations: 1) the presence of a visually salient item reduces the number of items that can be held in working memory, and 2) visually salient items are commonly kept in memory at the cost of not keeping as many non-salient items. Our model suggests that working memory capacity is determined by two fundamental processes: encoding of visual items into working memory and maintenance of the encoded items upon their removal from the visual display. While maintenance critically depends on the constraints that lateral inhibition imposes to the mnemonic activity, encoding is limited by the ability of the stimulated neural assemblies to reach a sufficiently high level of excitation, a process governed by the dynamics of competition and cooperation among neuronal pools. Encoding is therefore contingent upon the visual working memory task and has led us to introduce the concept of effective working memory capacity (eWMC) in contrast to the maximal upper capacity limit only reached under ideal conditions. PMID:22952608
Solanka, Lukas; van Rossum, Mark CW; Nolan, Matthew F
2015-01-01
Neural computations underlying cognitive functions require calibration of the strength of excitatory and inhibitory synaptic connections and are associated with modulation of gamma frequency oscillations in network activity. However, principles relating gamma oscillations, synaptic strength and circuit computations are unclear. We address this in attractor network models that account for grid firing and theta-nested gamma oscillations in the medial entorhinal cortex. We show that moderate intrinsic noise massively increases the range of synaptic strengths supporting gamma oscillations and grid computation. With moderate noise, variation in excitatory or inhibitory synaptic strength tunes the amplitude and frequency of gamma activity without disrupting grid firing. This beneficial role for noise results from disruption of epileptic-like network states. Thus, moderate noise promotes independent control of multiplexed firing rate- and gamma-based computational mechanisms. Our results have implications for tuning of normal circuit function and for disorders associated with changes in gamma oscillations and synaptic strength. DOI: http://dx.doi.org/10.7554/eLife.06444.001 PMID:26146940
Khodabakhshi, Mohammad Bagher; Moradi, Mohammad Hassan
2017-05-01
The respiratory system dynamic is of high significance when it comes to the detection of lung abnormalities, which highlights the importance of presenting a reliable model for it. In this paper, we introduce a novel dynamic modelling method for the characterization of the lung sounds (LS), based on the attractor recurrent neural network (ARNN). The ARNN structure allows the development of an effective LS model. Additionally, it has the capability to reproduce the distinctive features of the lung sounds using its formed attractors. Furthermore, a novel ARNN topology based on fuzzy functions (FFs-ARNN) is developed. Given the utility of the recurrent quantification analysis (RQA) as a tool to assess the nature of complex systems, it was used to evaluate the performance of both the ARNN and the FFs-ARNN models. The experimental results demonstrate the effectiveness of the proposed approaches for multichannel LS analysis. In particular, a classification accuracy of 91% was achieved using FFs-ARNN with sequences of RQA features. Copyright © 2017 Elsevier Ltd. All rights reserved.
Heteroclinic cycles between unstable attractors
International Nuclear Information System (INIS)
Broer, Henk; Efstathiou, Konstantinos; Subramanian, Easwar
2008-01-01
We consider networks of pulse coupled linear oscillators with non-zero delay where the coupling between the oscillators is given by the Mirollo–Strogatz function. We prove the existence of heteroclinic cycles between unstable attractors for a network of four oscillators and for an open set of parameter values
Heteroclinic cycles between unstable attractors
Broer, Henk; Efstathiou, Konstantinos; Subramanian, Easwar
We consider networks of pulse coupled linear oscillators with non-zero delay where the coupling between the oscillators is given by the Mirollo-Strogatz function. We prove the existence of heteroclinic cycles between unstable attractors for a network of four oscillators and for an open set of
Reactivation in working memory: an attractor network model of free recall.
Lansner, Anders; Marklund, Petter; Sikström, Sverker; Nilsson, Lars-Göran
2013-01-01
The dynamic nature of human working memory, the general-purpose system for processing continuous input, while keeping no longer externally available information active in the background, is well captured in immediate free recall of supraspan word-lists. Free recall tasks produce several benchmark memory phenomena, like the U-shaped serial position curve, reflecting enhanced memory for early and late list items. To account for empirical data, including primacy and recency as well as contiguity effects, we propose here a neurobiologically based neural network model that unifies short- and long-term forms of memory and challenges both the standard view of working memory as persistent activity and dual-store accounts of free recall. Rapidly expressed and volatile synaptic plasticity, modulated intrinsic excitability, and spike-frequency adaptation are suggested as key cellular mechanisms underlying working memory encoding, reactivation and recall. Recent findings on the synaptic and molecular mechanisms behind early LTP and on spiking activity during delayed-match-to-sample tasks support this view.
Reactivation in working memory: an attractor network model of free recall.
Directory of Open Access Journals (Sweden)
Anders Lansner
Full Text Available The dynamic nature of human working memory, the general-purpose system for processing continuous input, while keeping no longer externally available information active in the background, is well captured in immediate free recall of supraspan word-lists. Free recall tasks produce several benchmark memory phenomena, like the U-shaped serial position curve, reflecting enhanced memory for early and late list items. To account for empirical data, including primacy and recency as well as contiguity effects, we propose here a neurobiologically based neural network model that unifies short- and long-term forms of memory and challenges both the standard view of working memory as persistent activity and dual-store accounts of free recall. Rapidly expressed and volatile synaptic plasticity, modulated intrinsic excitability, and spike-frequency adaptation are suggested as key cellular mechanisms underlying working memory encoding, reactivation and recall. Recent findings on the synaptic and molecular mechanisms behind early LTP and on spiking activity during delayed-match-to-sample tasks support this view.
Reactivation in Working Memory: An Attractor Network Model of Free Recall
Lansner, Anders; Marklund, Petter; Sikström, Sverker; Nilsson, Lars-Göran
2013-01-01
The dynamic nature of human working memory, the general-purpose system for processing continuous input, while keeping no longer externally available information active in the background, is well captured in immediate free recall of supraspan word-lists. Free recall tasks produce several benchmark memory phenomena, like the U-shaped serial position curve, reflecting enhanced memory for early and late list items. To account for empirical data, including primacy and recency as well as contiguity effects, we propose here a neurobiologically based neural network model that unifies short- and long-term forms of memory and challenges both the standard view of working memory as persistent activity and dual-store accounts of free recall. Rapidly expressed and volatile synaptic plasticity, modulated intrinsic excitability, and spike-frequency adaptation are suggested as key cellular mechanisms underlying working memory encoding, reactivation and recall. Recent findings on the synaptic and molecular mechanisms behind early LTP and on spiking activity during delayed-match-to-sample tasks support this view. PMID:24023690
Modelling and prediction for chaotic fir laser attractor using rational function neural network.
Cho, S
2001-02-01
Many real-world systems such as irregular ECG signal, volatility of currency exchange rate and heated fluid reaction exhibit highly complex nonlinear characteristic known as chaos. These chaotic systems cannot be retreated satisfactorily using linear system theory due to its high dimensionality and irregularity. This research focuses on prediction and modelling of chaotic FIR (Far InfraRed) laser system for which the underlying equations are not given. This paper proposed a method for prediction and modelling a chaotic FIR laser time series using rational function neural network. Three network architectures, TDNN (Time Delayed Neural Network), RBF (radial basis function) network and the RF (rational function) network, are also presented. Comparisons between these networks performance show the improvements introduced by the RF network in terms of a decrement in network complexity and better ability of predictability.
Neiman, Tal; Loewenstein, Yonatan
2013-01-23
In free operant experiments, subjects alternate at will between targets that yield rewards stochastically. Behavior in these experiments is typically characterized by (1) an exponential distribution of stay durations, (2) matching of the relative time spent at a target to its relative share of the total number of rewards, and (3) adaptation after a change in the reward rates that can be very fast. The neural mechanism underlying these regularities is largely unknown. Moreover, current decision-making neural network models typically aim at explaining behavior in discrete-time experiments in which a single decision is made once in every trial, making these models hard to extend to the more natural case of free operant decisions. Here we show that a model based on attractor dynamics, in which transitions are induced by noise and preference is formed via covariance-based synaptic plasticity, can account for the characteristics of behavior in free operant experiments. We compare a specific instance of such a model, in which two recurrently excited populations of neurons compete for higher activity, to the behavior of rats responding on two levers for rewarding brain stimulation on a concurrent variable interval reward schedule (Gallistel et al., 2001). We show that the model is consistent with the rats' behavior, and in particular, with the observed fast adaptation to matching behavior. Further, we show that the neural model can be reduced to a behavioral model, and we use this model to deduce a novel "conservation law," which is consistent with the behavior of the rats.
New BFA Method Based on Attractor Neural Network and Likelihood Maximization
Czech Academy of Sciences Publication Activity Database
Frolov, A. A.; Húsek, Dušan; Polyakov, P.Y.; Snášel, V.
2014-01-01
Roč. 132, 20 May (2014), s. 14-29 ISSN 0925-2312 Grant - others:GA MŠk(CZ) ED1.1.00/02.0070; GA MŠk(CZ) EE.2.3.20.0073 Program:ED Institutional support: RVO:67985807 Keywords : recurrent neural network * associative memory * Hebbian learning rule * neural network application * data mining * statistics * Boolean factor analysis * information gain * dimension reduction * likelihood-maximization * bars problem Subject RIV: IN - Informatics, Computer Science Impact factor: 2.083, year: 2014
Attractor switching in neuron networks and Spatiotemporal filters for motion processing
Subramanian, Easwara Naga
2008-01-01
From a broader perspective, we address two important questions, viz., (a) what kind of mechanism would enable a neuronal network to switch between various tasks or stored patterns? (b) what are the properties of neurons that are used by the visual system in early motion detection? To address (a) we
Reactivation in Working Memory : An Attractor Network Model of Free Recall
Lansner, Anders; Marklund, Petter; Sikström, Sverker; Nilsson, Lars-Göran
2013-01-01
The dynamic nature of human working memory, the general-purpose system for processing continuous input, while keeping no longer externally available information active in the background, is well captured in immediate free recall of supraspan word-lists. Free recall tasks produce several benchmark memory phenomena, like the U-shaped serial position curve, reflecting enhanced memory for early and late list items. To account for empirical data, including primacy and recency as well as contiguity...
Imura, Jun-ichi; Ueta, Tetsushi
2015-01-01
This book is the first to report on theoretical breakthroughs on control of complex dynamical systems developed by collaborative researchers in the two fields of dynamical systems theory and control theory. As well, its basic point of view is of three kinds of complexity: bifurcation phenomena subject to model uncertainty, complex behavior including periodic/quasi-periodic orbits as well as chaotic orbits, and network complexity emerging from dynamical interactions between subsystems. Analysis and Control of Complex Dynamical Systems offers a valuable resource for mathematicians, physicists, and biophysicists, as well as for researchers in nonlinear science and control engineering, allowing them to develop a better fundamental understanding of the analysis and control synthesis of such complex systems.
Cortical computations via transient attractors.
Directory of Open Access Journals (Sweden)
Oliver L C Rourke
Full Text Available The ability of sensory networks to transiently store information on the scale of seconds can confer many advantages in processing time-varying stimuli. How a network could store information on such intermediate time scales, between typical neurophysiological time scales and those of long-term memory, is typically attributed to persistent neural activity. An alternative mechanism which might allow for such information storage is through temporary modifications to the neural connectivity which decay on the same second-long time scale as the underlying memories. Earlier work that has explored this method has done so by emphasizing one attractor from a limited, pre-defined set. Here, we describe an alternative, a Transient Attractor network, which can learn any pattern presented to it, store several simultaneously, and robustly recall them on demand using targeted probes in a manner reminiscent of Hopfield networks. We hypothesize that such functionality could be usefully embedded within sensory cortex, and allow for a flexibly-gated short-term memory, as well as conferring the ability of the network to perform automatic de-noising, and separation of input signals into distinct perceptual objects. We demonstrate that the stored information can be refreshed to extend storage time, is not sensitive to noise in the system, and can be turned on or off by simple neuromodulation. The diverse capabilities of transient attractors, as well as their resemblance to many features observed in sensory cortex, suggest the possibility that their actions might underlie neural processing in many sensory areas.
Cortical computations via transient attractors.
Rourke, Oliver L C; Butts, Daniel A
2017-01-01
The ability of sensory networks to transiently store information on the scale of seconds can confer many advantages in processing time-varying stimuli. How a network could store information on such intermediate time scales, between typical neurophysiological time scales and those of long-term memory, is typically attributed to persistent neural activity. An alternative mechanism which might allow for such information storage is through temporary modifications to the neural connectivity which decay on the same second-long time scale as the underlying memories. Earlier work that has explored this method has done so by emphasizing one attractor from a limited, pre-defined set. Here, we describe an alternative, a Transient Attractor network, which can learn any pattern presented to it, store several simultaneously, and robustly recall them on demand using targeted probes in a manner reminiscent of Hopfield networks. We hypothesize that such functionality could be usefully embedded within sensory cortex, and allow for a flexibly-gated short-term memory, as well as conferring the ability of the network to perform automatic de-noising, and separation of input signals into distinct perceptual objects. We demonstrate that the stored information can be refreshed to extend storage time, is not sensitive to noise in the system, and can be turned on or off by simple neuromodulation. The diverse capabilities of transient attractors, as well as their resemblance to many features observed in sensory cortex, suggest the possibility that their actions might underlie neural processing in many sensory areas.
A signature of attractor dynamics in the CA3 region of the hippocampus.
Directory of Open Access Journals (Sweden)
César Rennó-Costa
2014-05-01
Full Text Available The notion of attractor networks is the leading hypothesis for how associative memories are stored and recalled. A defining anatomical feature of such networks is excitatory recurrent connections. These "attract" the firing pattern of the network to a stored pattern, even when the external input is incomplete (pattern completion. The CA3 region of the hippocampus has been postulated to be such an attractor network; however, the experimental evidence has been ambiguous, leading to the suggestion that CA3 is not an attractor network. In order to resolve this controversy and to better understand how CA3 functions, we simulated CA3 and its input structures. In our simulation, we could reproduce critical experimental results and establish the criteria for identifying attractor properties. Notably, under conditions in which there is continuous input, the output should be "attracted" to a stored pattern. However, contrary to previous expectations, as a pattern is gradually "morphed" from one stored pattern to another, a sharp transition between output patterns is not expected. The observed firing patterns of CA3 meet these criteria and can be quantitatively accounted for by our model. Notably, as morphing proceeds, the activity pattern in the dentate gyrus changes; in contrast, the activity pattern in the downstream CA3 network is attracted to a stored pattern and thus undergoes little change. We furthermore show that other aspects of the observed firing patterns can be explained by learning that occurs during behavioral testing. The CA3 thus displays both the learning and recall signatures of an attractor network. These observations, taken together with existing anatomical and behavioral evidence, make the strong case that CA3 constructs associative memories based on attractor dynamics.
Cusps enable line attractors for neural computation
International Nuclear Information System (INIS)
Xiao, Zhuocheng; Zhang, Jiwei; Sornborger, Andrew T.; Tao, Louis
2017-01-01
Here, line attractors in neuronal networks have been suggested to be the basis of many brain functions, such as working memory, oculomotor control, head movement, locomotion, and sensory processing. In this paper, we make the connection between line attractors and pulse gating in feed-forward neuronal networks. In this context, because of their neutral stability along a one-dimensional manifold, line attractors are associated with a time-translational invariance that allows graded information to be propagated from one neuronal population to the next. To understand how pulse-gating manifests itself in a high-dimensional, nonlinear, feedforward integrate-and-fire network, we use a Fokker-Planck approach to analyze system dynamics. We make a connection between pulse-gated propagation in the Fokker-Planck and population-averaged mean-field (firing rate) models, and then identify an approximate line attractor in state space as the essential structure underlying graded information propagation. An analysis of the line attractor shows that it consists of three fixed points: a central saddle with an unstable manifold along the line and stable manifolds orthogonal to the line, which is surrounded on either side by stable fixed points. Along the manifold defined by the fixed points, slow dynamics give rise to a ghost. We show that this line attractor arises at a cusp catastrophe, where a fold bifurcation develops as a function of synaptic noise; and that the ghost dynamics near the fold of the cusp underly the robustness of the line attractor. Understanding the dynamical aspects of this cusp catastrophe allows us to show how line attractors can persist in biologically realistic neuronal networks and how the interplay of pulse gating, synaptic coupling, and neuronal stochasticity can be used to enable attracting one-dimensional manifolds and, thus, dynamically control the processing of graded information.
Cusps enable line attractors for neural computation
Xiao, Zhuocheng; Zhang, Jiwei; Sornborger, Andrew T.; Tao, Louis
2017-11-01
Line attractors in neuronal networks have been suggested to be the basis of many brain functions, such as working memory, oculomotor control, head movement, locomotion, and sensory processing. In this paper, we make the connection between line attractors and pulse gating in feed-forward neuronal networks. In this context, because of their neutral stability along a one-dimensional manifold, line attractors are associated with a time-translational invariance that allows graded information to be propagated from one neuronal population to the next. To understand how pulse-gating manifests itself in a high-dimensional, nonlinear, feedforward integrate-and-fire network, we use a Fokker-Planck approach to analyze system dynamics. We make a connection between pulse-gated propagation in the Fokker-Planck and population-averaged mean-field (firing rate) models, and then identify an approximate line attractor in state space as the essential structure underlying graded information propagation. An analysis of the line attractor shows that it consists of three fixed points: a central saddle with an unstable manifold along the line and stable manifolds orthogonal to the line, which is surrounded on either side by stable fixed points. Along the manifold defined by the fixed points, slow dynamics give rise to a ghost. We show that this line attractor arises at a cusp catastrophe, where a fold bifurcation develops as a function of synaptic noise; and that the ghost dynamics near the fold of the cusp underly the robustness of the line attractor. Understanding the dynamical aspects of this cusp catastrophe allows us to show how line attractors can persist in biologically realistic neuronal networks and how the interplay of pulse gating, synaptic coupling, and neuronal stochasticity can be used to enable attracting one-dimensional manifolds and, thus, dynamically control the processing of graded information.
Training trajectories by continuous recurrent multilayer networks.
Leistritz, L; Galicki, M; Witte, H; Kochs, E
2002-01-01
This paper addresses the problem of training trajectories by means of continuous recurrent neural networks whose feedforward parts are multilayer perceptrons. Such networks can approximate a general nonlinear dynamic system with arbitrary accuracy. The learning process is transformed into an optimal control framework where the weights are the controls to be determined. A training algorithm based upon a variational formulation of Pontryagin's maximum principle is proposed for such networks. Computer examples demonstrating the efficiency of the given approach are also presented.
Localization of hidden Chua's attractors
International Nuclear Information System (INIS)
Leonov, G.A.; Kuznetsov, N.V.; Vagaitsev, V.I.
2011-01-01
The classical attractors of Lorenz, Rossler, Chua, Chen, and other widely-known attractors are those excited from unstable equilibria. From computational point of view this allows one to use numerical method, in which after transient process a trajectory, started from a point of unstable manifold in the neighborhood of equilibrium, reaches an attractor and identifies it. However there are attractors of another type: hidden attractors, a basin of attraction of which does not contain neighborhoods of equilibria. In the present Letter for localization of hidden attractors of Chua's circuit it is suggested to use a special analytical-numerical algorithm. -- Highlights: → There are hidden attractors: basin doesn't contain neighborhoods of equilibria. → Hidden attractors cannot be reached by trajectory from neighborhoods of equilibria. → We suggested special procedure for localization of hidden attractors. → We discovered hidden attractor in Chua's system, L. Chua in his work didn't expect this.
Management continuity in local health networks
Directory of Open Access Journals (Sweden)
Mylaine Breton
2012-04-01
Full Text Available Introduction: Patients increasingly receive care from multiple providers in a variety of settings. They expect management continuity that crosses boundaries and bridges gaps in the healthcare system. To our knowledge, little research has been done to assess coordination across organizational and professional boundaries from the patients' perspective. Our objective was to assess whether greater local health network integration is associated with management continuity as perceived by patients. Method: We used the data from a research project on the development and validation of a generic and comprehensive continuity measurement instrument that can be applied to a variety of patient conditions and settings. We used the results of a cross-sectional survey conducted in 2009 with 256 patients in two local health networks in Quebec, Canada. We compared four aspects of management continuity between two contrasting network types (highly integrated vs. poorly integrated. Results: The scores obtained in the highly integrated network are better than those of the poorly integrated network on all dimensions of management continuity (coordinator role, role clarity and coordination between clinics, and information gaps between providers except for experience of care plan. Conclusion: Some aspects of care coordination among professionals and organizations are noticed by patients and may be valid indicators to assess care coordination.
Anisotropic nonequilibrium hydrodynamic attractor
Strickland, Michael; Noronha, Jorge; Denicol, Gabriel S.
2018-02-01
We determine the dynamical attractors associated with anisotropic hydrodynamics (aHydro) and the DNMR equations for a 0 +1 d conformal system using kinetic theory in the relaxation time approximation. We compare our results to the nonequilibrium attractor obtained from the exact solution of the 0 +1 d conformal Boltzmann equation, the Navier-Stokes theory, and the second-order Mueller-Israel-Stewart theory. We demonstrate that the aHydro attractor equation resums an infinite number of terms in the inverse Reynolds number. The resulting resummed aHydro attractor possesses a positive longitudinal-to-transverse pressure ratio and is virtually indistinguishable from the exact attractor. This suggests that an optimized hydrodynamic treatment of kinetic theory involves a resummation not only in gradients (Knudsen number) but also in the inverse Reynolds number. We also demonstrate that the DNMR result provides a better approximation of the exact kinetic theory attractor than the Mueller-Israel-Stewart theory. Finally, we introduce a new method for obtaining approximate aHydro equations which relies solely on an expansion in the inverse Reynolds number. We then carry this expansion out to the third order, and compare these third-order results to the exact kinetic theory solution.
Finite-time Lyapunov dimension and hidden attractor of the Rabinovich system
Kuznetsov, N. V.; Leonov, G. A.; Mokaev, T. N.; Prasad, A.; Shrimali, M. D.
2015-01-01
The Rabinovich system, describing the process of interaction between waves in plasma, is considered. It is shown that the Rabinovich system can exhibit a hidden attractor in the case of multistability as well as a classical self-excited attractor. The hidden attractor in this system can be localized by analytical/numerical methods based on the continuation and perpetual points. The concept of finite-time Lyapunov dimension is developed for numerical study of the dimension of attractors. A con...
Neural networks in continuous optical media
International Nuclear Information System (INIS)
Anderson, D.Z.
1987-01-01
The authors' interest is to see to what extent neural models can be implemented using continuous optical elements. Thus these optical networks represent a continuous distribution of neuronlike processors rather than a discrete collection. Most neural models have three characteristic features: interconnections; adaptivity; and nonlinearity. In their optical representation the interconnections are implemented with linear one- and two-port optical elements such as lenses and holograms. Real-time holographic media allow these interconnections to become adaptive. The nonlinearity is achieved with gain, for example, from two-beam coupling in photorefractive media or a pumped dye medium. Using these basic optical elements one can in principle construct continuous representations of a number of neural network models. The authors demonstrated two devices based on continuous optical elements: an associative memory which recalls an entire object when addressed with a partial object and a tracking novelty filter which identifies time-dependent features in an optical scene. These devices demonstrate the potential of distributed optical elements to implement more formal models of neural networks
Reliable dynamics in Boolean and continuous networks
International Nuclear Information System (INIS)
Ackermann, Eva; Drossel, Barbara; Peixoto, Tiago P
2012-01-01
We investigate the dynamical behavior of a model of robust gene regulatory networks which possess ‘entirely reliable’ trajectories. In a Boolean representation, these trajectories are characterized by being insensitive to the order in which the nodes are updated, i.e. they always go through the same sequence of states. The Boolean model for gene activity is compared with a continuous description in terms of differential equations for the concentrations of mRNA and proteins. We found that entirely reliable Boolean trajectories can be reproduced perfectly in the continuous model when realistic Hill coefficients are used. We investigate to what extent this high correspondence between Boolean and continuous trajectories depends on the extent of reliability of the Boolean trajectories, and we identify simple criteria that enable the faithful reproduction of the Boolean dynamics in the continuous description. (paper)
Horseshoes in modified Chen's attractors
International Nuclear Information System (INIS)
Huang Yan; Yang Xiaosong
2005-01-01
In this paper we study dynamics of a class of modified Chen's attractors, we show that these attractors are chaotic by giving a rigorous verification for existence of horseshoes in these systems. We prove that the Poincare maps derived from these modified Chen's attractors are semi-conjugate to the 2-shift map
Hidden attractors in dynamical systems
Dudkowski, Dawid; Jafari, Sajad; Kapitaniak, Tomasz; Kuznetsov, Nikolay V.; Leonov, Gennady A.; Prasad, Awadhesh
2016-06-01
Complex dynamical systems, ranging from the climate, ecosystems to financial markets and engineering applications typically have many coexisting attractors. This property of the system is called multistability. The final state, i.e., the attractor on which the multistable system evolves strongly depends on the initial conditions. Additionally, such systems are very sensitive towards noise and system parameters so a sudden shift to a contrasting regime may occur. To understand the dynamics of these systems one has to identify all possible attractors and their basins of attraction. Recently, it has been shown that multistability is connected with the occurrence of unpredictable attractors which have been called hidden attractors. The basins of attraction of the hidden attractors do not touch unstable fixed points (if exists) and are located far away from such points. Numerical localization of the hidden attractors is not straightforward since there are no transient processes leading to them from the neighborhoods of unstable fixed points and one has to use the special analytical-numerical procedures. From the viewpoint of applications, the identification of hidden attractors is the major issue. The knowledge about the emergence and properties of hidden attractors can increase the likelihood that the system will remain on the most desirable attractor and reduce the risk of the sudden jump to undesired behavior. We review the most representative examples of hidden attractors, discuss their theoretical properties and experimental observations. We also describe numerical methods which allow identification of the hidden attractors.
Continuous environmental radiation monitoring network at Kalpakkam
International Nuclear Information System (INIS)
Somayaji, K.M.; Mathiyarasu, R.; Prakash, G.S.; Meenakshisundaram, V.; Rajagopal, V.
1997-01-01
The report highlights our experience in the design and installation of monitoring stations as part of continuous environmental radiation monitoring network around the periphery of the nuclear complex at Kalpakkam. Five monitoring stations, one each in south-west sector (Main Gate I) and south-south west (Main Gate II) and the others in North sector (HASL and ESG) and in north-west section (WIP) have been set up. Two independent detector systems, based on high pressure ionisation chamber (HPIC) and energy compensated GM have been installed at each of these locations and the data has been logged continuously using a data logger. The data so gathered at each monitoring station is retrieved every week by means of a hand held terminal (HHT) with a built-in non-volatile memory and transferred to an IBM PC-AT for data analysis and archival. The report discusses in depth the design and developmental efforts undertaken to set up the network, starting from the basic detectors. The work involved the design of suitable electrometer circuits for measuring the low levels of current from HPICs, and the subsequent study of the performance of the highly sensitive preamplifier under diurnal variations of ambient conditions. The report includes, in detail the design aspects and fabrication details of low current measuring electrometer circuits
Czech Academy of Sciences Publication Activity Database
Frolov, A. A.; Húsek, Dušan; Muraviev, I. P.; Polyakov, P.Y.
2010-01-01
Roč. 73, č. 7-9 (2010), s. 1394-1404 ISSN 0925-2312 R&D Projects: GA ČR GA205/09/1079; GA MŠk(CZ) 1M0567 Institutional research plan: CEZ:AV0Z10300504 Keywords : Boolean factor analysis * Hopfield neural Network * unsupervised learning * dimension reduction * data mining Subject RIV: IN - Informatics, Computer Science Impact factor: 1.429, year: 2010
Attractors under discretisation
Han, Xiaoying
2017-01-01
This work focuses on the preservation of attractors and saddle points of ordinary differential equations under discretisation. In the 1980s, key results for autonomous ordinary differential equations were obtained – by Beyn for saddle points and by Kloeden & Lorenz for attractors. One-step numerical schemes with a constant step size were considered, so the resulting discrete time dynamical system was also autonomous. One of the aims of this book is to present new findings on the discretisation of dissipative nonautonomous dynamical systems that have been obtained in recent years, and in particular to examine the properties of nonautonomous omega limit sets and their approximations by numerical schemes – results that are also of importance for autonomous systems approximated by a numerical scheme with variable time steps, thus by a discrete time nonautonomous dynamical system.
Dimension of chaotic attractors
Energy Technology Data Exchange (ETDEWEB)
Farmer, J.D.; Ott, E.; Yorke, J.A.
1982-09-01
Dimension is perhaps the most basic property of an attractor. In this paper we discuss a variety of different definitions of dimension, compute their values for a typical example, and review previous work on the dimension of chaotic attractors. The relevant definitions of dimension are of two general types, those that depend only on metric properties, and those that depend on probabilistic properties (that is, they depend on the frequency with which a typical trajectory visits different regions of the attractor). Both our example and the previous work that we review support the conclusion that all of the probabilistic dimensions take on the same value, which we call the dimension of the natural measure, and all of the metric dimensions take on a common value, which we call the fractal dimension. Furthermore, the dimension of the natural measure is typically equal to the Lyapunov dimension, which is defined in terms of Lyapunov numbers, and thus is usually far easier to calculate than any other definition. Because it is computable and more physically relevant, we feel that the dimension of the natural measure is more important than the fractal dimension.
Multiple single-centered attractors
International Nuclear Information System (INIS)
Dominic, Pramod; Mandal, Taniya; Tripathy, Prasanta K.
2014-01-01
In this paper we study spherically symmetric single-centered attractors in N=2 supergravity in four dimensions. The attractor points are obtained by extremising the effective black hole potential in the moduli space. Both supersymmetric as well as non-supersymmetric attractors exist in mutually exclusive domains of the charge lattice. We construct axion free supersymmetric as well as non-supersymmetric multiple attractors in a simple two parameter model. We further obtain explicit examples of two distinct non-supersymmetric attractors in type IIA string theory compactified on K3×T"2 carrying D0−D4−D6 charges. We compute the entropy of these attractors and analyse their stability in detail.
Existence of a new three-dimensional chaotic attractor
International Nuclear Information System (INIS)
Wang Jiezhi; Chen Zengqiang; Yuan Zhuzhi
2009-01-01
In this paper, one heteroclinic orbit of a new three-dimensional continuous autonomous chaotic system, whose chaotic attractor belongs to the conjugate Lue attractor, is found. The series expression of the heteroclinic orbit of Shil'nikov type is derived by using the undetermined coefficient method. The uniform convergence of the precise series expansions of this heteroclinic orbits is proved. According to the Shil'nikov theorem, this system clearly has Smale horseshoes and the horseshoe chaos.
Attractors, universality, and inflation
Downes, Sean; Dutta, Bhaskar; Sinha, Kuver
2012-11-01
Studies of the initial conditions for inflation have conflicting predictions from exponential suppression to inevitability. At the level of phase space, this conflict arises from the competing intuitions of CPT invariance and thermodynamics. After reviewing this conflict, we enlarge the ensemble beyond phase space to include scalar potential data. We show how this leads to an important contribution from inflection point inflation, enhancing the likelihood of inflation to a power law, 1/Ne3. In the process, we emphasize the attractor dynamics of the gravity-scalar system and the existence of universality classes from inflection point inflation. Finally, we comment on the predictivity of inflation in light of these results.
Chaotic attractors with separated scrolls
International Nuclear Information System (INIS)
Bouallegue, Kais
2015-01-01
This paper proposes a new behavior of chaotic attractors with separated scrolls while combining Julia's process with Chua's attractor and Lorenz's attractor. The main motivation of this work is the ability to generate a set of separated scrolls with different behaviors, which in turn allows us to choose one or many scrolls combined with modulation (amplitude and frequency) for secure communication or synchronization. This set seems a new class of hyperchaos because each element of this set looks like a simple chaotic attractor with one positive Lyapunov exponent, so the cardinal of this set is greater than one. This new approach could be used to generate more general higher-dimensional hyperchaotic attractor for more potential application. Numerical simulations are given to show the effectiveness of the proposed theoretical results
Exploring continuous organisational transformation as a form of network interdependence
Stebbings, H; Braganza, A
2008-01-01
In this paper we examine the problematic area of continuous transformation. We conduct our analysis from three theoretical perspectives: the resource based view, social network theory, and stakeholder theory. We found that the continuous transformation can be explained through the concept of Network Interdependence. This paper describes Network Interdependence and develops theoretical propositions from a synthesis of the three theories. Our contribution of Network Interdependence offers f...
Directory of Open Access Journals (Sweden)
Botond Molnár
Full Text Available There has been a long history of using neural networks for combinatorial optimization and constraint satisfaction problems. Symmetric Hopfield networks and similar approaches use steepest descent dynamics, and they always converge to the closest local minimum of the energy landscape. For finding global minima additional parameter-sensitive techniques are used, such as classical simulated annealing or the so-called chaotic simulated annealing, which induces chaotic dynamics by addition of extra terms to the energy landscape. Here we show that asymmetric continuous-time neural networks can solve constraint satisfaction problems without getting trapped in non-solution attractors. We concentrate on a model solving Boolean satisfiability (k-SAT, which is a quintessential NP-complete problem. There is a one-to-one correspondence between the stable fixed points of the neural network and the k-SAT solutions and we present numerical evidence that limit cycles may also be avoided by appropriately choosing the parameters of the model. This optimal parameter region is fairly independent of the size and hardness of instances, this way parameters can be chosen independently of the properties of problems and no tuning is required during the dynamical process. The model is similar to cellular neural networks already used in CNN computers. On an analog device solving a SAT problem would take a single operation: the connection weights are determined by the k-SAT instance and starting from any initial condition the system searches until finding a solution. In this new approach transient chaotic behavior appears as a natural consequence of optimization hardness and not as an externally induced effect.
Attractor comparisons based on density
International Nuclear Information System (INIS)
Carroll, T. L.
2015-01-01
Recognizing a chaotic attractor can be seen as a problem in pattern recognition. Some feature vector must be extracted from the attractor and used to compare to other attractors. The field of machine learning has many methods for extracting feature vectors, including clustering methods, decision trees, support vector machines, and many others. In this work, feature vectors are created by representing the attractor as a density in phase space and creating polynomials based on this density. Density is useful in itself because it is a one dimensional function of phase space position, but representing an attractor as a density is also a way to reduce the size of a large data set before analyzing it with graph theory methods, which can be computationally intensive. The density computation in this paper is also fast to execute. In this paper, as a demonstration of the usefulness of density, the density is used directly to construct phase space polynomials for comparing attractors. Comparisons between attractors could be useful for tracking changes in an experiment when the underlying equations are too complicated for vector field modeling
Attractors for discrete periodic dynamical systems
John E. Franke; James F. Selgrade
2003-01-01
A mathematical framework is introduced to study attractors of discrete, nonautonomous dynamical systems which depend periodically on time. A structure theorem for such attractors is established which says that the attractor of a time-periodic dynamical system is the unin of attractors of appropriate autonomous maps. If the nonautonomous system is a perturbation of an...
When Darwin meets Lorenz: Evolving new chaotic attractors through genetic programming
International Nuclear Information System (INIS)
Pan, Indranil; Das, Saptarshi
2015-01-01
Highlights: •New 3D continuous time chaotic systems with analytical expressions are obtained. •The multi-gene genetic programming (MGGP) paradigm is employed to achieve this. •Extends earlier works for evolving generalised family of Lorenz attractors. •Over one hundred of new chaotic attractors along with their parameters are reported. •The MGGP method have the potential for finding other similar chaotic attractors. -- Abstract: In this paper, we propose a novel methodology for automatically finding new chaotic attractors through a computational intelligence technique known as multi-gene genetic programming (MGGP). We apply this technique to the case of the Lorenz attractor and evolve several new chaotic attractors based on the basic Lorenz template. The MGGP algorithm automatically finds new nonlinear expressions for the different state variables starting from the original Lorenz system. The Lyapunov exponents of each of the attractors are calculated numerically based on the time series of the state variables using time delay embedding techniques. The MGGP algorithm tries to search the functional space of the attractors by aiming to maximise the largest Lyapunov exponent (LLE) of the evolved attractors. To demonstrate the potential of the proposed methodology, we report over one hundred new chaotic attractor structures along with their parameters, which are evolved from just the Lorenz system alone
Low Cost Wireless Sensor Network for Continuous Bridge monitoring
DEFF Research Database (Denmark)
Han, Bo; Kalis, A; Tragas, P
2012-01-01
Continuous monitoring wireless sensor networks (WSN) are considered as one of the most promising means to harvest information from large structures in order to assist in structural health monitoring and management. At the same time, continuous monitoring WSNs suffer from limited network lifetimes...
Controlling Strange Attractor in Dynamics
Institute of Scientific and Technical Information of China (English)
无
2000-01-01
A nonlinear system which exhibits a strange attractor is considered, with the goal of illustrating how to control the chaotic dynamical system and to obtain a desired attracting periodic orbit by the OGY control algorithm.
Attractor behaviour in ELKO cosmology
International Nuclear Information System (INIS)
Basak, Abhishek; Bhatt, Jitesh R.; Shankaranarayanan, S.; Varma, K.V. Prasantha
2013-01-01
We study the dynamics of ELKO in the context of accelerated phase of our universe. To avoid the fine tuning problem associated with the initial conditions, it is required that the dynamical equations lead to an early-time attractor. In the earlier works, it was shown that the dynamical equations containing ELKO fields do not lead to early-time stable fixed points. In this work, using redefinition of variables, we show that ELKO cosmology admits early-time stable fixed points. More interestingly, we show that ELKO cosmology admit two sets of attractor points corresponding to slow and fast-roll inflation. The fast-roll inflation attractor point is unique for ELKO as it is independent of the form of the potential. We also discuss the plausible choice of interaction terms in these two sets of attractor points and constraints on the coupling constant
International Nuclear Information System (INIS)
Ferrara, S.; Kallosh, R.
1996-01-01
We find a general principle which allows one to compute the area of the horizon of N=2 extremal black holes as an extremum of the central charge. One considers the ADM mass equal to the central charge as a function of electric and magnetic charges and moduli and extremizes this function in the moduli space (a minimum corresponds to a fixed point of attraction). The extremal value of the square of the central charge provides the area of the horizon, which depends only on electric and magnetic charges. The doubling of unbroken supersymmetry at the fixed point of attraction for N=2 black holes near the horizon is derived via conformal flatness of the Bertotti-Robinson-type geometry. These results provide an explicit model-independent expression for the macroscopic Bekenstein-Hawking entropy of N=2 black holes which is manifestly duality invariant. The presence of hypermultiplets in the solution does not affect the area formula. Various examples of the general formula are displayed. We outline the attractor mechanism in N=4,8 supersymmetries and the relation to the N=2 case. The entropy-area formula in five dimensions, recently discussed in the literature, is also seen to be obtained by extremizing the 5d central charge. copyright 1996 The American Physical Society
Attractors of multivalued semiflows generated by differential inclusions and their approximations
Directory of Open Access Journals (Sweden)
Alexei V. Kapustian
2000-01-01
Full Text Available We prove the existence of global compact attractors for differential inclusions and obtain some results concerning the continuity and upper semicontinuity of the attractors for approximating and perturbed inclusions. Applications are given to a model of regional economic growth.
A novel one equilibrium hyper-chaotic system generated upon Lü attractor
International Nuclear Information System (INIS)
Hong-Yan, Jia; Zeng-Qiang, Chen; Zhu-Zhi, Yuan
2010-01-01
By introducing an additional state feedback into a three-dimensional autonomous chaotic attractor Lü system, this paper presents a novel four-dimensional continuous autonomous hyper-chaotic system which has only one equilibrium. There are only 8 terms in all four equations of the new hyper-chaotic system, which may be less than any other four-dimensional continuous autonomous hyper-chaotic systems generated by three-dimensional (3D) continuous autonomous chaotic systems. The hyper-chaotic system undergoes Hopf bifurcation when parameter c varies, and becomes the 3D modified Lü system when parameter k varies. Although the hyper-chaotic system does not undergo Hopf bifurcation when parameter k varies, many dynamic behaviours such as periodic attractor, quasi periodic attractor, chaotic attractor and hyper-chaotic attractor can be observed. A circuit is also designed when parameter k varies and the results of the circuit experiment are in good agreement with those of simulation. (general)
Cosmological attractors in massive gravity
Dubovsky, S; Tkachev, I I
2005-01-01
We study Lorentz-violating models of massive gravity which preserve rotations and are invariant under time-dependent shifts of the spatial coordinates. In the linear approximation the Newtonian potential in these models has an extra ``confining'' term proportional to the distance from the source. We argue that during cosmological expansion the Universe may be driven to an attractor point with larger symmetry which includes particular simultaneous dilatations of time and space coordinates. The confining term in the potential vanishes as one approaches the attractor. In the vicinity of the attractor the extra contribution is present in the Friedmann equation which, in a certain range of parameters, gives rise to the cosmic acceleration.
Moduli backreaction on inflationary attractors
International Nuclear Information System (INIS)
Roest, Diederik; Werkman, Pelle
2016-07-01
We investigate the interplay between moduli dynamics and inflation, focusing on the KKLT- scenario and cosmological α-attractors. General couplings between these sectors can induce a significant backreaction and potentially destroy the inflationary regime; however, we demonstrate that this generically does not happen for α-attractors. Depending on the details of the superpotential, the volume modulus can either be stable during the entire inflationary trajectory, or become tachyonic at some point and act as a waterfall field, resulting in a sudden end of inflation. In the latter case there is a universal supersymmetric minimum where the scalars end up, preventing the decompactification scenario. The gravitino mass is independent from the inflationary scale with no fine-tuning of the parameters. The observational predictions conform to the universal value of attractors, fully compatible with the Planck data, with possibly a capped number of e-folds due to the interplay with moduli.
Moduli Backreaction on Inflationary Attractors
Roest, Diederik; Werkman, Pelle
2016-01-01
We investigate the interplay between moduli dynamics and inflation, focusing on the KKLT-scenario and cosmological $\\alpha$-attractors. General couplings between these sectors can induce a significant backreaction and potentially destroy the inflationary regime; however, we demonstrate that this generically does not happen for $\\alpha$-attractors. Depending on the details of the superpotential, the volume modulus can either be stable during the entire inflationary trajectory, or become tachyonic at some point and act as a waterfall field, resulting in a sudden end of inflation. In the latter case there is a universal supersymmetric minimum where the scalars end up, preventing the decompactification scenario. The observational predictions conform to the universal value of attractors, fully compatible with the Planck data, with possibly a capped number of e-folds due to the interplay with moduli.
A continuous-time control model on production planning network ...
African Journals Online (AJOL)
A continuous-time control model on production planning network. DEA Omorogbe, MIU Okunsebor. Abstract. In this paper, we give a slightly detailed review of Graves and Hollywood model on constant inventory tactical planning model for a job shop. The limitations of this model are pointed out and a continuous time ...
General method to find the attractors of discrete dynamic models of biological systems
Gan, Xiao; Albert, Réka
2018-04-01
Analyzing the long-term behaviors (attractors) of dynamic models of biological networks can provide valuable insight. We propose a general method that can find the attractors of multilevel discrete dynamical systems by extending a method that finds the attractors of a Boolean network model. The previous method is based on finding stable motifs, subgraphs whose nodes' states can stabilize on their own. We extend the framework from binary states to any finite discrete levels by creating a virtual node for each level of a multilevel node, and describing each virtual node with a quasi-Boolean function. We then create an expanded representation of the multilevel network, find multilevel stable motifs and oscillating motifs, and identify attractors by successive network reduction. In this way, we find both fixed point attractors and complex attractors. We implemented an algorithm, which we test and validate on representative synthetic networks and on published multilevel models of biological networks. Despite its primary motivation to analyze biological networks, our motif-based method is general and can be applied to any finite discrete dynamical system.
General method to find the attractors of discrete dynamic models of biological systems.
Gan, Xiao; Albert, Réka
2018-04-01
Analyzing the long-term behaviors (attractors) of dynamic models of biological networks can provide valuable insight. We propose a general method that can find the attractors of multilevel discrete dynamical systems by extending a method that finds the attractors of a Boolean network model. The previous method is based on finding stable motifs, subgraphs whose nodes' states can stabilize on their own. We extend the framework from binary states to any finite discrete levels by creating a virtual node for each level of a multilevel node, and describing each virtual node with a quasi-Boolean function. We then create an expanded representation of the multilevel network, find multilevel stable motifs and oscillating motifs, and identify attractors by successive network reduction. In this way, we find both fixed point attractors and complex attractors. We implemented an algorithm, which we test and validate on representative synthetic networks and on published multilevel models of biological networks. Despite its primary motivation to analyze biological networks, our motif-based method is general and can be applied to any finite discrete dynamical system.
Phase-synchronisation in continuous flow models of production networks
Scholz-Reiter, Bernd; Tervo, Jan Topi; Freitag, Michael
2006-04-01
To improve their position at the market, many companies concentrate on their core competences and hence cooperate with suppliers and distributors. Thus, between many independent companies strong linkages develop and production and logistics networks emerge. These networks are characterised by permanently increasing complexity, and are nowadays forced to adapt to dynamically changing markets. This factor complicates an enterprise-spreading production planning and control enormously. Therefore, a continuous flow model for production networks will be derived regarding these special logistic problems. Furthermore, phase-synchronisation effects will be presented and their dependencies to the set of network parameters will be investigated.
Separation of attractors in 1-modulus quantum corrected special geometry
Bellucci, S; Marrani, A; Shcherbakov, A
2008-01-01
We study the solutions to the N=2, d=4 Attractor Equations in a dyonic, extremal, static, spherically symmetric and asymptotically flat black hole background, in the simplest case of perturbative quantum corrected cubic Special Kahler geometry consistent with continuous axion-shift symmetry, namely in the 1-modulus Special Kahler geometry described (in a suitable special symplectic coordinate) by the holomorphic Kahler gauge-invariant prepotential F=t^3+i*lambda, with lambda real. By performing computations in the ``magnetic'' charge configuration, we find evidence for interesting phenomena (absent in the classical limit of vanishing lambda). Namely, for a certain range of the quantum parameter lambda we find a ``splitting'' of attractors, i.e. the existence of multiple solutions to the Attractor Equations for fixed supporting charge configuration. This corresponds to the existence of ``area codes'' in the radial evolution of the scalar t, determined by the various disconnected regions of the moduli space, wh...
Hyperbolic geometry of cosmological attractors
Carrasco, John Joseph M.; Kallosh, Renata; Linde, Andrei; Roest, Diederik
2015-01-01
Cosmological alpha attractors give a natural explanation for the spectral index n(s) of inflation as measured by Planck while predicting a range for the tensor-to-scalar ratio r, consistent with all observations, to be measured more precisely in future B-mode experiments. We highlight the crucial
Generalized Attractor Points in Gauged Supergravity
Energy Technology Data Exchange (ETDEWEB)
Kachru, Shamit; /Stanford U., Phys. Dept. /SLAC; Kallosh, Renata; /Stanford U., Phys. Dept.; Shmakova, Marina; /KIPAC, Menlo Park /SLAC /Stanford U., Phys. Dept.
2011-08-15
The attractor mechanism governs the near-horizon geometry of extremal black holes in ungauged 4D N=2 supergravity theories and in Calabi-Yau compactifications of string theory. In this paper, we study a natural generalization of this mechanism to solutions of arbitrary 4D N=2 gauged supergravities. We define generalized attractor points as solutions of an ansatz which reduces the Einstein, gauge field, and scalar equations of motion to algebraic equations. The simplest generalized attractor geometries are characterized by non-vanishing constant anholonomy coefficients in an orthonormal frame. Basic examples include Lifshitz and Schroedinger solutions, as well as AdS and dS vacua. There is a generalized attractor potential whose critical points are the attractor points, and its extremization explains the algebraic nature of the equations governing both supersymmetric and non-supersymmetric attractors.
Continuous-time quantum walks on multilayer dendrimer networks
Galiceanu, Mircea; Strunz, Walter T.
2016-08-01
We consider continuous-time quantum walks (CTQWs) on multilayer dendrimer networks (MDs) and their application to quantum transport. A detailed study of properties of CTQWs is presented and transport efficiency is determined in terms of the exact and average return probabilities. The latter depends only on the eigenvalues of the connectivity matrix, which even for very large structures allows a complete analytical solution for this particular choice of network. In the case of MDs we observe an interplay between strong localization effects, due to the dendrimer topology, and good efficiency from the linear segments. We show that quantum transport is enhanced by interconnecting more layers of dendrimers.
Margolis, Alvaro; Parboosingh, John
2015-01-01
Prior interpersonal relationships and interactivity among members of professional associations may impact the learning process in continuing medical education (CME). On the other hand, CME programs that encourage interactivity between participants may impact structures and behaviors in these professional associations. With the advent of information and communication technologies, new communication spaces have emerged that have the potential to enhance networked learning in national and international professional associations and increase the effectiveness of CME for health professionals. In this article, network science, based on the application of network theory and other theories, is proposed as an approach to better understand the contribution networking and interactivity between health professionals in professional communities make to their learning and adoption of new practices over time. © 2015 The Alliance for Continuing Education in the Health Professions, the Society for Academic Continuing Medical Education, and the Council on Continuing Medical Education, Association for Hospital Medical Education.
Black hole microstates and attractor without supersymmetry
International Nuclear Information System (INIS)
Dabholkar, Atish; Trivedi, Sandip P.; Sen, Ashoke
2007-01-01
Due to the attractor mechanism, the entropy of an extremal black hole does not vary continuously as we vary the asymptotic values of various moduli fields. Using this fact we argue that the entropy of an extremal black hole in string theory, calculated for a range of values of the asymptotic moduli for which the microscopic theory is strongly coupled, should match the statistical entropy of the same system calculated for a range of values of the asymptotic moduli for which the microscopic theory is weakly coupled. This argument does not rely on supersymmetry and applies equally well to nonsupersymmetric extremal black holes. We discuss several examples which support this argument and also several caveats which could invalidate this argument
Finite time convergent learning law for continuous neural networks.
Chairez, Isaac
2014-02-01
This paper addresses the design of a discontinuous finite time convergent learning law for neural networks with continuous dynamics. The neural network was used here to obtain a non-parametric model for uncertain systems described by a set of ordinary differential equations. The source of uncertainties was the presence of some external perturbations and poor knowledge of the nonlinear function describing the system dynamics. A new adaptive algorithm based on discontinuous algorithms was used to adjust the weights of the neural network. The adaptive algorithm was derived by means of a non-standard Lyapunov function that is lower semi-continuous and differentiable in almost the whole space. A compensator term was included in the identifier to reject some specific perturbations using a nonlinear robust algorithm. Two numerical examples demonstrated the improvements achieved by the learning algorithm introduced in this paper compared to classical schemes with continuous learning methods. The first one dealt with a benchmark problem used in the paper to explain how the discontinuous learning law works. The second one used the methane production model to show the benefits in engineering applications of the learning law proposed in this paper. Copyright © 2013 Elsevier Ltd. All rights reserved.
Energy Technology Data Exchange (ETDEWEB)
Emenheiser, Jeffrey [Complexity Sciences Center, University of California, Davis, California 95616 (United States); Department of Physics, University of California, Davis, California 95616 (United States); Chapman, Airlie; Mesbahi, Mehran [William E. Boeing Department of Aeronautics and Astronautics, University of Washington, Seattle, Washington 98195 (United States); Pósfai, Márton [Complexity Sciences Center, University of California, Davis, California 95616 (United States); Department of Computer Science, University of California, Davis, California 95616 (United States); Crutchfield, James P. [Complexity Sciences Center, University of California, Davis, California 95616 (United States); Department of Physics, University of California, Davis, California 95616 (United States); Department of Computer Science, University of California, Davis, California 95616 (United States); Santa Fe Institute, Santa Fe, New Mexico 87501 (United States); D' Souza, Raissa M. [Complexity Sciences Center, University of California, Davis, California 95616 (United States); Department of Computer Science, University of California, Davis, California 95616 (United States); Santa Fe Institute, Santa Fe, New Mexico 87501 (United States); Department of Mechanical and Aerospace Engineering, University of California, Davis, California 95616 (United States)
2016-09-15
Following the long-lived qualitative-dynamics tradition of explaining behavior in complex systems via the architecture of their attractors and basins, we investigate the patterns of switching between distinct trajectories in a network of synchronized oscillators. Our system, consisting of nonlinear amplitude-phase oscillators arranged in a ring topology with reactive nearest-neighbor coupling, is simple and connects directly to experimental realizations. We seek to understand how the multiple stable synchronized states connect to each other in state space by applying Gaussian white noise to each of the oscillators' phases. To do this, we first analytically identify a set of locally stable limit cycles at any given coupling strength. For each of these attracting states, we analyze the effect of weak noise via the covariance matrix of deviations around those attractors. We then explore the noise-induced attractor switching behavior via numerical investigations. For a ring of three oscillators, we find that an attractor-switching event is always accompanied by the crossing of two adjacent oscillators' phases. For larger numbers of oscillators, we find that the distribution of times required to stochastically leave a given state falls off exponentially, and we build an attractor switching network out of the destination states as a coarse-grained description of the high-dimensional attractor-basin architecture.
Continuous Online Sequence Learning with an Unsupervised Neural Network Model.
Cui, Yuwei; Ahmad, Subutar; Hawkins, Jeff
2016-09-14
The ability to recognize and predict temporal sequences of sensory inputs is vital for survival in natural environments. Based on many known properties of cortical neurons, hierarchical temporal memory (HTM) sequence memory recently has been proposed as a theoretical framework for sequence learning in the cortex. In this letter, we analyze properties of HTM sequence memory and apply it to sequence learning and prediction problems with streaming data. We show the model is able to continuously learn a large number of variableorder temporal sequences using an unsupervised Hebbian-like learning rule. The sparse temporal codes formed by the model can robustly handle branching temporal sequences by maintaining multiple predictions until there is sufficient disambiguating evidence. We compare the HTM sequence memory with other sequence learning algorithms, including statistical methods: autoregressive integrated moving average; feedforward neural networks-time delay neural network and online sequential extreme learning machine; and recurrent neural networks-long short-term memory and echo-state networks on sequence prediction problems with both artificial and real-world data. The HTM model achieves comparable accuracy to other state-of-the-art algorithms. The model also exhibits properties that are critical for sequence learning, including continuous online learning, the ability to handle multiple predictions and branching sequences with high-order statistics, robustness to sensor noise and fault tolerance, and good performance without task-specific hyperparameter tuning. Therefore, the HTM sequence memory not only advances our understanding of how the brain may solve the sequence learning problem but is also applicable to real-world sequence learning problems from continuous data streams.
Attractors and basins of dynamical systems
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Attila Dénes
2011-03-01
Full Text Available There are several programs for studying dynamical systems, but none of them is very useful for investigating basins and attractors of higher dimensional systems. Our goal in this paper is to show a new algorithm for finding even chaotic attractors and their basins for these systems. We present an implementation and examples for the use of this program.
Tetrapterous butterfly attractors in modified Lorenz systems
International Nuclear Information System (INIS)
Yu Simin; Tang, Wallace K.S.
2009-01-01
In this paper, the Lorenz-type tetrapterous butterfly attractors are firstly reported. With the introduction of multiple segment piecewise linear functions, these interesting and complex attractors are obtained from two different modified Lorenz models. This approach are verified in both simulations and experiments.
Gender Differences in the Continuance of Online Social Networks
Shi, Na; Cheung, Christy M. K.; Lee, Matthew K. O.; Chen, Huaping
Social network sites (SNS) have become increasingly popular in the past few years benefiting from the rapid growth of Web 2.0 applications. However, research on the adoption and usage of SNS is limited. In this study, we attempt to understand users' continuance intention to use SNS and investigate the role of gender. A research model was developed and tested with 213 respondents from an online survey. The results confirm that users' continuance intention to use SNS is strongly determined by satisfaction. The effect of disconfirmation of maintaining offline contacts on satisfaction is more important for women, while the effect of disconfirmation of entertainment is more salient for men. Implications of this study for both researchers and practitioners are discussed.
Boundary Region Detection for Continuous Objects in Wireless Sensor Networks
Directory of Open Access Journals (Sweden)
Yaqiang Zhang
2018-01-01
Full Text Available Industrial Internet of Things has been widely used to facilitate disaster monitoring applications, such as liquid leakage and toxic gas detection. Since disasters are usually harmful to the environment, detecting accurate boundary regions for continuous objects in an energy-efficient and timely fashion is a long-standing research challenge. This article proposes a novel mechanism for continuous object boundary region detection in a fog computing environment, where sensing holes may exist in the deployed network region. Leveraging sensory data that have been gathered, interpolation algorithms have been applied to estimate sensory data at certain geographical locations, in order to estimate a more accurate boundary line. To examine whether estimated sensory data reflect that fact, mobile sensors are adopted to traverse these locations for gathering their sensory data, and the boundary region is calibrated accordingly. Experimental evaluation shows that this technique can generate a precise object boundary region with certain time constraints, and the network lifetime can be prolonged significantly.
Project ECHO: A Telementoring Network Model for Continuing Professional Development.
Arora, Sanjeev; Kalishman, Summers G; Thornton, Karla A; Komaromy, Miriam S; Katzman, Joanna G; Struminger, Bruce B; Rayburn, William F
2017-01-01
A major challenge with current systems of CME is the inability to translate the explosive growth in health care knowledge into daily practice. Project ECHO (Extension for Community Healthcare Outcomes) is a telementoring network designed for continuing professional development (CPD) and improving patient outcomes. The purpose of this article was to describe how the model has complied with recommendations from several authoritative reports about redesigning and enhancing CPD. This model links primary care clinicians through a knowledge network with an interprofessional team of specialists from an academic medical center who provide telementoring and ongoing education enabling community clinicians to treat patients with a variety of complex conditions. Knowledge and skills are shared during weekly condition-specific videoconferences. The model exemplifies learning as described in the seven levels of CPD by Moore (participation, satisfaction, learning, competence, performance, patient, and community health). The model is also aligned with recommendations from four national reports intended to redesign knowledge transfer in improving health care. Efforts in learning sessions focus on information that is relevant to practice, focus on evidence, education methodology, tailoring of recommendations to individual needs and community resources, and interprofessionalism. Project ECHO serves as a telementoring network model of CPD that aligns with current best practice recommendations for CME. This transformative initiative has the potential to serve as a leading model for larger scale CPD, nationally and globally, to enhance access to care, improve quality, and reduce cost.
Jiang, T; Jiang, C-Y; Shu, J-H; Xu, Y-J
2017-07-10
The molecular mechanism of nasopharyngeal carcinoma (NPC) is poorly understood and effective therapeutic approaches are needed. This research aimed to excavate the attractor modules involved in the progression of NPC and provide further understanding of the underlying mechanism of NPC. Based on the gene expression data of NPC, two specific protein-protein interaction networks for NPC and control conditions were re-weighted using Pearson correlation coefficient. Then, a systematic tracking of candidate modules was conducted on the re-weighted networks via cliques algorithm, and a total of 19 and 38 modules were separately identified from NPC and control networks, respectively. Among them, 8 pairs of modules with similar gene composition were selected, and 2 attractor modules were identified via the attract method. Functional analysis indicated that these two attractor modules participate in one common bioprocess of cell division. Based on the strategy of integrating systemic module inference with the attract method, we successfully identified 2 attractor modules. These attractor modules might play important roles in the molecular pathogenesis of NPC via affecting the bioprocess of cell division in a conjunct way. Further research is needed to explore the correlations between cell division and NPC.
The Lorentz Attractor and Other Attractors in the Economic System of a Firm
International Nuclear Information System (INIS)
Shapovalov, V I; Kazakov, N V
2015-01-01
A nonlinear model of the economic system of ''a firm'' is offered. It is shown that this model has several chaotic attractors, including the Lorentz attractor and a new attractor that, in our opinion, has not yet been described in the scientific literature. The chaotic nature of the attractors that were found was confirmed by computing the Lyapunov indicators. The functioning of our economic model is demonstrated with examples of firm behaviour that change the control parameters; these are well known in practice. In particular, it is shown that changes in the specific control parameters may change the system and avoid bankruptcy for the firm
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
Exponential attractors for a nonclassical diffusion equation
Directory of Open Access Journals (Sweden)
Qiaozhen Ma
2009-01-01
Full Text Available In this article, we prove the existence of exponential attractors for a nonclassical diffusion equation in ${H^{2}(Omega}cap{H}^{1}_{0}(Omega$ when the space dimension is less than 4.
Feigenbaum attractor and intermittency in particle collisions
International Nuclear Information System (INIS)
Batunin, A.V.
1992-01-01
The hypothesis is proposed that the Feigenbaum attractor arising as a limit set in an infinite pichfork bifurcation sequence for unimodal one-dimensional maps underlies the intermittency phenomena in particle collisions. 23 refs.; 8 figs
Continuous measurements of methane from a tower network over Siberia
International Nuclear Information System (INIS)
Sasakawa, M.; Machida, T.; Saeki, T.; Koyama, Y.; Maksyutov, S.; Shimoyama, K.; Tsuda, N.; Suto, H.; Arshinov, M.; Davydov, D.; Fofonov, A.; Krasnov, O.
2010-01-01
We have been conducting continuous measurements of Methane (CH 4 ) concentration from an expanding network of towers (JR-STATION: Japan-Russia Siberian Tall Tower Inland Observation Network) located in taiga, steppe and wetland biomes of Siberia since 2004. High daytime means (>2000 ppb) observed simultaneously at several towers during winter, together with in situ weather data and NCEP/NCAR reanalysis data, indicate that high pressure systems caused CH 4 accumulation at subcontinental scale due to the widespread formation of an inversion layer. Daytime means sometimes exceeded 2000 ppb, particularly in the summer of 2007 when temperature and precipitation rates were anomalously high over West Siberia, which implies that CH 4 emission from wetlands were exceptionally high in 2007. Many hot spots detected by MODIS in the summer of 2007 illustrate that the contribution of biomass burning also cannot be neglected. Daytime mean CH 4 concentrations from the Siberian tower sites were generally higher than CH 4 values reported at NOAA coastal sites in the same latitudinal zone, and the difference in concentrations between two sets of sites was reproduced with a coupled Eulerian-Lagrangian transport model. Simulations of emissions from different CH 4 sources suggested that the major contributor to variation switched from wetlands during summer to fossil fuel during winter.
Continuous measurements of methane from a tower network over Siberia
Energy Technology Data Exchange (ETDEWEB)
Sasakawa, M.; Machida, T.; Saeki, T.; Koyama, Y.; Maksyutov, S. (Center for Global Environmental Research, National Inst. for Environmental Studies, Tsukuba, Ibaraki (Japan)); Shimoyama, K. (Inst. of Low Temperature Science, Hokkaido Univ., Hokkaido (Japan)); Tsuda, N. (Global Environmental Forum, Tokyo (Japan)); Suto, H. (Japan Aerospace Exploration Agency (Japan)); Arshinov, M.; Davydov, D.; Fofonov, A.; Krasnov, O. (Inst. of Atmospheric Optics, Russian Academy of Sciences, Siberian Branch (Russian Federation))
2010-11-15
We have been conducting continuous measurements of Methane (CH{sub 4}) concentration from an expanding network of towers (JR-STATION: Japan-Russia Siberian Tall Tower Inland Observation Network) located in taiga, steppe and wetland biomes of Siberia since 2004. High daytime means (>2000 ppb) observed simultaneously at several towers during winter, together with in situ weather data and NCEP/NCAR reanalysis data, indicate that high pressure systems caused CH{sub 4} accumulation at subcontinental scale due to the widespread formation of an inversion layer. Daytime means sometimes exceeded 2000 ppb, particularly in the summer of 2007 when temperature and precipitation rates were anomalously high over West Siberia, which implies that CH{sub 4} emission from wetlands were exceptionally high in 2007. Many hot spots detected by MODIS in the summer of 2007 illustrate that the contribution of biomass burning also cannot be neglected. Daytime mean CH{sub 4} concentrations from the Siberian tower sites were generally higher than CH{sub 4} values reported at NOAA coastal sites in the same latitudinal zone, and the difference in concentrations between two sets of sites was reproduced with a coupled Eulerian-Lagrangian transport model. Simulations of emissions from different CH{sub 4} sources suggested that the major contributor to variation switched from wetlands during summer to fossil fuel during winter.
Continuous Learning of a Multilayered Network Topology in a Video Camera Network
Directory of Open Access Journals (Sweden)
Zou Xiaotao
2009-01-01
Full Text Available Abstract A multilayered camera network architecture with nodes as entry/exit points, cameras, and clusters of cameras at different layers is proposed. Unlike existing methods that used discrete events or appearance information to infer the network topology at a single level, this paper integrates face recognition that provides robustness to appearance changes and better models the time-varying traffic patterns in the network. The statistical dependence between the nodes, indicating the connectivity and traffic patterns of the camera network, is represented by a weighted directed graph and transition times that may have multimodal distributions. The traffic patterns and the network topology may be changing in the dynamic environment. We propose a Monte Carlo Expectation-Maximization algorithm-based continuous learning mechanism to capture the latent dynamically changing characteristics of the network topology. In the experiments, a nine-camera network with twenty-five nodes (at the lowest level is analyzed both in simulation and in real-life experiments and compared with previous approaches.
Continuous Learning of a Multilayered Network Topology in a Video Camera Network
Directory of Open Access Journals (Sweden)
Xiaotao Zou
2009-01-01
Full Text Available A multilayered camera network architecture with nodes as entry/exit points, cameras, and clusters of cameras at different layers is proposed. Unlike existing methods that used discrete events or appearance information to infer the network topology at a single level, this paper integrates face recognition that provides robustness to appearance changes and better models the time-varying traffic patterns in the network. The statistical dependence between the nodes, indicating the connectivity and traffic patterns of the camera network, is represented by a weighted directed graph and transition times that may have multimodal distributions. The traffic patterns and the network topology may be changing in the dynamic environment. We propose a Monte Carlo Expectation-Maximization algorithm-based continuous learning mechanism to capture the latent dynamically changing characteristics of the network topology. In the experiments, a nine-camera network with twenty-five nodes (at the lowest level is analyzed both in simulation and in real-life experiments and compared with previous approaches.
Strange Attractors in Drift Wave Turbulence
International Nuclear Information System (INIS)
Lewandowski, J.L.V.
2003-01-01
A multi-grid part-in-cell algorithm for a shearless slab drift wave model with kinetic electrons is presented. The algorithm, which is based on an exact separation of adiabatic and nonadiabatic electron responses, is used to investigate the presence of strange attractors in drift wave turbulence. Although the simulation model has a large number of degrees of freedom, it is found that the strange attractor is low-dimensional and that it is strongly affected by dissipative (collisional) effects
Rueckauer, Bodo; Lungu, Iulia-Alexandra; Hu, Yuhuang; Pfeiffer, Michael; Liu, Shih-Chii
2017-01-01
Spiking neural networks (SNNs) can potentially offer an efficient way of doing inference because the neurons in the networks are sparsely activated and computations are event-driven. Previous work showed that simple continuous-valued deep Convolutional Neural Networks (CNNs) can be converted into accurate spiking equivalents. These networks did not include certain common operations such as max-pooling, softmax, batch-normalization and Inception-modules. This paper presents spiking equivalents of these operations therefore allowing conversion of nearly arbitrary CNN architectures. We show conversion of popular CNN architectures, including VGG-16 and Inception-v3, into SNNs that produce the best results reported to date on MNIST, CIFAR-10 and the challenging ImageNet dataset. SNNs can trade off classification error rate against the number of available operations whereas deep continuous-valued neural networks require a fixed number of operations to achieve their classification error rate. From the examples of LeNet for MNIST and BinaryNet for CIFAR-10, we show that with an increase in error rate of a few percentage points, the SNNs can achieve more than 2x reductions in operations compared to the original CNNs. This highlights the potential of SNNs in particular when deployed on power-efficient neuromorphic spiking neuron chips, for use in embedded applications.
Directory of Open Access Journals (Sweden)
Bodo Rueckauer
2017-12-01
Full Text Available Spiking neural networks (SNNs can potentially offer an efficient way of doing inference because the neurons in the networks are sparsely activated and computations are event-driven. Previous work showed that simple continuous-valued deep Convolutional Neural Networks (CNNs can be converted into accurate spiking equivalents. These networks did not include certain common operations such as max-pooling, softmax, batch-normalization and Inception-modules. This paper presents spiking equivalents of these operations therefore allowing conversion of nearly arbitrary CNN architectures. We show conversion of popular CNN architectures, including VGG-16 and Inception-v3, into SNNs that produce the best results reported to date on MNIST, CIFAR-10 and the challenging ImageNet dataset. SNNs can trade off classification error rate against the number of available operations whereas deep continuous-valued neural networks require a fixed number of operations to achieve their classification error rate. From the examples of LeNet for MNIST and BinaryNet for CIFAR-10, we show that with an increase in error rate of a few percentage points, the SNNs can achieve more than 2x reductions in operations compared to the original CNNs. This highlights the potential of SNNs in particular when deployed on power-efficient neuromorphic spiking neuron chips, for use in embedded applications.
Supersymmetry, attractors and cosmic censorship
Energy Technology Data Exchange (ETDEWEB)
Bellorin, Jorge [Instituto de Fisica Teorica UAM/CSIC, Facultad de Ciencias C-XVI, C.U. Cantoblanco, E-28049 Madrid (Spain)]. E-mail: jorge.bellorin@uam.es; Meessen, Patrick [Instituto de Fisica Teorica UAM/CSIC, Facultad de Ciencias C-XVI, C.U. Cantoblanco, E-28049 Madrid (Spain)]. E-mail: patrick.meessen@cern.ch; Ortin, Tomas [Instituto de Fisica Teorica UAM/CSIC, Facultad de Ciencias C-XVI, C.U. Cantoblanco, E-28049 Madrid (Spain)]. E-mail: tomas.ortin@cern.ch
2007-01-29
We show that requiring unbroken supersymmetry everywhere in black-hole-type solutions of N=2, d=4 supergravity coupled to vector supermultiplets ensures in most cases absence of naked singularities. We formulate three specific conditions which we argue are equivalent to the requirement of global supersymmetry. These three conditions can be related to the absence of sources for NUT charge, angular momentum, scalar hair and negative energy, although the solutions can still have globally defined angular momentum and non-trivial scalar fields, as we show in an explicit example. Furthermore, only the solutions satisfying these requirements seem to have a microscopic interpretation in string theory since only they have supersymmetric sources. These conditions exclude, for instance, singular solutions such as the Kerr-Newman with M=|q|, which fails to be everywhere supersymmetric. We also present a re-derivation of several results concerning attractors in N=2, d=4 theories based on the explicit knowledge of the most general solutions in the timelike class.
Is attentional blink a byproduct of neocortical attractors?
Directory of Open Access Journals (Sweden)
David N Silverstein
2011-05-01
Full Text Available This study proposes a computational model for attentional blink or blink of the mind, a phenomenon where a human subject misses perception of a later expected visual pattern as two expected visual patterns are presented less than 500 ms apart. A neocortical patch modeled as an attractor network is stimulated with a sequence of 14 patterns 100 ms apart, two of which are expected targets. Patterns that become active attractors are considered recognized. A neocortical patch is represented as a square matrix of hypercolumns, each containing a set of minicolumns with synaptic connections within and across both minicolumns and hypercolumns. Each minicolumn consists of locally connected layer 2/3 pyramidal cells with interacting basket cells and layer 4 pyramidal cells for input stimulation. All neurons are implemented using the Hodgkin-Huxley multi-compartmental cell formalism and include calcium dynamics, and they interact via saturating and depressing AMPA / NMDA and GABAA synapses. Stored patterns are encoded with global connectivity of minicolumns across hypercolumns and active patterns compete as the result of lateral inhibition in the network. Stored patterns were stimulated over time intervals to create attractor interference measurable with synthetic spike traces. This setup corresponds with item presentations in human visual attentional blink studies. Stored target patterns were depolarized while distractor patterns where hyperpolarized to represent expectation of items in working memory. Additionally, studies on the inhibitory effect of benzodiazopines on attentional blink in human subjects were compared with neocortical simulations where the GABAA receptor conductance and decay time were increased. Simulations showed increases in the attentional blink duration, agreeing with observations in human studies.
Topological Effects and Performance Optimization in Transportation Continuous Network Design
Directory of Open Access Journals (Sweden)
Jianjun Wu
2014-01-01
Full Text Available Because of the limitation of budget, in the planning of road works, increased efforts should be made on links that are more critical to the whole traffic system. Therefore, it would be helpful to model and evaluate the vulnerability and reliability of the transportation network when the network design is processing. This paper proposes a bilevel transportation network design model, in which the upper level is to minimize the performance of the network under the given budgets, while the lower level is a typical user equilibrium assignment problem. A new solution approach based on particle swarm optimization (PSO method is presented. The topological effects on the performance of transportation networks are studied with the consideration of three typical networks, regular lattice, random graph, and small-world network. Numerical examples and simulations are presented to demonstrate the proposed model.
2013-11-18
... consumers value overall network reliability and quality in selecting mobile wireless service providers, they...-125] Improving the Resiliency of Mobile Wireless Communications Networks; Reliability and Continuity... (Reliability NOI) in 2011 to ``initiate a comprehensive examination of issues regarding the reliability...
Black hole attractors and pure spinors
International Nuclear Information System (INIS)
Hsu, Jonathan P.; Maloney, Alexander; Tomasiello, Alessandro
2006-01-01
We construct black hole attractor solutions for a wide class of N = 2 compactifications. The analysis is carried out in ten dimensions and makes crucial use of pure spinor techniques. This formalism can accommodate non-Kaehler manifolds as well as compactifications with flux, in addition to the usual Calabi-Yau case. At the attractor point, the charges fix the moduli according to Σf k = Im(CΦ), where Φ is a pure spinor of odd (even) chirality in IIB (A). For IIB on a Calabi-Yau, Φ = Ω and the equation reduces to the usual one. Methods in generalized complex geometry can be used to study solutions to the attractor equation
Describing chaotic attractors: Regular and perpetual points
Dudkowski, Dawid; Prasad, Awadhesh; Kapitaniak, Tomasz
2018-03-01
We study the concepts of regular and perpetual points for describing the behavior of chaotic attractors in dynamical systems. The idea of these points, which have been recently introduced to theoretical investigations, is thoroughly discussed and extended into new types of models. We analyze the correlation between regular and perpetual points, as well as their relation with phase space, showing the potential usefulness of both types of points in the qualitative description of co-existing states. The ability of perpetual points in finding attractors is indicated, along with its potential cause. The location of chaotic trajectories and sets of considered points is investigated and the study on the stability of systems is shown. The statistical analysis of the observing desired states is performed. We focus on various types of dynamical systems, i.e., chaotic flows with self-excited and hidden attractors, forced mechanical models, and semiconductor superlattices, exhibiting the universality of appearance of the observed patterns and relations.
Black Hole Attractors and Pure Spinors
International Nuclear Information System (INIS)
Hsu, Jonathan P.; Maloney, Alexander; Tomasiello, Alessandro
2006-01-01
We construct black hole attractor solutions for a wide class of N = 2 compactifications. The analysis is carried out in ten dimensions and makes crucial use of pure spinor techniques. This formalism can accommodate non-Kaehler manifolds as well as compactifications with flux, in addition to the usual Calabi-Yau case. At the attractor point, the charges fix the moduli according to Σf k = Im(CΦ), where Φ is a pure spinor of odd (even) chirality in IIB (A). For IIB on a Calabi-Yau, Φ = (Omega) and the equation reduces to the usual one. Methods in generalized complex geometry can be used to study solutions to the attractor equation
Non-linguistic Conditions for Causativization as a Linguistic Attractor
Johanna Nichols; Johanna Nichols; Johanna Nichols
2018-01-01
An attractor, in complex systems theory, is any state that is more easily or more often entered or acquired than departed or lost; attractor states therefore accumulate more members than non-attractors, other things being equal. In the context of language evolution, linguistic attractors include sounds, forms, and grammatical structures that are prone to be selected when sociolinguistics and language contact make it possible for speakers to choose between competing forms. The reasons why an e...
Connecting coherent structures and strange attractors
Keefe, Laurence R.
1990-01-01
A concept of turbulence derived from nonlinear dynamical systems theory suggests that turbulent solutions to the Navier-Stokes equations are restricted to strange attractors, and, by implication, that turbulent phenomenology must find some expression or source in the structure of these mathematical objects. Examples and discussions are presented to link coherent structures to some of the commonly known characteristics of strange attractors. Basic to this link is a geometric interpretation of conditional sampling techniques employed to educe coherent structures that offers an explanation for their appearance in measurements as well as their size.
Co-evolution of social networks and continuous actor attributes
Niezink, Nynke M.D.; Snijders, Tom A.B.
2017-01-01
Social networks and the attributes of the actors in these networks are not static; they may develop interdependently over time. The stochastic actor-oriented model allows for statistical inference on the mechanisms driving this co-evolution process. In earlier versions of this model, dynamic actor
Non-homogeneous dynamic Bayesian networks for continuous data
Grzegorczyk, Marco; Husmeier, Dirk
Classical dynamic Bayesian networks (DBNs) are based on the homogeneous Markov assumption and cannot deal with non-homogeneous temporal processes. Various approaches to relax the homogeneity assumption have recently been proposed. The present paper presents a combination of a Bayesian network with
Osaka, Kengo; Toriumi, Fujio; Sugawara, Toshihauru
2017-01-01
Social networking services (SNSs) are widely used as communicative tools for a variety of purposes. SNSs rely on the users' individual activities associated with some cost and effort, and thus it is not known why users voluntarily continue to participate in SNSs. Because the structures of SNSs are similar to that of the public goods (PG) game, some studies have focused on why voluntary activities emerge as an optimal strategy by modifying the PG game. However, their models do not include direct reciprocity between users, even though reciprocity is a key mechanism that evolves and sustains cooperation in human society. We developed an abstract SNS model called the reciprocity rewards and meta-rewards games that include direct reciprocity by extending the existing models. Then, we investigated how direct reciprocity in an SNS facilitates cooperation that corresponds to participation in SNS by posting articles and comments and how the structure of the networks of users exerts an influence on the strategies of users using the reciprocity rewards game. We run reciprocity rewards games on various complex networks and an instance network of Facebook and found that two types of stable cooperation emerged. First, reciprocity slightly improves the rate of cooperation in complete graphs but the improvement is insignificant because of the instability of cooperation. However, this instability can be avoided by making two assumptions: high degree of fun, i.e. articles are read with high probability, and different attitudes to reciprocal and non-reciprocal agents. We then propose the concept of half free riders to explain what strategy sustains cooperation-dominant situations. Second, we indicate that a certain WS network structure affects users' optimal strategy and facilitates stable cooperation without any extra assumptions. We give a detailed analysis of the different characteristics of the two types of cooperation-dominant situations and the effect of the memory of
Applying Chaos Theory to Careers: Attraction and Attractors
Pryor, Robert G. L.; Bright, Jim E. H.
2007-01-01
This article presents the Chaos Theory of Careers with particular reference to the concepts of "attraction" and "attractors". Attractors are defined in terms of characteristic trajectories, feedback mechanisms, end states, ordered boundedness, reality visions and equilibrium and fluctuation. The identified types of attractors (point, pendulum,…
Multifractal chaotic attractors in a system of delay-differential equations modeling road traffic.
Safonov, Leonid A.; Tomer, Elad; Strygin, Vadim V.; Ashkenazy, Yosef; Havlin, Shlomo
2002-12-01
We study a system of delay-differential equations modeling single-lane road traffic. The cars move in a closed circuit and the system's variables are each car's velocity and the distance to the car ahead. For low and high values of traffic density the system has a stable equilibrium solution, corresponding to the uniform flow. Gradually decreasing the density from high to intermediate values we observe a sequence of supercritical Hopf bifurcations forming multistable limit cycles, corresponding to flow regimes with periodically moving traffic jams. Using an asymptotic technique we find approximately small limit cycles born at Hopf bifurcations and numerically preform their global continuations with decreasing density. For sufficiently large delay the system passes to chaos following the Ruelle-Takens-Newhouse scenario (limit cycles-two-tori-three-tori-chaotic attractors). We find that chaotic and nonchaotic attractors coexist for the same parameter values and that chaotic attractors have a broad multifractal spectrum. (c) 2002 American Institute of Physics.
Energy Technology Data Exchange (ETDEWEB)
Guo, Kong-Ming, E-mail: kmguo@xidian.edu.cn [School of Electromechanical Engineering, Xidian University, P.O. Box 187, Xi' an 710071 (China); Jiang, Jun, E-mail: jun.jiang@mail.xjtu.edu.cn [State Key Laboratory for Strength and Vibration, Xi' an Jiaotong University, Xi' an 710049 (China)
2014-07-04
To apply stochastic sensitivity function method, which can estimate the probabilistic distribution of stochastic attractors, to non-autonomous dynamical systems, a 1/N-period stroboscopic map for a periodic motion is constructed in order to discretize the continuous cycle into a discrete one. In this way, the sensitivity analysis of a cycle for discrete map can be utilized and a numerical algorithm for the stochastic sensitivity analysis of periodic solutions of non-autonomous nonlinear dynamical systems under stochastic disturbances is devised. An external excited Duffing oscillator and a parametric excited laser system are studied as examples to show the validity of the proposed method. - Highlights: • A method to analyze sensitivity of stochastic periodic attractors in non-autonomous dynamical systems is proposed. • Probabilistic distribution around periodic attractors in an external excited Φ{sup 6} Duffing system is obtained. • Probabilistic distribution around a periodic attractor in a parametric excited laser system is determined.
Hematopoietic differentiation: a coordinated dynamical process towards attractor stable states
Directory of Open Access Journals (Sweden)
Rossi Simona
2010-06-01
Full Text Available Abstract Background The differentiation process, proceeding from stem cells towards the different committed cell types, can be considered as a trajectory towards an attractor of a dynamical process. This view, taking into consideration the transcriptome and miRNome dynamics considered as a whole, instead of looking at few 'master genes' driving the system, offers a novel perspective on this phenomenon. We investigated the 'differentiation trajectories' of the hematopoietic system considering a genome-wide scenario. Results We developed serum-free liquid suspension unilineage cultures of cord blood (CB CD34+ hematopoietic progenitor cells through erythroid (E, megakaryocytic (MK, granulocytic (G and monocytic (Mo pathways. These cultures recapitulate physiological hematopoiesis, allowing the analysis of almost pure unilineage precursors starting from initial differentiation of HPCs until terminal maturation. By analyzing the expression profile of protein coding genes and microRNAs in unilineage CB E, MK, G and Mo cultures, at sequential stages of differentiation and maturation, we observed a coordinated, fully interconnected and scalable character of cell population behaviour in both transcriptome and miRNome spaces reminiscent of an attractor-like dynamics. MiRNome and transcriptome space differed for a still not terminally committed behaviour of microRNAs. Conclusions Consistent with their roles, the transcriptome system can be considered as the state space of a cell population, while the continuously evolving miRNA space corresponds to the tuning system necessary to reach the attractor. The behaviour of miRNA machinery could be of great relevance not only for the promise of reversing the differentiated state but even for tumor biology.
Recurrence quantification analysis in Liu's attractor
International Nuclear Information System (INIS)
Balibrea, Francisco; Caballero, M. Victoria; Molera, Lourdes
2008-01-01
Recurrence Quantification Analysis is used to detect transitions chaos to periodical states or chaos to chaos in a new dynamical system proposed by Liu et al. This system contains a control parameter in the second equation and was originally introduced to investigate the forming mechanism of the compound structure of the chaotic attractor which exists when the control parameter is zero
Attractor merging crisis in chaotic business cycles
International Nuclear Information System (INIS)
Chian, Abraham C.-L.; Borotto, Felix A.; Rempel, Erico L.; Rogers, Colin
2005-01-01
A numerical study is performed on a forced-oscillator model of nonlinear business cycles. An attractor merging crisis due to a global bifurcation is analyzed using the unstable periodic orbits and their associated stable and unstable manifolds. Characterization of crisis can improve our ability to forecast sudden major changes in economic systems
Trajectory attractors of equations of mathematical physics
International Nuclear Information System (INIS)
Vishik, Marko I; Chepyzhov, Vladimir V
2011-01-01
In this survey the method of trajectory dynamical systems and trajectory attractors is described, and is applied in the study of the limiting asymptotic behaviour of solutions of non-linear evolution equations. This method is especially useful in the study of dissipative equations of mathematical physics for which the corresponding Cauchy initial-value problem has a global (weak) solution with respect to the time but the uniqueness of this solution either has not been established or does not hold. An important example of such an equation is the 3D Navier-Stokes system in a bounded domain. In such a situation one cannot use directly the classical scheme of construction of a dynamical system in the phase space of initial conditions of the Cauchy problem of a given equation and find a global attractor of this dynamical system. Nevertheless, for such equations it is possible to construct a trajectory dynamical system and investigate a trajectory attractor of the corresponding translation semigroup. This universal method is applied for various types of equations arising in mathematical physics: for general dissipative reaction-diffusion systems, for the 3D Navier-Stokes system, for dissipative wave equations, for non-linear elliptic equations in cylindrical domains, and for other equations and systems. Special attention is given to using the method of trajectory attractors in approximation and perturbation problems arising in complicated models of mathematical physics. Bibliography: 96 titles.
COSMOS-e'-soft Higgsotic attractors
Choudhury, Sayantan
2017-07-01
In this work, we have developed an elegant algorithm to study the cosmological consequences from a huge class of quantum field theories (i.e. superstring theory, supergravity, extra dimensional theory, modified gravity, etc.), which are equivalently described by soft attractors in the effective field theory framework. In this description we have restricted our analysis for two scalar fields - dilaton and Higgsotic fields minimally coupled with Einstein gravity, which can be generalized for any arbitrary number of scalar field contents with generalized non-canonical and non-minimal interactions. We have explicitly used R^2 gravity, from which we have studied the attractor and non-attractor phases by exactly computing two point, three point and four point correlation functions from scalar fluctuations using the In-In (Schwinger-Keldysh) and the δ N formalisms. We have also presented theoretical bounds on the amplitude, tilt and running of the primordial power spectrum, various shapes (equilateral, squeezed, folded kite or counter-collinear) of the amplitude as obtained from three and four point scalar functions, which are consistent with observed data. Also the results from two point tensor fluctuations and the field excursion formula are explicitly presented for the attractor and non-attractor phase. Further, reheating constraints, scale dependent behavior of the couplings and the dynamical solution for the dilaton and Higgsotic fields are also presented. New sets of consistency relations between two, three and four point observables are also presented, which shows significant deviation from canonical slow-roll models. Additionally, three possible theoretical proposals have presented to overcome the tachyonic instability at the time of late time acceleration. Finally, we have also provided the bulk interpretation from the three and four point scalar correlation functions for completeness.
COSMOS-e"'-soft Higgsotic attractors
International Nuclear Information System (INIS)
Choudhury, Sayantan
2017-01-01
In this work, we have developed an elegant algorithm to study the cosmological consequences from a huge class of quantum field theories (i.e. superstring theory, supergravity, extra dimensional theory, modified gravity, etc.), which are equivalently described by soft attractors in the effective field theory framework. In this description we have restricted our analysis for two scalar fields - dilaton and Higgsotic fields minimally coupled with Einstein gravity, which can be generalized for any arbitrary number of scalar field contents with generalized non-canonical and non-minimal interactions. We have explicitly used R"2 gravity, from which we have studied the attractor and non-attractor phases by exactly computing two point, three point and four point correlation functions from scalar fluctuations using the In-In (Schwinger-Keldysh) and the δN formalisms. We have also presented theoretical bounds on the amplitude, tilt and running of the primordial power spectrum, various shapes (equilateral, squeezed, folded kite or counter-collinear) of the amplitude as obtained from three and four point scalar functions, which are consistent with observed data. Also the results from two point tensor fluctuations and the field excursion formula are explicitly presented for the attractor and non-attractor phase. Further, reheating constraints, scale dependent behavior of the couplings and the dynamical solution for the dilaton and Higgsotic fields are also presented. New sets of consistency relations between two, three and four point observables are also presented, which shows significant deviation from canonical slow-roll models. Additionally, three possible theoretical proposals have presented to overcome the tachyonic instability at the time of late time acceleration. Finally, we have also provided the bulk interpretation from the three and four point scalar correlation functions for completeness. (orig.)
International Nuclear Information System (INIS)
Lian Yimin; Xie Changde; Peng Kunchi
2007-01-01
A variety of optical quantum information networks based on the multipartite entanglement of amplitude and phase quadratures of an electromagnetic field have been proposed and experimentally realized in recent years. The multipartite entanglement of optical continuous variables provides flexible and reliable quantum resources for developing unconditional quantum information networks. In this paper, we review the generation schemes of the multipartite entangled states of optical continuous quantum variables and some applications in the quantum communication networks with emphasis on the experimental implementations
Energy Technology Data Exchange (ETDEWEB)
Llibre, Jaume, E-mail: jllibre@mat.uab.cat [Universitat Autònoma de Barcelona, Departament de Matemàtiques (Spain); Valls, Claudia, E-mail: cvalls@math.ist.utl.pt [Universidade de Lisboa, Departamento de Matemática, Instituto Superior Técnico (Portugal)
2017-06-15
For a dynamical system described by a set of autonomous differential equations, an attractor can be either a point, or a periodic orbit, or even a strange attractor. Recently a new chaotic system with only one parameter has been presented where besides a point attractor and a chaotic attractor, it also has a coexisting attractor limit cycle which makes evident the complexity of such a system. We study using analytic tools the dynamics of such system. We describe its global dynamics near the infinity, and prove that it has no Darboux first integrals.
Global dissipativity of continuous-time recurrent neural networks with time delay
International Nuclear Information System (INIS)
Liao Xiaoxin; Wang Jun
2003-01-01
This paper addresses the global dissipativity of a general class of continuous-time recurrent neural networks. First, the concepts of global dissipation and global exponential dissipation are defined and elaborated. Next, the sets of global dissipativity and global exponentially dissipativity are characterized using the parameters of recurrent neural network models. In particular, it is shown that the Hopfield network and cellular neural networks with or without time delays are dissipative systems
Split Attractor Flow in N=2 Minimally Coupled Supergravity
Ferrara, Sergio; Orazi, Emanuele
2011-01-01
We classify the stability region, marginal stability walls (MS) and split attractor flows for two-center extremal black holes in four-dimensional N=2 supergravity minimally coupled to n vector multiplets. It is found that two-center (continuous) charge orbits, classified by four duality invariants, either support a stability region ending on a MS wall or on an anti-marginal stability (AMS) wall, but not both. Therefore, the scalar manifold never contains both walls. Moreover, the BPS mass of the black hole composite (in its stability region) never vanishes in the scalar manifold. For these reasons, the "bound state transformation walls" phenomenon does not necessarily occur in these theories. The entropy of the flow trees also satisfies an inequality which forbids "entropy enigma" decays in these models. Finally, the non-BPS case, due to the existence of a "fake" superpotential satisfying a triangle inequality, can be treated as well, and it can be shown to exhibit a split attractor flow dynamics which, at le...
International Nuclear Information System (INIS)
Huo Haifeng; Li Wantong
2009-01-01
This paper is concerned with the global stability characteristics of a system of equations modelling the dynamics of continuous-time bidirectional associative memory neural networks with impulses. Sufficient conditions which guarantee the existence of a unique equilibrium and its exponential stability of the networks are obtained. For the goal of computation, discrete-time analogues of the corresponding continuous-time bidirectional associative memory neural networks with impulses are also formulated and studied. Our results show that the above continuous-time and discrete-time systems with impulses preserve the dynamics of the networks without impulses when we make some modifications and impose some additional conditions on the systems, the convergence characteristics dynamics of the networks are preserved by both continuous-time and discrete-time systems with some restriction imposed on the impulse effect.
Two-Layer Feedback Neural Networks with Associative Memories
International Nuclear Information System (INIS)
Gui-Kun, Wu; Hong, Zhao
2008-01-01
We construct a two-layer feedback neural network by a Monte Carlo based algorithm to store memories as fixed-point attractors or as limit-cycle attractors. Special attention is focused on comparing the dynamics of the network with limit-cycle attractors and with fixed-point attractors. It is found that the former has better retrieval property than the latter. Particularly, spurious memories may be suppressed completely when the memories are stored as a long-limit cycle. Potential application of limit-cycle-attractor networks is discussed briefly. (general)
International Nuclear Information System (INIS)
Liang Jinling; Cao Jinde
2004-01-01
First, convergence of continuous-time Bidirectional Associative Memory (BAM) neural networks are studied. By using Lyapunov functionals and some analysis technique, the delay-independent sufficient conditions are obtained for the networks to converge exponentially toward the equilibrium associated with the constant input sources. Second, discrete-time analogues of the continuous-time BAM networks are formulated and studied. It is shown that the convergence characteristics of the continuous-time systems are preserved by the discrete-time analogues without any restriction imposed on the uniform discretionary step size. An illustrative example is given to demonstrate the effectiveness of the obtained results
Black hole entropy functions and attractor equations
International Nuclear Information System (INIS)
Lopes Cardoso, Gabriel; Wit, Bernard de; Mahapatra, Swapna
2007-01-01
The entropy and the attractor equations for static extremal black hole solutions follow from a variational principle based on an entropy function. In the general case such an entropy function can be derived from the reduced action evaluated in a near-horizon geometry. BPS black holes constitute special solutions of this variational principle, but they can also be derived directly from a different entropy function based on supersymmetry enhancement at the horizon. Both functions are consistent with electric/magnetic duality and for BPS black holes their corresponding OSV-type integrals give identical results at the semi-classical level. We clarify the relation between the two entropy functions and the corresponding attractor equations for N = 2 supergravity theories with higher-derivative couplings in four space-time dimensions. We discuss how non-holomorphic corrections will modify these entropy functions
D0-branes in black hole attractors
International Nuclear Information System (INIS)
Gaiotto, Davide; Simons, Aaron; Strominger, Andrew; Yin Xi
2006-01-01
Configurations of N probe D0-branes in a Calabi-Yau black hole are studied. A large degeneracy of near-horizon bound states are found which can be described as lowest Landau levels tiling the horizon of the black hole. These states preserve some of the enhanced supersymmetry of the near-horizon AdS 2 x S 2 x CY 3 attractor geometry, but not of the full asymptotically flat solution. Supersymmetric non-abelian configurations are constructed which, via the Myers effect, develop charges associated with higher-dimensional branes wrapping CY 3 cycles. An SU(1,1/2) superconformal quantum mechanics describing D0-branes in the attractor geometry is explicitly constructed
Sneutrino Inflation with $\\alpha$-attractors
Kallosh, Renata; Roest, Diederik; Wrase, Timm
2016-11-22
Sneutrino inflation employs the fermionic partners of the inflaton and stabilizer field as right-handed neutrinos to realize the seesaw mechanism for light neutrino masses. A crucial ingredient in existing constructions for sneutrino (multi-)natural inflation is an unbroken discrete shift symmetry. We demonstrate that a similar construction applies to $\\alpha$-attractor models. In this case the hyperbolic geometry protects the neutrino Yukawa couplings to the inflaton field, and the masses of leptons and Higgs fields, from blowing up when the inflaton is super-Planckian. We find that the predictions for $n_s$ and $r$ for $\\alpha$-attractor cosmological models, compatible with the current cosmological data, are preserved in the presence of the neutrino sector.
Attractors near grazing–sliding bifurcations
International Nuclear Information System (INIS)
Glendinning, P; Kowalczyk, P; Nordmark, A B
2012-01-01
In this paper we prove, for the first time, that multistability can occur in three-dimensional Fillipov type flows due to grazing–sliding bifurcations. We do this by reducing the study of the dynamics of Filippov type flows around a grazing–sliding bifurcation to the study of appropriately defined one-dimensional maps. In particular, we prove the presence of three qualitatively different types of multiple attractors born in grazing–sliding bifurcations. Namely, a period-two orbit with a sliding segment may coexist with a chaotic attractor, two stable, period-two and period-three orbits with a segment of sliding each may coexist, or a non-sliding and period-three orbit with two sliding segments may coexist
The power spectrum of inflationary attractors
International Nuclear Information System (INIS)
Broy, Benedict J.; Westphal, Alexander; Roest, Diederik
2014-08-01
Inflationary attractors predict the spectral index and tensor-to-scalar ratio to take specific values that are consistent with Planck. An example is the universal attractor for models with a generalised non-minimal coupling, leading to Starobinsky inflation. In this letter we demonstrate that it also predicts a specific relation between the amplitude of the power spectrum and the number of e-folds. The length and height of the inflationary plateau are related via the non-minimal coupling: in a wide variety of examples, the observed power normalisation leads to at least 55 flat e-foldings. Prior to this phase, the inflationary predictions vary and can account for the observational indications of power loss at large angular scales.
Contractive function systems, their attractors and metrization
Czech Academy of Sciences Publication Activity Database
Banakh, T.; Kubiś, Wieslaw; Novosad, N.; Nowak, M.; Strobin, F.
2015-01-01
Roč. 46, č. 2 (2015), s. 1029-1066 ISSN 1230-3429 R&D Projects: GA ČR(CZ) GA14-07880S Institutional support: RVO:67985840 Keywords : fractal * attractor * iterated function system * contracting function system Subject RIV: BA - General Mathematics Impact factor: 0.717, year: 2015 http://www.apcz.pl/czasopisma/index.php/TMNA/article/view/TMNA.2015.076
Internal wave attractors: different scenarios of instability
Brouzet, Christophe; Ermanyuk, E. V.; Joubaud, Sylvain; Pillet, Grimaud; Dauxois, Thierry
2017-01-01
International audience; This paper presents an experimental study of different instability scenarios in a parallelogram-shaped internal wave attractor in a trapezoidal domain filled with a uniformly stratified fluid.Energy is injected into the system via the oscillatory motion of a vertical wall of the trapezoidal domain. Whole-field velocity measurements are performed with the conventional PIV technique. In the linear regime, the total kinetic energyof the fluid system is used to quantify th...
Holonomy Attractor Connecting Spaces of Different Curvature Responsible for ``Anomalies''
Binder, Bernd
2009-03-01
SO(3). MAP can be extended to a neural network, where the synaptic connection of the holonomy attractor is just the mathematical condition adjusting and bridging spaces with positive (spherical) and negative (hyperbolic) curvature allowing for lossless/supra spin currents. Another strategy is to look for existing spin/precession anomalies and corresponding nonlinear holonomy conditions at the most fundamental level from the quark level to the cosmic scale. In these sceneries the geodesic attractor could control holonomy and curvature near the fixed points. It was proposed in 2002 that this should happen with electrons in atomic orbits showing a Berry phase part of the Rydberg or Sommerfeld fine structure constant and in 2003 that this effect could be responsible for (in)stabilities in the nuclear range and in superconductors. In 2008 it was shown that the attractor is part of the chaotic mechanical dynamics successfully at work in the Gyro-twister fitness device, and in 2007-2009 that there could be some deep relevance to "anomalies" in many scenarios even on the cosmic scales. Thus, we will point to and discuss some possible future applications that could be utilized for metric engineering: generating artificial holonomy and curvature (DC effect) for propulsion, or forcing holonomy waves (AC effect) in hyperbolic space-time, which are just gravitational waves interesting for communication.
Directory of Open Access Journals (Sweden)
Jacques Demongeot
2018-01-01
Full Text Available Networks used in biological applications at different scales (molecule, cell and population are of different types: neuronal, genetic, and social, but they share the same dynamical concepts, in their continuous differential versions (e.g., non-linear Wilson-Cowan system as well as in their discrete Boolean versions (e.g., non-linear Hopfield system; in both cases, the notion of interaction graph G(J associated to its Jacobian matrix J, and also the concepts of frustrated nodes, positive or negative circuits of G(J, kinetic energy, entropy, attractors, structural stability, etc., are relevant and useful for studying the dynamics and the robustness of these systems. We will give some general results available for both continuous and discrete biological networks, and then study some specific applications of three new notions of entropy: (i attractor entropy, (ii isochronal entropy and (iii entropy centrality; in three domains: a neural network involved in the memory evocation, a genetic network responsible of the iron control and a social network accounting for the obesity spread in high school environment.
Noise-Assisted Concurrent Multipath Traffic Distribution in Ad Hoc Networks
Murata, Masayuki
2013-01-01
The concept of biologically inspired networking has been introduced to tackle unpredictable and unstable situations in computer networks, especially in wireless ad hoc networks where network conditions are continuously changing, resulting in the need of robustness and adaptability of control methods. Unfortunately, existing methods often rely heavily on the detailed knowledge of each network component and the preconfigured, that is, fine-tuned, parameters. In this paper, we utilize a new concept, called attractor perturbation (AP), which enables controlling the network performance using only end-to-end information. Based on AP, we propose a concurrent multipath traffic distribution method, which aims at lowering the average end-to-end delay by only adjusting the transmission rate on each path. We demonstrate through simulations that, by utilizing the attractor perturbation relationship, the proposed method achieves a lower average end-to-end delay compared to other methods which do not take fluctuations into account. PMID:24319375
International Nuclear Information System (INIS)
Sun Mei; Zeng Changyan; Tao Yangwei; Tian Lixin
2009-01-01
Based on the comparison theorem for the stability of impulsive control system, adaptive-impulsive synchronization in drive-response networks of continuous systems with time-delay and non-time-delay is investigated. And the continuous control input, the simple updated laws and a linear impulsive controller are proposed. Moreover, two numerical examples are presented to verify the effectiveness and correctness of the theorem, using the energy resource system and Lue's system as the nodes of the networks.
International Nuclear Information System (INIS)
Cao Jinde
2004-01-01
In this Letter, the domain of attraction of memory patterns and exponential convergence rate of the network trajectories to memory patterns for Hopfield continuous associative memory are estimated by means of matrix measure and comparison principle. A new estimation is given for the domain of attraction of memory patterns and exponential convergence rate. These results can be used for the evaluation of fault-tolerance capability and the synthesis procedures for Hopfield continuous feedback associative memory neural networks
Black-Hole Attractors in N=1 Supergravity
Andrianopoli, L; Ferrara, Sergio; Trigiante, M; Andrianopoli, Laura; Auria, Riccardo D'; Ferrara, Sergio; Trigiante, Mario
2007-01-01
We study the attractor mechanism for N=1 supergravity coupled to vector and chiral multiplets and compute the attractor equations of these theories. These equations may have solutions depending on the choice of the holomorphic symmetric matrix f_{\\Lambda\\Sigma} which appears in the kinetic lagrangian of the vector sector. Models with non trivial electric-magnetic duality group which have or have not attractor behavior are exhibited. For a particular class of models, based on an N=1 reduction of homogeneous special geometries, the attractor equations are related to the theory of pure spinors.
Loonen, Anton J M; Ivanova, Svetlana A
2017-01-01
The non-reward attractor theory of depression describes this mood disorder as originating from a neuronal dysfunction that arises from increased vulnerability of a cortical network that detects failure to receive an expected reward. From an evolutionary standpoint, the concept that the cerebral
3rd School on Attractor Mechanism
SAM 2007; The Attractor Mechanism: Proceedings of the INFN-Laboratori Nazionali di Frascati School 2007
2010-01-01
This book is based upon lectures presented in June 2007 at the INFN-Laboratori Nazionali di Frascati School on Attractor Mechanism, directed by Stefano Bellucci. The symposium included such prestigious lecturers as S. Ferrara, M. Gunaydin, P. Levay, and T. Mohaupt. All lectures were given at a pedagogical, introductory level, which is reflected in the specific "flavor" of this volume. The book also benefits from extensive discussions about, and related reworking of, the various contributions. In addition, this volume contains contributions originating from short presentations of rece
Strange Attractors in Drift Wave Turbulence
International Nuclear Information System (INIS)
Lewandowski, Jerome L.V.
2003-01-01
There are growing experimental, numerical and theoretical evidences that the anomalous transport observed in tokamaks and stellarators is caused by slow, drift-type modes (such as trapped electron modes and ion-temperature gradient-driven modes). Although typical collision frequencies in hot, magnetized fusion plasmas can be quite low in absolute values, collisional effects are nevertheless important since they act as dissipative sinks. As it is well known, dissipative systems with many (strictly speaking more than two) degrees of freedom are often chaotic and may evolve towards a so-called attractor
Attractors of the periodically forced Rayleigh system
Directory of Open Access Journals (Sweden)
Petre Bazavan
2011-07-01
Full Text Available The autonomous second order nonlinear ordinary differential equation(ODE introduced in 1883 by Lord Rayleigh, is the equation whichappears to be the closest to the ODE of the harmonic oscillator withdumping.In this paper we present a numerical study of the periodic andchaotic attractors in the dynamical system associated with the generalized Rayleigh equation. Transition between periodic and quasiperiodic motion is also studied. Numerical results describe the system dynamics changes (in particular bifurcations, when the forcing frequency is varied and thus, periodic, quasiperiodic or chaotic behaviour regions are predicted.
Existence of global attractor for the Trojan Y Chromosome model
Directory of Open Access Journals (Sweden)
Xiaopeng Zhao
2012-04-01
Full Text Available This paper is concerned with the long time behavior of solution for the equation derived by the Trojan Y Chromosome (TYC model with spatial spread. Based on the regularity estimates for the semigroups and the classical existence theorem of global attractors, we prove that this equations possesses a global attractor in $H^k(\\Omega^4$ $(k\\geq 0$ space.
Attractors for a class of doubly nonlinear parabolic systems
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Hamid El Ouardi
2006-03-01
Full Text Available In this paper, we establish the existence and boundedness of solutions of a doubly nonlinear parabolic system. We also obtain the existence of a global attractor and the regularity property for this attractor in $\\left[ L^{\\infty }(\\Omega \\right] ^{2}$ and ${\\prod_{i=1}^{2}}{B_{\\infty }^{1+\\sigma_{i},p_{i}}( \\Omega } $.
Existence and attractors of solutions for nonlinear parabolic systems
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Hamid El Ouardi
2001-01-01
Full Text Available We prove existence and asymptotic behaviour results for weak solutions of a mixed problem (S. We also obtain the existence of the global attractor and the regularity for this attractor in $\\left[H^{2}(\\Omega \\right] ^{2}$ and we derive estimates of its Haussdorf and fractal dimensions.
Synchronization in Coupled Oscillators with Two Coexisting Attractors
International Nuclear Information System (INIS)
Han-Han, Zhu; Jun-Zhong, Yang
2008-01-01
Dynamics in coupled Duffing oscillators with two coexisting symmetrical attractors is investigated. For a pair of Duffing oscillators coupled linearly, the transition to the synchronization generally consists of two steps: Firstly, the two oscillators have to jump onto a same attractor, then they reach synchronization similarly to coupled monostable oscillators. The transition scenarios to the synchronization observed are strongly dependent on initial conditions. (general)
Attractor mechanism as a distillation procedure
International Nuclear Information System (INIS)
Levay, Peter; Szalay, Szilard
2010-01-01
In a recent paper it was shown that for double extremal static spherical symmetric BPS black hole solutions in the STU model the well-known process of moduli stabilization at the horizon can be recast in a form of a distillation procedure of a three-qubit entangled state of a Greenberger-Horne-Zeilinger type. By studying the full flow in moduli space in this paper we investigate this distillation procedure in more detail. We introduce a three-qubit state with amplitudes depending on the conserved charges, the warp factor, and the moduli. We show that for the recently discovered non-BPS solutions it is possible to see how the distillation procedure unfolds itself as we approach the horizon. For the non-BPS seed solutions at the asymptotically Minkowski region we are starting with a three-qubit state having seven nonequal nonvanishing amplitudes and finally at the horizon we get a Greenberger-Horne-Zeilinger state with merely four nonvanishing ones with equal magnitudes. The magnitude of the surviving nonvanishing amplitudes is proportional to the macroscopic black hole entropy. A systematic study of such attractor states shows that their properties reflect the structure of the fake superpotential. We also demonstrate that when starting with the very special values for the moduli corresponding to flat directions the uniform structure at the horizon deteriorates due to errors generalizing the usual bit flips acting on the qubits of the attractor states.
Baars, Holger; Althausen, Dietrich; Engelmann, Ronny; Heese, Birgit; Ansmann, Albert; Wandinger, Ulla; Hofer, Julian; Skupin, Annett; Komppula, Mika; Giannakaki, Eleni; Filioglou, Maria; Bortoli, Daniele; Silva, Ana Maria; Pereira, Sergio; Stachlewska, Iwona S.; Kumala, Wojciech; Szczepanik, Dominika; Amiridis, Vassilis; Marinou, Eleni; Kottas, Michail; Mattis, Ina; Müller, Gerhard
2018-04-01
PollyNET is a network of portable, automated, and continuously measuring Ramanpolarization lidars of type Polly operated by several institutes worldwide. The data from permanent and temporary measurements sites are automatically processed in terms of optical aerosol profiles and displayed in near-real time at polly.tropos.de. According to current schedules, the network will grow by 3-4 systems during the upcoming 2-3 years and will then comprise 11 permanent stations and 2 mobile platforms.
Breakout Prediction Based on BP Neural Network in Continuous Casting Process
Directory of Open Access Journals (Sweden)
Zhang Ben-guo
2016-01-01
Full Text Available An improved BP neural network model was presented by modifying the learning algorithm of the traditional BP neural network, based on the Levenberg-Marquardt algorithm, and was applied to the breakout prediction system in the continuous casting process. The results showed that the accuracy rate of the model for the temperature pattern of sticking breakout was 96.43%, and the quote rate was 100%, that verified the feasibility of the model.
C-RNN-GAN: Continuous recurrent neural networks with adversarial training
Mogren, Olof
2016-01-01
Generative adversarial networks have been proposed as a way of efficiently training deep generative neural networks. We propose a generative adversarial model that works on continuous sequential data, and apply it by training it on a collection of classical music. We conclude that it generates music that sounds better and better as the model is trained, report statistics on generated music, and let the reader judge the quality by downloading the generated songs.
Janssen, Hans-Karl; Stenull, Olaf
2004-02-01
We investigate corrections to scaling induced by irrelevant operators in randomly diluted systems near the percolation threshold. The specific systems that we consider are the random resistor network and a class of continuous spin systems, such as the x-y model. We focus on a family of least irrelevant operators and determine the corrections to scaling that originate from this family. Our field theoretic analysis carefully takes into account that irrelevant operators mix under renormalization. It turns out that long standing results on corrections to scaling are respectively incorrect (random resistor networks) or incomplete (continuous spin systems).
International Nuclear Information System (INIS)
Abdullah, M.A.; Agalgaonkar, A.P.; Muttaqi, K.M.
2014-01-01
Highlights: • Difficulties in assessing distribution network adequacy with DG are addressed. • Indices are proposed to assess adequacy of energy supply and service continuity. • Analytical methodology is developed to assess the proposed indices. • Concept of joint probability distribution of demand and generation is applied. - Abstract: Continuity of electricity supply with renewable distributed generation (DG) is a topical issue for distribution system planning and operation, especially due to the stochastic nature of power generation and time varying load demand. The conventional adequacy and reliability analysis methods related to bulk generation systems cannot be applied directly for the evaluation of adequacy criteria such as ‘energy supply’ and ‘continuity of service’ for distribution networks embedded with renewable DG. In this paper, new indices highlighting ‘available supply capacity’ and ‘continuity of service’ are proposed for ‘energy supply’ and ‘continuation of service’ evaluation of generation-rich distribution networks, and analytical techniques are developed for their quantification. A probability based analytical method has been developed using the joint probability of the demand and generation, and probability distributions of the proposed indices have been used to evaluate the network adequacy in energy supply and service continuation. A data clustering technique has been used to evaluate the joint probability between coincidental demand and renewable generation. Time sequential Monte Carlo simulation has been used to compare the results obtained using the proposed analytical method. A standard distribution network derived from Roy Billinton test system and a practical radial distribution network have been used to test the proposed method and demonstrate the estimation of the well-being of a system for hosting renewable DG units. It is found that renewable DG systems improve the ‘energy supply’ and ‘continuity
Directory of Open Access Journals (Sweden)
J. Verhoef
2004-07-01
Full Text Available Purpose: To evaluate the feasibility of regional physical therapy networks including continuing education in rheumatology. The aim of these networks was to improve care provided by primary care physical therapists by improving specific knowledge, technical and communicative skills and the collaboration with rheumatologists. Methods: In two regions in The Netherlands continuing education (CE programmes, consisting of a 5-day postgraduate training course followed by bimonthly workshops and teaching practices, were organised simultaneously. Network activities included consultations, newsletters and the development of a communication guideline. Endpoint measures included the participation rate, compliance, quality of the CE programme, teaching practices, knowledge, network activities, communication, number of patients treated and patient satisfaction. Results: Sixty-three physical therapists out of 193 practices (33% participated in the project. They all completed the education programmes and were formally registered. All evaluations of the education programmes showed positive scores. Knowledge scores increased significantly directly after the training course and at 18 months. A draft guideline on communication between physical therapists and rheumatologists was developed, and 4 newsletters were distributed. A substantial proportion of physical therapists and rheumatologists reported improved communication at 18 months. The mean number of patients treated by physical therapists participating in the networks increased significantly. Patients' satisfaction scores within the networks were significantly higher than those from outside the networks at 18 months. Conclusions: Setting up a system of networks for continuing education for physical therapists regarding the treatment of patients with rheumatic diseases is feasible. Further research will focus on the effectiveness of the system and its implementation on a larger scale.
Periodicity, chaos, and multiple attractors in a memristor-based Shinriki's circuit
Energy Technology Data Exchange (ETDEWEB)
Kengne, J. [Laboratory of Automation and Applied Computer (LAIA), Department of Electrical Engineering, IUT-FV Bandjoun, University of Dschang, Dschang (Cameroon); Njitacke Tabekoueng, Z.; Kamdoum Tamba, V.; Nguomkam Negou, A. [Laboratory of Automation and Applied Computer (LAIA), Department of Electrical Engineering, IUT-FV Bandjoun, University of Dschang, Dschang (Cameroon); Department of Physics, Laboratory of Electronics and Signal Processing (LETS), Faculty of Science, University of Dschang, Dschang (Cameroon)
2015-10-15
In this contribution, a novel memristor-based oscillator, obtained from Shinriki's circuit by substituting the nonlinear positive conductance with a first order memristive diode bridge, is introduced. The model is described by a continuous time four-dimensional autonomous system with smooth nonlinearities. The basic dynamical properties of the system are investigated including equilibria and stability, phase portraits, frequency spectra, bifurcation diagrams, and Lyapunov exponents' spectrum. It is found that in addition to the classical period-doubling and symmetry restoring crisis scenarios reported in the original circuit, the memristor-based oscillator experiences the unusual and striking feature of multiple attractors (i.e., coexistence of a pair of asymmetric periodic attractors with a pair of asymmetric chaotic ones) over a broad range of circuit parameters. Results of theoretical analyses are verified by laboratory experimental measurements.
A New Chaotic Attractor with Quadratic Exponential Nonlinear Term from Chen’s Attractor
Directory of Open Access Journals (Sweden)
Iftikhar Ahmed
2014-02-01
Full Text Available In this paper a new three-dimensional chaotic system is proposed, which relies on a nonlinear exponential term and a nonlinear quadratic cross term necessary for folding trajectories. Basic dynamical characteristics of the new system are analyzed. Compared with the Chen system, the equilibrium points of the new system does not contain the origin, and has a greater positive Lyapunov index, can produce more complex shaped chaotic attractor.
Analyzing Networked Learning Practices in HigherEducation and Continuing Professional Development
DEFF Research Database (Denmark)
Dirckinck-Holmfeld, Lone
Deliverable 28.5.4 reports on the preparation of the book "Analysing Networked Learning Practices in Higher Education and Continuing Professional Development", which consists of an Introduction, case studies and a concluding section, which presents the theoretical work and empirical work conducte...
Global asymptotic stability of Cohen-Grossberg neural network with continuously distributed delays
International Nuclear Information System (INIS)
Wan Li; Sun Jianhua
2005-01-01
The convergence dynamical behaviors of Cohen-Grossberg neural network with continuously distributed delays are discussed. By using Brouwer's fixed point theorem, matrix theory and analysis techniques such as Gronwall inequality, some new sufficient conditions guaranteeing the existence, uniqueness of an equilibrium point and its global asymptotic stability are obtained. An example is given to illustrate the theoretical results
International Nuclear Information System (INIS)
Wang Yixuan; Xiong Wanmin; Zhou Qiyuan; Xiao Bing; Yu Yuehua
2006-01-01
In this Letter cellular neural networks with continuously distributed delays and impulses are considered. Sufficient conditions for the existence and global exponential stability of a unique equilibrium point are established by using the fixed point theorem and differential inequality techniques. The results of this Letter are new and they complement previously known results
Fibre inflation and α-attractors
Energy Technology Data Exchange (ETDEWEB)
Kallosh, Renata; Linde, Andrei [Stanford Univ., Stanford, CA (United States). Stanford Inst. for Theoretical Physics and Dept. of Physics; Leiden Univ. (Netherlands). Lorentz Inst. for Theoretical Physics; Roest, Diederik [Groningen Univ. (Netherlands). Van Swinderen Inst. for Particle Physics and Gravity; Westphal, Alexander [DESY, Hamburg (Germany). Theory Group; Yamada, Yusuke [Stanford Univ., Stanford, CA (United States). Stanford Inst. for Theoretical Physics and Dept. of Physics
2017-07-15
Fibre inflation is a specific string theory construction based on the Large Volume Scenario that produces an inflationary plateau. We outline its relation to α-attractor models for inflation, with the cosmological sector originating from certain string theory corrections leading to α=2 and α=1/2. Above a certain field range, the steepening effect of higher-order corrections leads first to the breakdown of single-field slow-roll and after that to the onset of 2-field dynamics: the overall volume of the extra dimensions starts to participate in the effective dynamics. Finally, we propose effective supergravity models of fibre inflation based on an D3 uplift term with a nilpotent superfield. Specific moduli dependent D3 induced geometries lead to cosmological fibre models but have in addition a de Sitter minimum exit. These supergravity models motivated by fibre inflation are relatively simple, stabilize the axions and disentangle the Hubble parameter from supersymmetry breaking.
Attractor cosmology from nonminimally coupled gravity
Odintsov, S. D.; Oikonomou, V. K.
2018-03-01
By using a bottom-up reconstruction technique for nonminimally coupled scalar-tensor theories, we realize the Einstein frame attractor cosmologies in the Ω (ϕ )-Jordan frame. For our approach, what is needed for the reconstruction method to work is the functional form of the nonminimal coupling Ω (ϕ ) and of the scalar-to-tensor ratio, and also the assumption of the slow-roll inflation in the Ω (ϕ )-Jordan frame. By appropriately choosing the scalar-to-tensor ratio, we demonstrate that the observational indices of the attractor cosmologies can be realized directly in the Ω (ϕ )-Jordan frame. We investigate the special conditions that are required to hold true in for this realization to occur, and we provide the analytic form of the potential in the Ω (ϕ )-Jordan frame. Also, by performing a conformal transformation, we find the corresponding Einstein frame canonical scalar-tensor theory, and we calculate in detail the corresponding observational indices. The result indicates that although the spectral index of the primordial curvature perturbations is the same in the Jordan and Einstein frames, at leading order in the e -foldings number, the scalar-to-tensor ratio differs. We discuss the possible reasons behind this discrepancy, and we argue that the difference is due to some approximation we performed to the functional form of the potential in the Einstein frame, in order to obtain analytical results, and also due to the difference in the definition of the e -foldings number in the two frames, which is also pointed out in the related literature. Finally, we find the F (R ) gravity corresponding to the Einstein frame canonical scalar-tensor theory.
DEFF Research Database (Denmark)
Baber, Sikunder Ali
" and shows how a number of professional associations have become as networks of learning to encourage the continuing professional education of both pre-service and in-service teachers in the context of Pakistan. A case of the Mathematics Association of Pakistan (MAP) as a Network of Learning is presented....... The formation and growth of this network can be viewed as developing insights into the improvement of mathematics education in the developing world. The contributions of the association may also add value to the learning of teacher colleagues in other parts of the world. This sharing of the experience may......Importance of the professional development of teachers has been recognized and research has contributed greatly in terms of proposing variety of approaches for the development of teachers,both pre-service and in-service. Among them, networking among teachers, teacher educators,curriculum developers...
Continual and One-Shot Learning Through Neural Networks with Dynamic External Memory
DEFF Research Database (Denmark)
Lüders, Benno; Schläger, Mikkel; Korach, Aleksandra
2017-01-01
it easier to find unused memory location and therefor facilitates the evolution of continual learning networks. Our results suggest that augmenting evolving networks with an external memory component is not only a viable mechanism for adaptive behaviors in neuroevolution but also allows these networks...... a new task is learned. This paper takes a step in overcoming this limitation by building on the recently proposed Evolving Neural Turing Machine (ENTM) approach. In the ENTM, neural networks are augmented with an external memory component that they can write to and read from, which allows them to store...... associations quickly and over long periods of time. The results in this paper demonstrate that the ENTM is able to perform one-shot learning in reinforcement learning tasks without catastrophic forgetting of previously stored associations. Additionally, we introduce a new ENTM default jump mechanism that makes...
Merging Bottom-Up with Top-Down: Continuous Lamellar Networks and Block Copolymer Lithography
Campbell, Ian Patrick
Block copolymer lithography is an emerging nanopatterning technology with capabilities that may complement and eventually replace those provided by existing optical lithography techniques. This bottom-up process relies on the parallel self-assembly of macromolecules composed of covalently linked, chemically distinct blocks to generate periodic nanostructures. Among the myriad potential morphologies, lamellar structures formed by diblock copolymers with symmetric volume fractions have attracted the most interest as a patterning tool. When confined to thin films and directed to assemble with interfaces perpendicular to the substrate, two-dimensional domains are formed between the free surface and the substrate, and selective removal of a single block creates a nanostructured polymeric template. The substrate exposed between the polymeric features can subsequently be modified through standard top-down microfabrication processes to generate novel nanostructured materials. Despite tremendous progress in our understanding of block copolymer self-assembly, continuous two-dimensional materials have not yet been fabricated via this robust technique, which may enable nanostructured material combinations that cannot be fabricated through bottom-up methods. This thesis aims to study the effects of block copolymer composition and processing on the lamellar network morphology of polystyrene-block-poly(methyl methacrylate) (PS-b-PMMA) and utilize this knowledge to fabricate continuous two-dimensional materials through top-down methods. First, block copolymer composition was varied through homopolymer blending to explore the physical phenomena surrounding lamellar network continuity. After establishing a framework for tuning the continuity, the effects of various processing parameters were explored to engineer the network connectivity via defect annihilation processes. Precisely controlling the connectivity and continuity of lamellar networks through defect engineering and
McGeachie, Michael J; Chang, Hsun-Hsien; Weiss, Scott T
2014-06-01
Bayesian Networks (BN) have been a popular predictive modeling formalism in bioinformatics, but their application in modern genomics has been slowed by an inability to cleanly handle domains with mixed discrete and continuous variables. Existing free BN software packages either discretize continuous variables, which can lead to information loss, or do not include inference routines, which makes prediction with the BN impossible. We present CGBayesNets, a BN package focused around prediction of a clinical phenotype from mixed discrete and continuous variables, which fills these gaps. CGBayesNets implements Bayesian likelihood and inference algorithms for the conditional Gaussian Bayesian network (CGBNs) formalism, one appropriate for predicting an outcome of interest from, e.g., multimodal genomic data. We provide four different network learning algorithms, each making a different tradeoff between computational cost and network likelihood. CGBayesNets provides a full suite of functions for model exploration and verification, including cross validation, bootstrapping, and AUC manipulation. We highlight several results obtained previously with CGBayesNets, including predictive models of wood properties from tree genomics, leukemia subtype classification from mixed genomic data, and robust prediction of intensive care unit mortality outcomes from metabolomic profiles. We also provide detailed example analysis on public metabolomic and gene expression datasets. CGBayesNets is implemented in MATLAB and available as MATLAB source code, under an Open Source license and anonymous download at http://www.cgbayesnets.com.
Hyperbolic Plykin attractor can exist in neuron models
DEFF Research Database (Denmark)
Belykh, V.; Belykh, I.; Mosekilde, Erik
2005-01-01
Strange hyperbolic attractors are hard to find in real physical systems. This paper provides the first example of a realistic system, a canonical three-dimensional (3D) model of bursting neurons, that is likely to have a strange hyperbolic attractor. Using a geometrical approach to the study...... of the neuron model, we derive a flow-defined Poincare map giving ail accurate account of the system's dynamics. In a parameter region where the neuron system undergoes bifurcations causing transitions between tonic spiking and bursting, this two-dimensional map becomes a map of a disk with several periodic...... holes. A particular case is the map of a disk with three holes, matching the Plykin example of a planar hyperbolic attractor. The corresponding attractor of the 3D neuron model appears to be hyperbolic (this property is not verified in the present paper) and arises as a result of a two-loop (secondary...
Multi-wing hyperchaotic attractors from coupled Lorenz systems
International Nuclear Information System (INIS)
Grassi, Giuseppe; Severance, Frank L.; Miller, Damon A.
2009-01-01
This paper illustrates an approach to generate multi-wing attractors in coupled Lorenz systems. In particular, novel four-wing (eight-wing) hyperchaotic attractors are generated by coupling two (three) identical Lorenz systems. The paper shows that the equilibria of the proposed systems have certain symmetries with respect to specific coordinate planes and the eigenvalues of the associated Jacobian matrices exhibit the property of similarity. In analogy with the original Lorenz system, where the two-wings of the butterfly attractor are located around the two equilibria with the unstable pair of complex-conjugate eigenvalues, this paper shows that the four-wings (eight-wings) of these attractors are located around the four (eight) equilibria with two (three) pairs of unstable complex-conjugate eigenvalues.
International Nuclear Information System (INIS)
Fu Hailong; Jia Mingchun; Peng Guichu
2010-01-01
According to the characteristics of environmental gamma radiation monitoring and the requirement of nuclear power plant (NPP) developing, a new continuous environmental radiation monitoring system based on wireless sensor network (WSN) was presented. The basic concepts and application of WSN were introduced firstly. And then the characteristics of the new system were analyzed. At the same time the configuration of the WSN and the whole structure of the system were built. Finally, the crucial techniques used in system designing, such as the design of sensor node, the choice of communication mode and protocol, the time synchronization and space location, the security of the network and the faults tolerance were introduced. (authors)
Coexisting multiple attractors and riddled basins of a memristive system.
Wang, Guangyi; Yuan, Fang; Chen, Guanrong; Zhang, Yu
2018-01-01
In this paper, a new memristor-based chaotic system is designed, analyzed, and implemented. Multistability, multiple attractors, and complex riddled basins are observed from the system, which are investigated along with other dynamical behaviors such as equilibrium points and their stabilities, symmetrical bifurcation diagrams, and sustained chaotic states. With different sets of system parameters, the system can also generate various multi-scroll attractors. Finally, the system is realized by experimental circuits.
Attractor of reaction-diffusion equations in Banach spaces
Directory of Open Access Journals (Sweden)
José Valero
2001-04-01
Full Text Available In this paper we prove first some abstract theorems on existence of global attractors for differential inclusions generated by w-dissipative operators. Then these results are applied to reaction-diffusion equations in which the Babach space Lp is used as phase space. Finally, new results concerning the fractal dimension of the global attractor in the space L2 are obtained.
Revisiting non-Gaussianity from non-attractor inflation models
Cai, Yi-Fu; Chen, Xingang; Namjoo, Mohammad Hossein; Sasaki, Misao; Wang, Dong-Gang; Wang, Ziwei
2018-05-01
Non-attractor inflation is known as the only single field inflationary scenario that can violate non-Gaussianity consistency relation with the Bunch-Davies vacuum state and generate large local non-Gaussianity. However, it is also known that the non-attractor inflation by itself is incomplete and should be followed by a phase of slow-roll attractor. Moreover, there is a transition process between these two phases. In the past literature, this transition was approximated as instant and the evolution of non-Gaussianity in this phase was not fully studied. In this paper, we follow the detailed evolution of the non-Gaussianity through the transition phase into the slow-roll attractor phase, considering different types of transition. We find that the transition process has important effect on the size of the local non-Gaussianity. We first compute the net contribution of the non-Gaussianities at the end of inflation in canonical non-attractor models. If the curvature perturbations keep evolving during the transition—such as in the case of smooth transition or some sharp transition scenarios—the Script O(1) local non-Gaussianity generated in the non-attractor phase can be completely erased by the subsequent evolution, although the consistency relation remains violated. In extremal cases of sharp transition where the super-horizon modes freeze immediately right after the end of the non-attractor phase, the original non-attractor result can be recovered. We also study models with non-canonical kinetic terms, and find that the transition can typically contribute a suppression factor in the squeezed bispectrum, but the final local non-Gaussianity can still be made parametrically large.
Internal Waves and Wave Attractors in Enceladus' Subsurface Ocean
van Oers, A. M.; Maas, L. R.; Vermeersen, B. L. A.
2016-12-01
One of the most peculiar features on Saturn moon Enceladus is its so-called tiger stripe pattern at the geologically active South Polar Terrain (SPT), as first observed in detail by the Cassini spacecraft early 2005. It is generally assumed that the four almost parallel surface lines that constitute this pattern are faults in the icy surface overlying a confined salty water reservoir. In 2013, we formulated the original idea [Vermeersen et al., AGU Fall Meeting 2013, abstract #P53B-1848] that the tiger stripe pattern is formed and maintained by induced, tidally and rotationally driven, wave-attractor motions in the ocean underneath the icy surface of the tiger-stripe region. Such wave-attractor motions are observed in water tank experiments in laboratories on Earth and in numerical experiments [Maas et al., Nature, 338, 557-561, 1997; Drijfhout and Maas, J. Phys. Oceanogr., 37, 2740-2763, 2007; Hazewinkel et al., Phys. Fluids, 22, 107102, 2010]. Numerical simulations show the persistence of wave attractors for a range of ocean shapes and stratifications. The intensification of the wave field near the location of the surface reflections of wave attractors has been numerically and experimentally confirmed. We measured the forces a wave attractor exerts on a solid surface, near a reflection point. These reflection points would correspond to the location of the tiger stripes. Combining experiments and numerical simulations we conclude that (1) wave attractors can exist in Enceladus' subsurface sea, (2) their shape can be matched to the tiger stripes, (3) the wave attractors cause a localized force at the water-ice boundaries, (4) this force could have been large enough to contribute to fracturing the ice and (5) the wave attractors localize energy (and particles) and cause dissipation along its path, helping explain Enceladus' enigmatic heat output at the tiger stripes.
Integration of Continuous-Time Dynamics in a Spiking Neural Network Simulator
Directory of Open Access Journals (Sweden)
Jan Hahne
2017-05-01
Full Text Available Contemporary modeling approaches to the dynamics of neural networks include two important classes of models: biologically grounded spiking neuron models and functionally inspired rate-based units. We present a unified simulation framework that supports the combination of the two for multi-scale modeling, enables the quantitative validation of mean-field approaches by spiking network simulations, and provides an increase in reliability by usage of the same simulation code and the same network model specifications for both model classes. While most spiking simulations rely on the communication of discrete events, rate models require time-continuous interactions between neurons. Exploiting the conceptual similarity to the inclusion of gap junctions in spiking network simulations, we arrive at a reference implementation of instantaneous and delayed interactions between rate-based models in a spiking network simulator. The separation of rate dynamics from the general connection and communication infrastructure ensures flexibility of the framework. In addition to the standard implementation we present an iterative approach based on waveform-relaxation techniques to reduce communication and increase performance for large-scale simulations of rate-based models with instantaneous interactions. Finally we demonstrate the broad applicability of the framework by considering various examples from the literature, ranging from random networks to neural-field models. The study provides the prerequisite for interactions between rate-based and spiking models in a joint simulation.
Integration of Continuous-Time Dynamics in a Spiking Neural Network Simulator.
Hahne, Jan; Dahmen, David; Schuecker, Jannis; Frommer, Andreas; Bolten, Matthias; Helias, Moritz; Diesmann, Markus
2017-01-01
Contemporary modeling approaches to the dynamics of neural networks include two important classes of models: biologically grounded spiking neuron models and functionally inspired rate-based units. We present a unified simulation framework that supports the combination of the two for multi-scale modeling, enables the quantitative validation of mean-field approaches by spiking network simulations, and provides an increase in reliability by usage of the same simulation code and the same network model specifications for both model classes. While most spiking simulations rely on the communication of discrete events, rate models require time-continuous interactions between neurons. Exploiting the conceptual similarity to the inclusion of gap junctions in spiking network simulations, we arrive at a reference implementation of instantaneous and delayed interactions between rate-based models in a spiking network simulator. The separation of rate dynamics from the general connection and communication infrastructure ensures flexibility of the framework. In addition to the standard implementation we present an iterative approach based on waveform-relaxation techniques to reduce communication and increase performance for large-scale simulations of rate-based models with instantaneous interactions. Finally we demonstrate the broad applicability of the framework by considering various examples from the literature, ranging from random networks to neural-field models. The study provides the prerequisite for interactions between rate-based and spiking models in a joint simulation.
Li, Fei; Zhao, Wei; Guo, Ying
2018-01-01
Continuous-variable (CV) measurement-device-independent (MDI) quantum cryptography is now heading towards solving the practical problem of implementing scalable quantum networks. In this paper, we show that a solution can come from deploying an optical amplifier in the CV-MDI system, aiming to establish a high-rate quantum network. We suggest an improved CV-MDI protocol using the EPR states coupled with optical amplifiers. It can implement a practical quantum network scheme, where the legal participants create the secret correlations by using EPR states connecting to an untrusted relay via insecure links and applying the multi-entangled Greenberger-Horne-Zeilinger (GHZ) state analysis at relay station. Despite the possibility that the relay could be completely tampered with and imperfect links are subject to the powerful attacks, the legal participants are still able to extract a secret key from network communication. The numerical simulation indicates that the quantum network communication can be achieved in an asymmetric scenario, fulfilling the demands of a practical quantum network. Furthermore, we show that the use of optical amplifiers can compensate the inherent imperfections and improve the secret key rate of the CV-MDI system.
A Realistic Framework for Delay-Tolerant Network Routing in Open Terrains with Continuous Churn
Mahendran, Veeramani; Anirudh, Sivaraman K.; Murthy, C. Siva Ram
The conventional analysis of Delay-Tolerant Network (DTN) routing assumes that the terrain over which nodes move is closed implying that when the nodes hit a boundary, they either wrap around or get reflected. In this work, we study the effect of relaxing this closed terrain assumption on the routing performance, where a continuous stream of nodes enter the terrain and get absorbed upon hitting the boundary.
Oscillatory attractors: a new cosmological phase
Energy Technology Data Exchange (ETDEWEB)
Bains, Jasdeep S. [Center for the Fundamental Laws of Nature, Harvard University, 17 Oxford St, Cambridge, MA 02138 (United States); Hertzberg, Mark P. [Institute of Cosmology, Department of Physics and Astronomy, Tufts University, 574 Boston Ave, Medford, MA 02155 (United States); Wilczek, Frank, E-mail: bains@physics.harvard.edu, E-mail: mark.hertzberg@tufts.edu, E-mail: wilczek@mit.edu [Center for Theoretical Physics, Department of Physics, MIT, 77 Massachusetts Ave, Cambridge, MA 02139 (United States)
2017-05-01
In expanding FRW spacetimes, it is usually the case that homogeneous scalar fields redshift and their amplitudes approach limiting values: Hubble friction usually ensures that the field relaxes to its minimum energy configuration, which is usually a static configuration. Here we discover a class of relativistic scalar field models in which the attractor behavior is the field oscillating indefinitely, with finite amplitude, in an expanding FRW spacetime, despite the presence of Hubble friction. This is an example of spontaneous breaking of time translation symmetry. We find that the effective equation of state of the field has average value ( w )=−1, implying that the field itself could drive an inflationary or dark energy dominated phase. This behavior is reminiscent of ghost condensate models, but in the new models, unlike in the ghost condensate models, the energy-momentum tensor is time dependent, so that these new models embody a more definitive breaking of time translation symmetry. We explore (quantum) fluctuations around the homogeneous background solution, and find that low k -modes can be stable, while high k -modes are typically unstable. We discuss possible interpretations and implications of that instability.
Quintessential inflation with α-attractors
Energy Technology Data Exchange (ETDEWEB)
Dimopoulos, Konstantinos; Owen, Charlotte, E-mail: k.dimopoulos1@lancaster.ac.uk, E-mail: c.owen@lancaster.ac.uk [Consortium for Fundamental Physics, Physics Department, Lancaster University, Lancaster LA1 4YB (United Kingdom)
2017-06-01
A novel approach to quintessential inflation model building is studied, within the framework of α-attractors, motivated by supergravity theories. Inflationary observables are in excellent agreement with the latest CMB observations, while quintessence explains the dark energy observations without any fine-tuning. The model is kept intentionally minimal, avoiding the introduction of many degrees of freedom, couplings and mass scales. In stark contrast to ΛCDM, for natural values of the parameters, the model attains transient accelerated expansion, which avoids the future horizon problem, while it maintains the field displacement mildly sub-Planckian such that the flatness of the quintessential tail is not lifted by radiative corrections and violations of the equivalence principle (fifth force) are under control. In particular, the required value of the cosmological constant is near the eletroweak scale. Attention is paid to the reheating of the Universe, which avoids gravitino overproduction and respects nucleosynthesis constraints. Kination is treated in a model independent way. A spike in gravitational waves, due to kination, is found not to disturb nucleosynthesis as well.
Fibre inflation and α-attractors
Kallosh, Renata; Linde, Andrei; Roest, Diederik; Westphal, Alexander; Yamada, Yusuke
2018-02-01
Fibre inflation is a specific string theory construction based on the Large Volume Scenario that produces an inflationary plateau. We outline its relation to α-attractor models for inflation, with the cosmological sector originating from certain string theory corrections leading to α = 2 and α = 1/2. Above a certain field range, the steepening effect of higher-order corrections leads first to the breakdown of single-field slow-roll and after that to the onset of 2-field dynamics: the overall volume of the extra dimensions starts to participate in the effective dynamics. Finally, we propose effective supergravity models of fibre inflation based on an \\overline{D3} uplift term with a nilpotent superfield. Specific moduli dependent \\overline{D3} induced geometries lead to cosmological fibre models but have in addition a de Sitter minimum exit. These supergravity models motivated by fibre inflation are relatively simple, stabilize the axions and disentangle the Hubble parameter from supersymmetry breaking.
Directory of Open Access Journals (Sweden)
Caroline S Wagner
Full Text Available Global collaboration continues to grow as a share of all scientific cooperation, measured as coauthorships of peer-reviewed, published papers. The percent of all scientific papers that are internationally coauthored has more than doubled in 20 years, and they account for all the growth in output among the scientifically advanced countries. Emerging countries, particularly China, have increased their participation in global science, in part by doubling their spending on R&D; they are increasingly likely to appear as partners on internationally coauthored scientific papers. Given the growth of connections at the international level, it is helpful to examine the phenomenon as a communications network and to consider the network as a new organization on the world stage that adds to and complements national systems. When examined as interconnections across the globe over two decades, a global network has grown denser but not more clustered, meaning there are many more connections but they are not grouping into exclusive 'cliques'. This suggests that power relationships are not reproducing those of the political system. The network has features an open system, attracting productive scientists to participate in international projects. National governments could gain efficiencies and influence by developing policies and strategies designed to maximize network benefits-a model different from those designed for national systems.
Osama, Ahmed; Sayed, Tarek
2017-10-01
With the increasing demand for sustainability, walking is being encouraged as one of the main active modes of transportation. However, pedestrians are vulnerable to severe injuries when involved in crashes which can discourage road users from walking. Therefore, studying factors that affect the safety of pedestrians is important. This paper investigates the relationship between pedestrian-motorist crashes and various sidewalk network indicators in the city of Vancouver. The goal is to assess the impact of network connectivity, directness, and topography on pedestrian safety using macro-level collision prediction models. The models were developed using generalized linear regression and full Bayesian techniques. Both walking trips and vehicle kilometers travelled were used as the main traffic exposure variables in the models. The safety models supported the safety in numbers hypothesis showing a non-linear positive association between pedestrian-motorist crashes and the increase in walking trips and vehicle traffic. The model results also suggested that higher continuity, linearity, coverage, and slope of sidewalk networks were associated with lower crash occurrence. However, network connectivity was associated with higher crash occurrence. The spatial effects were accounted for in the full Bayes models and were found significant. The models provide insights about the factors that influence pedestrian safety and the spatial variability of pedestrian crashes within a city, which can be useful for the planning of pedestrian networks. Copyright © 2017 Elsevier Ltd. All rights reserved.
Non-linguistic Conditions for Causativization as a Linguistic Attractor.
Nichols, Johanna
2017-01-01
An attractor, in complex systems theory, is any state that is more easily or more often entered or acquired than departed or lost; attractor states therefore accumulate more members than non-attractors, other things being equal. In the context of language evolution, linguistic attractors include sounds, forms, and grammatical structures that are prone to be selected when sociolinguistics and language contact make it possible for speakers to choose between competing forms. The reasons why an element is an attractor are linguistic (auditory salience, ease of processing, paradigm structure, etc.), but the factors that make selection possible and propagate selected items through the speech community are non-linguistic. This paper uses the consonants in personal pronouns to show what makes for an attractor and how selection and diffusion work, then presents a survey of several language families and areas showing that the derivational morphology of pairs of verbs like fear and frighten , or Turkish korkmak 'fear, be afraid' and korkutmak 'frighten, scare', or Finnish istua 'sit' and istutta 'seat (someone)', or Spanish sentarse 'sit down' and sentar 'seat (someone)' is susceptible to selection. Specifically, the Turkish and Finnish pattern, where 'seat' is derived from 'sit' by addition of a suffix-is an attractor and a favored target of selection. This selection occurs chiefly in sociolinguistic contexts of what is defined here as linguistic symbiosis, where languages mingle in speech, which in turn is favored by certain demographic, sociocultural, and environmental factors here termed frontier conditions. Evidence is surveyed from northern Eurasia, the Caucasus, North and Central America, and the Pacific and from both modern and ancient languages to raise the hypothesis that frontier conditions and symbiosis favor causativization.
Non-linguistic Conditions for Causativization as a Linguistic Attractor
Directory of Open Access Journals (Sweden)
Johanna Nichols
2018-01-01
Full Text Available An attractor, in complex systems theory, is any state that is more easily or more often entered or acquired than departed or lost; attractor states therefore accumulate more members than non-attractors, other things being equal. In the context of language evolution, linguistic attractors include sounds, forms, and grammatical structures that are prone to be selected when sociolinguistics and language contact make it possible for speakers to choose between competing forms. The reasons why an element is an attractor are linguistic (auditory salience, ease of processing, paradigm structure, etc., but the factors that make selection possible and propagate selected items through the speech community are non-linguistic. This paper uses the consonants in personal pronouns to show what makes for an attractor and how selection and diffusion work, then presents a survey of several language families and areas showing that the derivational morphology of pairs of verbs like fear and frighten, or Turkish korkmak ‘fear, be afraid’ and korkutmak ‘frighten, scare’, or Finnish istua ‘sit’ and istutta ‘seat (someone’, or Spanish sentarse ‘sit down’ and sentar ‘seat (someone’ is susceptible to selection. Specifically, the Turkish and Finnish pattern, where ‘seat’ is derived from ‘sit’ by addition of a suffix—is an attractor and a favored target of selection. This selection occurs chiefly in sociolinguistic contexts of what is defined here as linguistic symbiosis, where languages mingle in speech, which in turn is favored by certain demographic, sociocultural, and environmental factors here termed frontier conditions. Evidence is surveyed from northern Eurasia, the Caucasus, North and Central America, and the Pacific and from both modern and ancient languages to raise the hypothesis that frontier conditions and symbiosis favor causativization.
D'Angelo, Lorenzo T; Schneider, Michael; Neugebauer, Paul; Lueth, Tim C
2011-01-01
In this contribution, a new concept for interfacing sensor network nodes (motes) and smartphones is presented for the first time. In the last years, a variety of telemedicine applications on smartphones for data reception, display and transmission have been developed. However, it is not always practical or possible to have a smartphone application running continuously to accomplish these tasks. The presented system allows receiving and storing data continuously using a mote and visualizing or sending it on the go using the smartphone as user interface only when desired. Thus, the processes of data reception and storage run on a safe system consuming less energy and the smartphone's potential along with its battery are not demanded continuously. Both, system concept and realization with an Apple iPhone are presented.
3D position estimation using an artificial neural network for a continuous scintillator PET detector
International Nuclear Information System (INIS)
Wang, Y; Zhu, W; Cheng, X; Li, D
2013-01-01
Continuous crystal based PET detectors have features of simple design, low cost, good energy resolution and high detection efficiency. Through single-end readout of scintillation light, direct three-dimensional (3D) position estimation could be another advantage that the continuous crystal detector would have. In this paper, we propose to use artificial neural networks to simultaneously estimate the plane coordinate and DOI coordinate of incident γ photons with detected scintillation light. Using our experimental setup with an ‘8 + 8’ simplified signal readout scheme, the training data of perpendicular irradiation on the front surface and one side surface are obtained, and the plane (x, y) networks and DOI networks are trained and evaluated. The test results show that the artificial neural network for DOI estimation is as effective as for plane estimation. The performance of both estimators is presented by resolution and bias. Without bias correction, the resolution of the plane estimator is on average better than 2 mm and that of the DOI estimator is about 2 mm over the whole area of the detector. With bias correction, the resolution at the edge area for plane estimation or at the end of the block away from the readout PMT for DOI estimation becomes worse, as we expect. The comprehensive performance of the 3D positioning by a neural network is accessed by the experimental test data of oblique irradiations. To show the combined effect of the 3D positioning over the whole area of the detector, the 2D flood images of oblique irradiation are presented with and without bias correction. (paper)
β-expansion attractors observed in A/D converters
Kohda, Tohru; Horio, Yoshihiko; Aihara, Kazuyuki
2012-12-01
The recently proposed β-encoders, analog-to-digital converters using an amplifier with a factor β and a flaky quantizer with threshold ν, have proven to be explained by the deterministic dynamics of multi-valued Rényi-Parry maps. Such a map is locally eventually onto [ν-1, ν), which is topologically conjugate to Parry's (β,α)-map with α =(β-1)(ν-1). This implies that β-encoders have a closed subinterval [ν-1,ν), which includes an attractor. Thus, the iteration of the multi-valued Rényi-Parry map performs the β-expansion of x while quantization errors in β-encoders behave chaotically and do not converge to a fixed point. This β-expansion attractor is relatively simpler than previously reported attractors. The object of this paper is twofold: to observe the embedded attractors in the β-encoder and to identify attractors that are useful for spread-spectrum codes and optimization techniques using pseudo-random numbers.
E-I balance emerges naturally from continuous Hebbian learning in autonomous neural networks.
Trapp, Philip; Echeveste, Rodrigo; Gros, Claudius
2018-06-12
Spontaneous brain activity is characterized in part by a balanced asynchronous chaotic state. Cortical recordings show that excitatory (E) and inhibitory (I) drivings in the E-I balanced state are substantially larger than the overall input. We show that such a state arises naturally in fully adapting networks which are deterministic, autonomously active and not subject to stochastic external or internal drivings. Temporary imbalances between excitatory and inhibitory inputs lead to large but short-lived activity bursts that stabilize irregular dynamics. We simulate autonomous networks of rate-encoding neurons for which all synaptic weights are plastic and subject to a Hebbian plasticity rule, the flux rule, that can be derived from the stationarity principle of statistical learning. Moreover, the average firing rate is regulated individually via a standard homeostatic adaption of the bias of each neuron's input-output non-linear function. Additionally, networks with and without short-term plasticity are considered. E-I balance may arise only when the mean excitatory and inhibitory weights are themselves balanced, modulo the overall activity level. We show that synaptic weight balance, which has been considered hitherto as given, naturally arises in autonomous neural networks when the here considered self-limiting Hebbian synaptic plasticity rule is continuously active.
Directory of Open Access Journals (Sweden)
Tuan Anh Nguyen
2015-01-01
Full Text Available Sensitivity assessment of availability for data center networks (DCNs is of paramount importance in design and management of cloud computing based businesses. Previous work has presented a performance modeling and analysis of a fat-tree based DCN using queuing theory. In this paper, we present a comprehensive availability modeling and sensitivity analysis of a DCell-based DCN with server virtualization for business continuity using stochastic reward nets (SRN. We use SRN in modeling to capture complex behaviors and dependencies of the system in detail. The models take into account (i two DCell configurations, respectively, composed of two and three physical hosts in a DCell0 unit, (ii failure modes and corresponding recovery behaviors of hosts, switches, and VMs, and VM live migration mechanism within and between DCell0s, and (iii dependencies between subsystems (e.g., between a host and VMs and between switches and VMs in the same DCell0. The constructed SRN models are analyzed in detail with regard to various metrics of interest to investigate system’s characteristics. A comprehensive sensitivity analysis of system availability is carried out in consideration of the major impacting parameters in order to observe the system’s complicated behaviors and find the bottlenecks of system availability. The analysis results show the availability improvement, capability of fault tolerance, and business continuity of the DCNs complying with DCell network topology. This study provides a basis of designing and management of DCNs for business continuity.
Directory of Open Access Journals (Sweden)
Yasser Roudi
2007-09-01
Full Text Available A fundamental problem in neuroscience is understanding how working memory--the ability to store information at intermediate timescales, like tens of seconds--is implemented in realistic neuronal networks. The most likely candidate mechanism is the attractor network, and a great deal of effort has gone toward investigating it theoretically. Yet, despite almost a quarter century of intense work, attractor networks are not fully understood. In particular, there are still two unanswered questions. First, how is it that attractor networks exhibit irregular firing, as is observed experimentally during working memory tasks? And second, how many memories can be stored under biologically realistic conditions? Here we answer both questions by studying an attractor neural network in which inhibition and excitation balance each other. Using mean-field analysis, we derive a three-variable description of attractor networks. From this description it follows that irregular firing can exist only if the number of neurons involved in a memory is large. The same mean-field analysis also shows that the number of memories that can be stored in a network scales with the number of excitatory connections, a result that has been suggested for simple models but never shown for realistic ones. Both of these predictions are verified using simulations with large networks of spiking neurons.
Bi-Criteria System Optimum Traffic Assignment in Networks With Continuous Value of Time
Directory of Open Access Journals (Sweden)
Xin Wang
2013-04-01
Full Text Available For an elastic demand transportation network with continuously distributed value of time, the system disutility can be measured either in time units or in cost units. The user equilibrium model and the system optimization model are each formulated in two different criteria. The conditions required for making the system optimum link flow pattern equivalent to the user equilibrium link flow pattern are derived. Furthermore, a bi-objective model has been developed which minimizes simultaneously the system travel time and the system travel cost. The existence of a pricing scheme with anonymous link tolls which can decentralize a Pareto system optimum into the user equilibrium has been investigated.
Dynamical chaos and uniformly hyperbolic attractors: from mathematics to physics
Energy Technology Data Exchange (ETDEWEB)
Kuznetsov, Sergei P [Saratov Branch, Kotel' nikov Institute of Radio Engineering and Electronics, Russian Academy of Sciences, Saratov (Russian Federation)
2011-02-28
Research is reviewed on the identification and construction of physical systems with chaotic dynamics due to uniformly hyperbolic attractors (such as the Plykin attraction or the Smale-Williams solenoid). Basic concepts of the mathematics involved and approaches proposed in the literature for constructing systems with hyperbolic attractors are discussed. Topics covered include periodic pulse-driven models; dynamics models consisting of periodically repeated stages, each described by its own differential equations; the construction of systems of alternately excited coupled oscillators; the use of parametrically excited oscillations; and the introduction of delayed feedback. Some maps, differential equations, and simple mechanical and electronic systems exhibiting chaotic dynamics due to the presence of uniformly hyperbolic attractors are presented as examples. (reviews of topical problems)
The dimension of attractors underlying periodic turbulent Poiseuille flow
Keefe, Laurence; Moin, Parviz; Kim, John
1992-01-01
A lower bound on the Liapunov dimenison, D-lambda, of the attractor underlying turbulent, periodic Poiseuille flow at a pressure-gradient Reynolds number of 3200 is calculated, on the basis of a coarse-grained (16x33x8) numerical solution, to be approximately 352. Comparison of Liapunov exponent spectra from this and a higher-resolution (16x33x16) simulation on the same spatial domain shows these spectra to have a universal shape when properly scaled. On the basis of these scaling properties, and a partial exponent spectrum from a still higher-resolution (32x33x32) simulation, it is argued that the actual dimension of the attractor underlying motion of the given computational domain is approximately 780. It is suggested that this periodic turbulent shear flow is deterministic chaos, and that a strange attractor does underly solutions to the Navier-Stokes equations in such flows.
Strange attractors in weakly turbulent Couette-Taylor flow
Brandstater, A.; Swinney, Harry L.
1987-01-01
An experiment is conducted on the transition from quasi-periodic to weakly turbulent flow of a fluid contained between concentric cylinders with the inner cylinder rotating and the outer cylinder at rest. Power spectra, phase-space portraits, and circle maps obtained from velocity time-series data indicate that the nonperiodic behavior observed is deterministic, that is, it is described by strange attractors. Various problems that arise in computing the dimension of strange attractors constructed from experimental data are discussed and it is shown that these problems impose severe requirements on the quantity and accuracy of data necessary for determining dimensions greater than about 5. In the present experiment the attractor dimension increases from 2 at the onset of turbulence to about 4 at a Reynolds number 50-percent above the onset of turbulence.
Continuity of care in the Health Care Network: negotiation between users and professionals
Directory of Open Access Journals (Sweden)
Maria Denise Schimith
2014-12-01
Full Text Available This study aimed to identify the negotiation and shared decision-making between professionals and users in a Family Health Unit and its influence on the continuity of care in the Health Care Network. Qualitative research created from a case study. One conducted 19 interviews, observation and document research. It was developed in a city in the countryside of Rio Grande do Sul, Brazil, in 2012. The results show that decisions used to happen unilaterally and that users and professionals looked for alternative ways to the continuity of care. It was not possible to identify the negotiation between professional and users and it was noticed that the user was alone looking for access. It is understood that primary care in the city researched needs to take responsibility for users and their access.
Attractors of equations of non-Newtonian fluid dynamics
International Nuclear Information System (INIS)
Zvyagin, V G; Kondrat'ev, S K
2014-01-01
This survey describes a version of the trajectory-attractor method, which is applied to study the limit asymptotic behaviour of solutions of equations of non-Newtonian fluid dynamics. The trajectory-attractor method emerged in papers of the Russian mathematicians Vishik and Chepyzhov and the American mathematician Sell under the condition that the corresponding trajectory spaces be invariant under the translation semigroup. The need for such an approach was caused by the fact that for many equations of mathematical physics for which the Cauchy initial-value problem has a global (weak) solution with respect to the time, the uniqueness of such a solution has either not been established or does not hold. In particular, this is the case for equations of fluid dynamics. At the same time, trajectory spaces invariant under the translation semigroup could not be constructed for many equations of non-Newtonian fluid dynamics. In this connection, a different approach to the construction of trajectory attractors for dissipative systems was proposed in papers of Zvyagin and Vorotnikov without using invariance of trajectory spaces under the translation semigroup and is based on the topological lemma of Shura-Bura. This paper presents examples of equations of non-Newtonian fluid dynamics (the Jeffreys system describing movement of the Earth's crust, the model of motion of weak aqueous solutions of polymers, a system with memory) for which the aforementioned construction is used to prove the existence of attractors in both the autonomous and the non-autonomous cases. At the beginning of the paper there is also a brief exposition of the results of Ladyzhenskaya on the existence of attractors of the two-dimensional Navier-Stokes system and the result of Vishik and Chepyzhov for the case of attractors of the three-dimensional Navier-Stokes system. Bibliography: 34 titles
Coexisting chaotic attractors in a single neuron model with adapting feedback synapse
International Nuclear Information System (INIS)
Li Chunguang; Chen Guanrong
2005-01-01
In this paper, we consider the nonlinear dynamical behavior of a single neuron model with adapting feedback synapse, and show that chaotic behaviors exist in this model. In some parameter domain, we observe two coexisting chaotic attractors, switching from the coexisting chaotic attractors to a connected chaotic attractor, and then switching back to the two coexisting chaotic attractors. We confirm the chaoticity by simulations with phase plots, waveform plots, and power spectra
Cabral-Cano, E.; Salazar-Tlaczani, L.; Adams, D. K.; Vivoni, E. R.; Grutter, M.; Serra, Y. L.; DeMets, C.; Galetzka, J.; Feaux, K.; Mattioli, G. S.; Miller, M. M.
2017-12-01
TLALOCNet is a network of continuous GPS and meteorology stations in Mexico to study atmospheric and solid earth processes. This recently completed network spans most of Mexico with a strong coverage emphasis on southern and western Mexico. This network, funded by NSF, CONACyT and UNAM, recently built 40 cGPS-Met sites to EarthScope Plate Boundary Observatory standards and upgraded 25 additional GPS stations. TLALOCNet provides open and freely available raw GPS data, and high frequency surface meteorology measurements, and time series of daily positions. This is accomplished through the development of the TLALOCNet data center (http://tlalocnet.udg.mx) that serves as a collection and distribution point. This data center is based on UNAVCO's Dataworks-GSAC software and also works as part of UNAVCO's seamless archive for discovery, sharing, and access to GPS data. The TLALOCNet data center also contains contributed data from several regional GPS networks in Mexico for a total of 100+ stations. By using the same protocols and structure as the UNAVCO and other COCONet regional data centers, the scientific community has the capability of accessing data from the largest Mexican GPS network. This archive provides a fully queryable and scriptable GPS and Meteorological data retrieval point. In addition, real-time 1Hz streams from selected TLALOCNet stations are available in BINEX, RTCM 2.3 and RTCM 3.1 formats via the Networked Transport of RTCM via Internet Protocol (NTRIP) for real-time seismic and weather forecasting applications. TLALOCNet served as a GPS-Met backbone for the binational Mexico-US North American Monsoon GPS Hydrometeorological Network 2017 campaign experiment. This innovative experiment attempts to address water vapor source regions and land-surface water vapor flux contributions to precipitation (i.e., moisture recycling) during the 2017 North American Monsoon in Baja California, Sonora, Chihuahua, and Arizona. Models suggest that moisture recycling is
Analysis of chaos attractors of MCG-recordings.
Jiang, Shiqin; Yang, Fan; Yi, Panke; Chen, Bo; Luo, Ming; Wang, Lemin
2006-01-01
By studying the chaos attractor of cardiac magnetic induction strength B(z) generated by the electrical activity of the heart, we found that its projection in the reconstructed phase space has a similar shape with the map of the total current dipole vector. It is worth noting that the map of the total current dipole vector is computed with MCG recordings measured at 36 locations, whereas the chaos attractor of B(z) is generated by only one cardiac magnetic field recordings on the measured plan. We discuss only two subjects of different ages in this paper.
Strange attractor in the Potts spin glass on hierarchical lattices
Energy Technology Data Exchange (ETDEWEB)
Lima, Washington de [Universidade Federal de Pernambuco, Centro Acadêmico do Agreste, Pernambuco (Brazil); Camelo-Neto, G. [Universidade Federal de Alagoas, Núcleo de Ciências Exatas, Laboratório de Física Teórica e Computacional, CEP 57309-005 Arapiraca, Alagoas (Brazil); Coutinho, S., E-mail: sergio@ufpe.br [Universidade Federal de Pernambuco, Departamento de Física, Laboratório de Física Teórica e Computacional, Cidade Universitária, CEP 50670-901 Recife, Pernambuco (Brazil)
2013-11-29
The spin-glass q-state Potts model on d-dimensional diamond hierarchical lattices is investigated by an exact real space renormalization group scheme. Above a critical dimension d{sub l}(q) for q>2, the coupling constants probability distribution flows to a low-temperature strange attractor or to the high-temperature paramagnetic fixed point, according to the temperature is below or above the critical temperature T{sub c}(q,d). The strange attractor was investigated considering four initial different distributions for q=3 and d=5 presenting strong robustness in shape and temperature interval suggesting a condensed phase with algebraic decay.
STRANGE ATTRACTORS ON PSEUDOSPECTRAL SOLUTIONS FOR DISSIPATIVE ZAKHAROV EQUATIONS
Institute of Scientific and Technical Information of China (English)
马书清; 常谦顺
2004-01-01
In this paper, the pseudospcctral method to solve the dissipative Zakharov equations is used. Its convergence is proved by priori estinates. The existence of the global attractors and the estimates of dimension are presented. A class of steady state solutions is also disscussed. The numerical results show that if the steady state solutions satisfy some special conditions, they become unstable and limit cycles and strange attractors will occur for very small perturbations.The largest Lyapunov exponent and analysis of the lincarized system are applied to explain these phenomena.
Statistical properties of chaotic dynamical systems which exhibit strange attractors
International Nuclear Information System (INIS)
Jensen, R.V.; Oberman, C.R.
1981-07-01
A path integral method is developed for the calculation of the statistical properties of turbulent dynamical systems. The method is applicable to conservative systems which exhibit a transition to stochasticity as well as dissipative systems which exhibit strange attractors. A specific dissipative mapping is considered in detail which models the dynamics of a Brownian particle in a wave field with a broad frequency spectrum. Results are presented for the low order statistical moments for three turbulent regimes which exhibit strange attractors corresponding to strong, intermediate, and weak collisional damping
Simplified Chua's attractor via bridging a diode pair
Directory of Open Access Journals (Sweden)
Quan Xu
2015-04-01
Full Text Available In this paper, a simplified Chua's circuit is realised by bridging a diode pair between a passive LC (inductance and capacitance in parallel connection - LC oscillator and an active RC (resistance and capacitance in parallel connection - RC filter. The dynamical behaviours of the circuit are investigated by numerical simulations and verified by experimental measurements. It is found that the simplified Chua's circuit generates Chua's attractors similarly and demonstrates complex non-linear phenomena including coexisting bifurcation modes and coexisting attractors in particular.
Prediction of hot-ductility of steels during continuous casting using artificial neural networks
International Nuclear Information System (INIS)
Liu, W.J.; Emadi, D.; Essadiqi, E.
2000-01-01
During continuous casting, transversal cracks can be developed due to tensile stress in temperature regions where the steel exhibits a low ductility. The cracking tendency during continuous casting depends on the steel chemistry and the casting parameters such as lubrication, mold type, secondary cooling and bending/unbending temperatures. To prevent cracking one needs to predict the hot-ductility of a material under continuous-casting conditions. However, hot-ductility is one of the poorly understood material behaviors and cannot be readily modeled using conventional techniques. In the present study, we used an alternative method, namely Artificial Neural Networks (ANN), to model the ductility of a steel under continuous casting conditions. A hot-ductility database was established based on published literature. Several standard three-layer ANN models were then trained using data randomly selected from the database. The outputs of the ANN models were subsequently compared with the remaining data in the database. The results indicate that ANN is a suitable modelling technique for hot-ductility prediction. (author)
Continuous Timescale Long-Short Term Memory Neural Network for Human Intent Understanding
Directory of Open Access Journals (Sweden)
Zhibin Yu
2017-08-01
Full Text Available Understanding of human intention by observing a series of human actions has been a challenging task. In order to do so, we need to analyze longer sequences of human actions related with intentions and extract the context from the dynamic features. The multiple timescales recurrent neural network (MTRNN model, which is believed to be a kind of solution, is a useful tool for recording and regenerating a continuous signal for dynamic tasks. However, the conventional MTRNN suffers from the vanishing gradient problem which renders it impossible to be used for longer sequence understanding. To address this problem, we propose a new model named Continuous Timescale Long-Short Term Memory (CTLSTM in which we inherit the multiple timescales concept into the Long-Short Term Memory (LSTM recurrent neural network (RNN that addresses the vanishing gradient problem. We design an additional recurrent connection in the LSTM cell outputs to produce a time-delay in order to capture the slow context. Our experiments show that the proposed model exhibits better context modeling ability and captures the dynamic features on multiple large dataset classification tasks. The results illustrate that the multiple timescales concept enhances the ability of our model to handle longer sequences related with human intentions and hence proving to be more suitable for complex tasks, such as intention recognition.
Pellerin, Brian; Stauffer, Beth A; Young, Dwane A; Sullivan, Daniel J.; Bricker, Suzanne B.; Walbridge, Mark R; Clyde, Gerard A; Shaw, Denice M
2016-01-01
Sensors and enabling technologies are becoming increasingly important tools for water quality monitoring and associated water resource management decisions. In particular, nutrient sensors are of interest because of the well-known adverse effects of nutrient enrichment on coastal hypoxia, harmful algal blooms, and impacts to human health. Accurate and timely information on nutrient concentrations and loads is integral to strategies designed to minimize risk to humans and manage the underlying drivers of water quality impairment. Using nitrate sensors as an example, we highlight the types of applications in freshwater and coastal environments that are likely to benefit from continuous, real-time nutrient data. The concurrent emergence of new tools to integrate, manage and share large data sets is critical to the successful use of nutrient sensors and has made it possible for the field of continuous nutrient monitoring to rapidly move forward. We highlight several near-term opportunities for Federal agencies, as well as the broader scientific and management community, that will help accelerate sensor development, build and leverage sites within a national network, and develop open data standards and data management protocols that are key to realizing the benefits of a large-scale, integrated monitoring network. Investing in these opportunities will provide new information to guide management and policies designed to protect and restore our nation’s water resources.
A scalable and continuous-upgradable optical wireless and wired convergent access network.
Sung, J Y; Cheng, K T; Chow, C W; Yeh, C H; Pan, C-L
2014-06-02
In this work, a scalable and continuous upgradable convergent optical access network is proposed. By using a multi-wavelength coherent comb source and a programmable waveshaper at the central office (CO), optical millimeter-wave (mm-wave) signals of different frequencies (from baseband to > 100 GHz) can be generated. Hence, it provides a scalable and continuous upgradable solution for end-user who needs 60 GHz wireless services now and > 100 GHz wireless services in the future. During the upgrade, user only needs to upgrade their optical networking unit (ONU). A programmable waveshaper is used to select the suitable optical tones with wavelength separation equals to the desired mm-wave frequency; while the CO remains intact. The centralized characteristics of the proposed system can easily add any new service and end-user. The centralized control of the wavelength makes the system more stable. Wired data rate of 17.45 Gb/s and w-band wireless data rate up to 3.36 Gb/s were demonstrated after transmission over 40 km of single-mode fiber (SMF).
Directory of Open Access Journals (Sweden)
Abednico Montshiwa
2016-02-01
Full Text Available This paper presents an optimized diamond structured automobile supply chain network towards a robust Business Continuity Management model. The model is necessitated by the nature of the automobile supply chain. Companies in tier two are centralized and numerically limited and have to supply multiple tier one companies with goods and services. The challenge with this supply chain structure is the inherent risks in the supply chain. Once supply chain disruption takes place at tier 2 level, the whole supply chain network suffers huge loses. To address this challenge, the paper replaces Risk Analysis with Risk Ranking and it introduces Supply Chain Cooperation (SCC to the traditional Business Continuity Plan (BCP concept. The paper employed three statistical analysis techniques (correlation analysis, regression analysis and Smart PLS 3.0 calculations. In this study, correlation and regression analysis results on risk rankings, SCC and Business Impact Analysis were significant, ascertaining the value of the model. The multivariate data analysis calculations demonstrated that SCC has a positive total significant effect on risk rankings and BCM while BIA has strongest positive effects on all BCP factors. Finally, sensitivity analysis demonstrated that company size plays a role in BCM.
Assimilation of Spatially Sparse In Situ Soil Moisture Networks into a Continuous Model Domain
Gruber, A.; Crow, W. T.; Dorigo, W. A.
2018-02-01
Growth in the availability of near-real-time soil moisture observations from ground-based networks has spurred interest in the assimilation of these observations into land surface models via a two-dimensional data assimilation system. However, the design of such systems is currently hampered by our ignorance concerning the spatial structure of error afflicting ground and model-based soil moisture estimates. Here we apply newly developed triple collocation techniques to provide the spatial error information required to fully parameterize a two-dimensional (2-D) data assimilation system designed to assimilate spatially sparse observations acquired from existing ground-based soil moisture networks into a spatially continuous Antecedent Precipitation Index (API) model for operational agricultural drought monitoring. Over the contiguous United States (CONUS), the posterior uncertainty of surface soil moisture estimates associated with this 2-D system is compared to that obtained from the 1-D assimilation of remote sensing retrievals to assess the value of ground-based observations to constrain a surface soil moisture analysis. Results demonstrate that a fourfold increase in existing CONUS ground station density is needed for ground network observations to provide a level of skill comparable to that provided by existing satellite-based surface soil moisture retrievals.
Directory of Open Access Journals (Sweden)
Hyung-Ju Cho
2012-01-01
Full Text Available Given two positive parameters k and r, a constrained k-nearest neighbor (CkNN query returns the k closest objects within a network distance r of the query location in road networks. In terms of the scalability of monitoring these CkNN queries, existing solutions based on central processing at a server suffer from a sudden and sharp rise in server load as well as messaging cost as the number of queries increases. In this paper, we propose a distributed and scalable scheme called DAEMON for the continuous monitoring of CkNN queries in road networks. Our query processing is distributed among clients (query objects and server. Specifically, the server evaluates CkNN queries issued at intersections of road segments, retrieves the objects on the road segments between neighboring intersections, and sends responses to the query objects. Finally, each client makes its own query result using this server response. As a result, our distributed scheme achieves close-to-optimal communication costs and scales well to large numbers of monitoring queries. Exhaustive experimental results demonstrate that our scheme substantially outperforms its competitor in terms of query processing time and messaging cost.
Directory of Open Access Journals (Sweden)
Songchao Xue
Full Text Available The topology of the cerebral vasculature, which is the energy transport corridor of the brain, can be used to study cerebral circulatory pathways. Limited by the restrictions of the vascular markers and imaging methods, studies on cerebral vascular structure now mainly focus on either observation of the macro vessels in a whole brain or imaging of the micro vessels in a small region. Simultaneous vascular studies of arteries, veins and capillaries have not been achieved in the whole brain of mammals. Here, we have combined the improved gelatin-Indian ink vessel perfusion process with Micro-Optical Sectioning Tomography for imaging the vessel network of an entire mouse brain. With 17 days of work, an integral dataset for the entire cerebral vessels was acquired. The voxel resolution is 0.35×0.4×2.0 µm(3 for the whole brain. Besides the observations of fine and complex vascular networks in the reconstructed slices and entire brain views, a representative continuous vascular tracking has been demonstrated in the deep thalamus. This study provided an effective method for studying the entire macro and micro vascular networks of mouse brain simultaneously.
Present day geodynamics in Iceland monitored by a permanent network of continuous GPS stations
Völksen, Christof; Árnadóttir, Thóra; Geirsson, Halldór; Valsson, Guðmundur
2009-12-01
Iceland is located on the Mid-Atlantic Ridge and thereby offers a rare opportunity to study crustal movements at a divergent plate boundary. Iceland is not only characterized by the divergence of the Eurasian and North American Plates, as several active volcanoes are located on the island. Moderate size earthquakes occur in the transform zones, causing measurable crustal deformation. In 1999 the installation of a permanent network of continuous GPS stations (ISGPS) was initiated in order to observe deformation due to unrest in the Hengill volcanic system and at the Katla volcano. The ISGPS network has been enlarged over the years and consists today of more than 25 CGPS stations. Most of the stations are located along the plate boundary, where most of the active deformation takes place. Uplift due to post-glacial rebound due to the melting of the largest glacier in Europe, Vatnajökull, is also detected by the ISGPS network. This study presents results from analysis of 9 years of data from the ISGPS network, in the global reference frame PDR05, which has been evaluated by the Potsdam-Dresden-Reprocessing group with reprocessed GPS data only. We thus determine subsidence or land uplift in a global frame. The horizontal station velocities clearly show spreading across the plate boundary of about 20 mm/a. Stations in the vicinity of the glacier Vatnajökull indicate uplift in the range of 12 mm/a, while a station in the central part of Iceland shows uplift rates of about 25 mm/a. Tide gauge readings in Reykjavik and current subsidence rates observed with CGPS agree also quite well.
Characterizing steady states of genome-scale metabolic networks in continuous cell cultures.
Directory of Open Access Journals (Sweden)
Jorge Fernandez-de-Cossio-Diaz
2017-11-01
Full Text Available In the continuous mode of cell culture, a constant flow carrying fresh media replaces culture fluid, cells, nutrients and secreted metabolites. Here we present a model for continuous cell culture coupling intra-cellular metabolism to extracellular variables describing the state of the bioreactor, taking into account the growth capacity of the cell and the impact of toxic byproduct accumulation. We provide a method to determine the steady states of this system that is tractable for metabolic networks of arbitrary complexity. We demonstrate our approach in a toy model first, and then in a genome-scale metabolic network of the Chinese hamster ovary cell line, obtaining results that are in qualitative agreement with experimental observations. We derive a number of consequences from the model that are independent of parameter values. The ratio between cell density and dilution rate is an ideal control parameter to fix a steady state with desired metabolic properties. This conclusion is robust even in the presence of multi-stability, which is explained in our model by a negative feedback loop due to toxic byproduct accumulation. A complex landscape of steady states emerges from our simulations, including multiple metabolic switches, which also explain why cell-line and media benchmarks carried out in batch culture cannot be extrapolated to perfusion. On the other hand, we predict invariance laws between continuous cell cultures with different parameters. A practical consequence is that the chemostat is an ideal experimental model for large-scale high-density perfusion cultures, where the complex landscape of metabolic transitions is faithfully reproduced.
Fisher, Aaron J.; Newman, Michelle G.; Molenaar, Peter C. M.
2011-01-01
Objective: The present article aimed to demonstrate that the establishment of dynamic patterns during the course of psychotherapy can create attractor states for continued adaptive change following the conclusion of treatment. Method: This study is a secondary analysis of T. D. Borkovec and E. Costello (1993). Of the 55 participants in the…
Lai, Bang-Cheng; He, Jian-Jun
2018-03-01
In this paper, we construct a novel 4D autonomous chaotic system with four cross-product nonlinear terms and five equilibria. The multiple coexisting attractors and the multiscroll attractor of the system are numerically investigated. Research results show that the system has various types of multiple attractors, including three strange attractors with a limit cycle, three limit cycles, two strange attractors with a pair of limit cycles, two coexisting strange attractors. By using the passive control theory, a controller is designed for controlling the chaos of the system. Both analytical and numerical studies verify that the designed controller can suppress chaotic motion and stabilise the system at the origin. Moreover, an electronic circuit is presented for implementing the chaotic system.
MAXIMUM-LIKELIHOOD-ESTIMATION OF THE ENTROPY OF AN ATTRACTOR
SCHOUTEN, JC; TAKENS, F; VANDENBLEEK, CM
In this paper, a maximum-likelihood estimate of the (Kolmogorov) entropy of an attractor is proposed that can be obtained directly from a time series. Also, the relative standard deviation of the entropy estimate is derived; it is dependent on the entropy and on the number of samples used in the
Low-dimensional chaotic attractors in drift wave turbulence
International Nuclear Information System (INIS)
Persson, M.; Nordman, H.
1991-01-01
Simulation results of toroidal η i -mode turbulence are analyzed using mathematical tools of nonlinear dynamics. Low-dimensional chaotic attractors are found in the strongly nonlinear regime while in the weakly interacting regime the dynamics is high dimensional. In both regimes, the solutions are found to display sensitive dependence on initial conditions, characterized by a positive largest Liapunov exponent. (au)
The Geometric Structure of Strange Attractors in the Lozi Map
Institute of Scientific and Technical Information of China (English)
YongluoCAO; ZengrongLIU
1998-01-01
In this paper,the structure of the strange attractors in the Lozi map is investigated on basis of the results gotten by the authors in 1991-1993,The new results of the strange atrtractors of the Lozi map show that our viewpoint is correct.
Global attractors for the coupled suspension bridge system with temperature
Czech Academy of Sciences Publication Activity Database
Dell'Oro, Filippo; Giorgi, C.
2016-01-01
Roč. 39, č. 4 (2016), s. 864-875 ISSN 0170-4214 Institutional support: RVO:67985840 Keywords : absorbing set * coupled bridge system * global attractor Subject RIV: BA - General Mathematics Impact factor: 1.017, year: 2016 http://onlinelibrary.wiley.com/doi/10.1002/mma.3526/abstract
Sourcing dark matter and dark energy from α-attractors
International Nuclear Information System (INIS)
Mishra, Swagat S.; Sahni, Varun; Shtanov, Yuri
2017-01-01
In [1], Kallosh and Linde drew attention to a new family of superconformal inflationary potentials, subsequently called α-attractors [2]. The α-attractor family can interpolate between a large class of inflationary models. It also has an important theoretical underpinning within the framework of supergravity. We demonstrate that the α-attractors have an even wider appeal since they may describe dark matter and perhaps even dark energy. The dark matter associated with the α-attractors, which we call α-dark matter (αDM), shares many of the attractive features of fuzzy dark matter, with V (φ) = ½ m 2 φ 2 , while having none of its drawbacks. Like fuzzy dark matter, αDM can have a large Jeans length which could resolve the cusp-core and substructure problems faced by standard cold dark matter. αDM also has an appealing tracker property which enables it to converge to the late-time dark matter asymptote, ( w ) ≅ 0, from a wide range of initial conditions. It thus avoids the enormous fine-tuning problems faced by the m 2 φ 2 potential in describing dark matter.
Probability Density Function Method for Observing Reconstructed Attractor Structure
Institute of Scientific and Technical Information of China (English)
陆宏伟; 陈亚珠; 卫青
2004-01-01
Probability density function (PDF) method is proposed for analysing the structure of the reconstructed attractor in computing the correlation dimensions of RR intervals of ten normal old men. PDF contains important information about the spatial distribution of the phase points in the reconstructed attractor. To the best of our knowledge, it is the first time that the PDF method is put forward for the analysis of the reconstructed attractor structure. Numerical simulations demonstrate that the cardiac systems of healthy old men are about 6 - 6.5 dimensional complex dynamical systems. It is found that PDF is not symmetrically distributed when time delay is small, while PDF satisfies Gaussian distribution when time delay is big enough. A cluster effect mechanism is presented to explain this phenomenon. By studying the shape of PDFs, that the roles played by time delay are more important than embedding dimension in the reconstruction is clearly indicated. Results have demonstrated that the PDF method represents a promising numerical approach for the observation of the reconstructed attractor structure and may provide more information and new diagnostic potential of the analyzed cardiac system.
Sourcing dark matter and dark energy from α-attractors
Energy Technology Data Exchange (ETDEWEB)
Mishra, Swagat S.; Sahni, Varun [Inter-University Centre for Astronomy and Astrophysics, Post Bag 4, Ganeshkhind, Pune 411 007 (India); Shtanov, Yuri, E-mail: swagat@iucaa.in, E-mail: varun@iucaa.in, E-mail: shtanov@bitp.kiev.ua [Bogolyubov Institute for Theoretical Physics, Kiev 03680 (Ukraine)
2017-06-01
In [1], Kallosh and Linde drew attention to a new family of superconformal inflationary potentials, subsequently called α-attractors [2]. The α-attractor family can interpolate between a large class of inflationary models. It also has an important theoretical underpinning within the framework of supergravity. We demonstrate that the α-attractors have an even wider appeal since they may describe dark matter and perhaps even dark energy. The dark matter associated with the α-attractors, which we call α-dark matter (αDM), shares many of the attractive features of fuzzy dark matter, with V (φ) = ½ m {sup 2}φ{sup 2}, while having none of its drawbacks. Like fuzzy dark matter, αDM can have a large Jeans length which could resolve the cusp-core and substructure problems faced by standard cold dark matter. αDM also has an appealing tracker property which enables it to converge to the late-time dark matter asymptote, ( w ) ≅ 0, from a wide range of initial conditions. It thus avoids the enormous fine-tuning problems faced by the m {sup 2}φ{sup 2} potential in describing dark matter.
Our universe as an attractor in a superstring model
International Nuclear Information System (INIS)
Maeda, Keiichi.
1986-11-01
One preferential scenario of the evolution of the universe is discussed in a superstring model. The universe can reach the present state as an attractor in the dynamical system. The kinetic terms of the ''axions'' play an important role so that our present universe is realized almost uniquely. (author)
Attractor horizons in six-dimensional type IIB supergravity
Energy Technology Data Exchange (ETDEWEB)
Astefanesei, Dumitru, E-mail: dumitru.astefanesei@ucv.cl [Instituto de Fisica, Pontificia Universidad Catolica de Valparaiso, Casilla 4059, Valparaiso (Chile); Miskovic, Olivera, E-mail: olivera.miskovic@ucv.cl [Instituto de Fisica, Pontificia Universidad Catolica de Valparaiso, Casilla 4059, Valparaiso (Chile); Olea, Rodrigo, E-mail: rodrigo.olea@unab.cl [Universidad Andres Bello, Departamento de Ciencias Fisicas, Republica 220, Santiago (Chile)
2012-08-14
We consider near horizon geometries of extremal black holes in six-dimensional type IIB supergravity. In particular, we use the entropy function formalism to compute the charges and thermodynamic entropy of these solutions. We also comment on the role of attractor mechanism in understanding the entropy of the Hopf T-dual solutions in type IIA supergravity.
On reliability of singular-value decomposition in attractor reconstruction
International Nuclear Information System (INIS)
Palus, M.; Dvorak, I.
1990-12-01
Applicability of singular-value decomposition for reconstructing the strange attractor from one-dimensional chaotic time series, proposed by Broomhead and King, is extensively tested and discussed. Previously published doubts about its reliability are confirmed: singular-value decomposition, by nature a linear method, is only of a limited power when nonlinear structures are studied. (author). 29 refs, 9 figs
Vaidyanathan, S.; Sambas, A.; Sukono; Mamat, M.; Gundara, G.; Mada Sanjaya, W. S.; Subiyanto
2018-03-01
A 3-D new chaotic attractor with two quadratic nonlinearities is proposed in this paper. The dynamical properties of the new chaotic system are described in terms of phase portraits, equilibrium points, Lyapunov exponents, Kaplan-Yorke dimension, dissipativity, etc. We show that the new chaotic system has three unstable equilibrium points. The new chaotic attractor is dissipative in nature. As an engineering application, adaptive synchronization of identical new chaotic attractors is designed via nonlinear control and Lyapunov stability theory. Furthermore, an electronic circuit realization of the new chaotic attractor is presented in detail to confirm the feasibility of the theoretical chaotic attractor model.
A novel 3D autonomous system with different multilayer chaotic attractors
International Nuclear Information System (INIS)
Dong Gaogao; Du Ruijin; Tian Lixin; Jia Qiang
2009-01-01
This Letter proposes a novel three-dimensional autonomous system which has complex chaotic dynamics behaviors and gives analysis of novel system. More importantly, the novel system can generate three-layer chaotic attractor, four-layer chaotic attractor, five-layer chaotic attractor, multilayer chaotic attractor by choosing different parameters and initial condition. We analyze the new system by means of phase portraits, Lyapunov exponent spectrum, fractional dimension, bifurcation diagram and Poincare maps of the system. The three-dimensional autonomous system is totally different from the well-known systems in previous work. The new multilayer chaotic attractors are also worth causing attention.
COSMOS-e{sup '}-soft Higgsotic attractors
Energy Technology Data Exchange (ETDEWEB)
Choudhury, Sayantan [Tata Institute of Fundamental Research, Department of Theoretical Physics, Mumbai (India)
2017-07-15
In this work, we have developed an elegant algorithm to study the cosmological consequences from a huge class of quantum field theories (i.e. superstring theory, supergravity, extra dimensional theory, modified gravity, etc.), which are equivalently described by soft attractors in the effective field theory framework. In this description we have restricted our analysis for two scalar fields - dilaton and Higgsotic fields minimally coupled with Einstein gravity, which can be generalized for any arbitrary number of scalar field contents with generalized non-canonical and non-minimal interactions. We have explicitly used R{sup 2} gravity, from which we have studied the attractor and non-attractor phases by exactly computing two point, three point and four point correlation functions from scalar fluctuations using the In-In (Schwinger-Keldysh) and the δN formalisms. We have also presented theoretical bounds on the amplitude, tilt and running of the primordial power spectrum, various shapes (equilateral, squeezed, folded kite or counter-collinear) of the amplitude as obtained from three and four point scalar functions, which are consistent with observed data. Also the results from two point tensor fluctuations and the field excursion formula are explicitly presented for the attractor and non-attractor phase. Further, reheating constraints, scale dependent behavior of the couplings and the dynamical solution for the dilaton and Higgsotic fields are also presented. New sets of consistency relations between two, three and four point observables are also presented, which shows significant deviation from canonical slow-roll models. Additionally, three possible theoretical proposals have presented to overcome the tachyonic instability at the time of late time acceleration. Finally, we have also provided the bulk interpretation from the three and four point scalar correlation functions for completeness. (orig.)
Energy Technology Data Exchange (ETDEWEB)
Wolk, P.J. van der; Wang, J. [Delft Univ. of Technology (Netherlands); Sietsma, J.; Zwaag, S. van der [Delft Univ. of Technology, Lab. for Materials Science (Netherlands)
2002-12-01
A neural network model for the calculation of the phase regions of the continuous cooling transformation (CCT) diagram of engineering steels has been developed. The model is based on experimental CCT diagrams of 459 low-alloy steels, and calculates the CCT diagram as a function of composition and austenitisation temperature. In considering the composition, 9 alloying elements are taken into account. The model reproduces the original diagrams rather accurately, with deviations that are not larger than the average experimental inaccuracy of the experimental diagrams. Therefore, it can be considered an adequate alternative to the experimental determination of the CCT diagram of a certain steel within the composition range used. The effects of alloying elements can be quantified, either individually or in combination, with the model. Nonlinear composition dependencies are observed. (orig.)
Duane, Gregory S.; Grabow, Carsten; Selten, Frank; Ghil, Michael
2017-12-01
The synchronization of loosely coupled chaotic systems has increasingly found applications to large networks of differential equations and to models of continuous media. These applications are at the core of the present Focus Issue. Synchronization between a system and its model, based on limited observations, gives a new perspective on data assimilation. Synchronization among different models of the same system defines a supermodel that can achieve partial consensus among models that otherwise disagree in several respects. Finally, novel methods of time series analysis permit a better description of synchronization in a system that is only observed partially and for a relatively short time. This Focus Issue discusses synchronization in extended systems or in components thereof, with particular attention to data assimilation, supermodeling, and their applications to various areas, from climate modeling to macroeconomics.
Duane, Gregory S; Grabow, Carsten; Selten, Frank; Ghil, Michael
2017-12-01
The synchronization of loosely coupled chaotic systems has increasingly found applications to large networks of differential equations and to models of continuous media. These applications are at the core of the present Focus Issue. Synchronization between a system and its model, based on limited observations, gives a new perspective on data assimilation. Synchronization among different models of the same system defines a supermodel that can achieve partial consensus among models that otherwise disagree in several respects. Finally, novel methods of time series analysis permit a better description of synchronization in a system that is only observed partially and for a relatively short time. This Focus Issue discusses synchronization in extended systems or in components thereof, with particular attention to data assimilation, supermodeling, and their applications to various areas, from climate modeling to macroeconomics.
A snapshot attractor view of the advection of inertial particles in the presence of history force
Guseva, Ksenia; Daitche, Anton; Tél, Tamás
2017-06-01
We analyse the effect of the Basset history force on the sedimentation or rising of inertial particles in a two-dimensional convection flow. We find that the concept of snapshot attractors is useful to understand the extraordinary slow convergence due to long-term memory: an ensemble of particles converges exponentially fast towards a snapshot attractor, and this attractor undergoes a slow drift for long times. We demonstrate for the case of a periodic attractor that the drift of the snapshot attractor can be well characterized both in the space of the fluid and in the velocity space. For the case of quasiperiodic and chaotic dynamics we propose the use of the average settling velocity of the ensemble as a distinctive measure to characterize the snapshot attractor and the time scale separation corresponding to the convergence towards the snapshot attractor and its own slow dynamics.
Framework and implementation of a continuous network-wide health monitoring system for roadways
Wang, Ming; Birken, Ralf; Shahini Shamsabadi, Salar
2014-03-01
According to the 2013 ASCE report card America's infrastructure scores only a D+. There are more than four million miles of roads (grade D) in the U.S. requiring a broad range of maintenance activities. The nation faces a monumental problem of infrastructure management in the scheduling and implementation of maintenance and repair operations, and in the prioritization of expenditures within budgetary constraints. The efficient and effective performance of these operations however is crucial to ensuring roadway safety, preventing catastrophic failures, and promoting economic growth. There is a critical need for technology that can cost-effectively monitor the condition of a network-wide road system and provide accurate, up-to-date information for maintenance activity prioritization. The Versatile Onboard Traffic Embedded Roaming Sensors (VOTERS) project provides a framework and the sensing capability to complement periodical localized inspections to continuous network-wide health monitoring. Research focused on the development of a cost-effective, lightweight package of multi-modal sensor systems compatible with this framework. An innovative software infrastructure is created that collects, processes, and evaluates these large time-lapse multi-modal data streams. A GIS-based control center manages multiple inspection vehicles and the data for further analysis, visualization, and decision making. VOTERS' technology can monitor road conditions at both the surface and sub-surface levels while the vehicle is navigating through daily traffic going about its normal business, thereby allowing for network-wide frequent assessment of roadways. This deterioration process monitoring at unprecedented time and spatial scales provides unique experimental data that can be used to improve life-cycle cost analysis models.
Directory of Open Access Journals (Sweden)
Na Lin
2017-03-01
Full Text Available In recent years, symbiosis as a rich source of potential engineering applications and computational model has attracted more and more attentions in the adaptive complex systems and evolution computing domains. Inspired by different symbiotic coevolution forms in nature, this paper proposed a series of multi-swarm particle swarm optimizers called PS2Os, which extend the single population particle swarm optimization (PSO algorithm to interacting multi-swarms model by constructing hierarchical interaction topologies and enhanced dynamical update equations. According to different symbiotic interrelationships, four versions of PS2O are initiated to mimic mutualism, commensalism, predation, and competition mechanism, respectively. In the experiments, with five benchmark problems, the proposed algorithms are proved to have considerable potential for solving complex optimization problems. The coevolutionary dynamics of symbiotic species in each PS2O version are also studied respectively to demonstrate the heterogeneity of different symbiotic interrelationships that effect on the algorithm’s performance. Then PS2O is used for solving the radio frequency identification (RFID network planning (RNP problem with a mixture of discrete and continuous variables. Simulation results show that the proposed algorithm outperforms the reference algorithms for planning RFID networks, in terms of optimization accuracy and computation robustness.
Continuous-time random walks on networks with vertex- and time-dependent forcing.
Angstmann, C N; Donnelly, I C; Henry, B I; Langlands, T A M
2013-08-01
We have investigated the transport of particles moving as random walks on the vertices of a network, subject to vertex- and time-dependent forcing. We have derived the generalized master equations for this transport using continuous time random walks, characterized by jump and waiting time densities, as the underlying stochastic process. The forcing is incorporated through a vertex- and time-dependent bias in the jump densities governing the random walking particles. As a particular case, we consider particle forcing proportional to the concentration of particles on adjacent vertices, analogous to self-chemotactic attraction in a spatial continuum. Our algebraic and numerical studies of this system reveal an interesting pair-aggregation pattern formation in which the steady state is composed of a high concentration of particles on a small number of isolated pairs of adjacent vertices. The steady states do not exhibit this pair aggregation if the transport is random on the vertices, i.e., without forcing. The manifestation of pair aggregation on a transport network may thus be a signature of self-chemotactic-like forcing.
Lin, Na; Chen, Hanning; Jing, Shikai; Liu, Fang; Liang, Xiaodan
2017-03-01
In recent years, symbiosis as a rich source of potential engineering applications and computational model has attracted more and more attentions in the adaptive complex systems and evolution computing domains. Inspired by different symbiotic coevolution forms in nature, this paper proposed a series of multi-swarm particle swarm optimizers called PS 2 Os, which extend the single population particle swarm optimization (PSO) algorithm to interacting multi-swarms model by constructing hierarchical interaction topologies and enhanced dynamical update equations. According to different symbiotic interrelationships, four versions of PS 2 O are initiated to mimic mutualism, commensalism, predation, and competition mechanism, respectively. In the experiments, with five benchmark problems, the proposed algorithms are proved to have considerable potential for solving complex optimization problems. The coevolutionary dynamics of symbiotic species in each PS 2 O version are also studied respectively to demonstrate the heterogeneity of different symbiotic interrelationships that effect on the algorithm's performance. Then PS 2 O is used for solving the radio frequency identification (RFID) network planning (RNP) problem with a mixture of discrete and continuous variables. Simulation results show that the proposed algorithm outperforms the reference algorithms for planning RFID networks, in terms of optimization accuracy and computation robustness.
An MPCC Formulation and Its Smooth Solution Algorithm for Continuous Network Design Problem
Directory of Open Access Journals (Sweden)
Guangmin Wang
2017-12-01
Full Text Available Continuous network design problem (CNDP is searching for a transportation network configuration to minimize the sum of the total system travel time and the investment cost of link capacity expansions by considering that the travellers follow a traditional Wardrop user equilibrium (UE to choose their routes. In this paper, the CNDP model can be formulated as mathematical programs with complementarity constraints (MPCC by describing UE as a non-linear complementarity problem (NCP. To address the difficulty resulting from complementarity constraints in MPCC, they are substituted by the Fischer-Burmeister (FB function, which can be smoothed by the introduction of the smoothing parameter. Therefore, the MPCC can be transformed into a well-behaved non-linear program (NLP by replacing the complementarity constraints with a smooth equation. Consequently, the solver such as LINDOGLOBAL in GAMS can be used to solve the smooth approximate NLP to obtain the solution to MPCC for modelling CNDP. The numerical experiments on the example from the literature demonstrate that the proposed algorithm is feasible.
Influence of individual rationality on continuous double auction markets with networked traders
Zhang, Junhuan
2018-04-01
This paper investigates the influence of individual rationality of buyers and sellers on continuous double auction market outcomes in terms of the proportion of boundedly-rational buyers and sellers. The individual rationality is discussed in a social network artificial stock market model by embedding network formation and information set. Traders automatically select the most profitable trading strategy based on individual and social learning of the profits and trading strategies of themselves and their neighbors, and submit orders to markets. The results show that (i) a higher proportion of boundedly-rational sellers induces a higher market price, higher sellers' profits and a higher market efficiency; (ii) a higher proportion of boundedly-rational sellers induces a lower number of trades and lower buyers' profits; (iii) a higher proportion of boundedly-rational buyers induces a lower market price, a lower number of trades, and lower sellers' profits; (iv) a higher proportion of boundedly-rational buyers induces higher buyers' profits and a higher market efficiency.
An Eco-Driving Advisory System for Continuous Signalized Intersections by Vehicular Ad Hoc Network
Directory of Open Access Journals (Sweden)
Wei-Hsun Lee
2018-01-01
Full Text Available With the vehicular ad hoc network (VANET technology which support vehicle-to-vehicle (V2V and vehicle to road side unit (V2R/R2V communications, vehicles can preview the intersection signal plan such as signal countdown message. In this paper, an ecodriving advisory system (EDAS is proposed to reduce CO2 emissions and energy consumption by letting the vehicle continuously pass through multiple intersections with the minimum possibilities of stops. We extend the isolated intersection model to multiple continuous intersections scenario. A hybrid method combining three strategies including maximized throughput model (MTM, smooth speed model (SSM, and minimized acceleration and deceleration (MinADM is designed, and it is compared with related works maximized throughput model (MaxTM, open traffic light control model (OTLCM, and predictive cruise control (PCC models. Some issues for the practical application including safe car following, queue clearing, and gliding mode are discussed and conquered. Simulation results show that the proposed model outperforms OTLCM 25.1%~81.2% in the isolated intersection scenario for the CO2 emissions and 20.5%~84.3% in averaged travel time. It also performs better than the compared PCC model in CO2 emissions (19.9%~31.2% as well as travel time (24.5%~35.9% in the multiple intersections scenario.
Generic Properties of Random Gene Regulatory Networks.
Li, Zhiyuan; Bianco, Simone; Zhang, Zhaoyang; Tang, Chao
2013-12-01
Modeling gene regulatory networks (GRNs) is an important topic in systems biology. Although there has been much work focusing on various specific systems, the generic behavior of GRNs with continuous variables is still elusive. In particular, it is not clear typically how attractors partition among the three types of orbits: steady state, periodic and chaotic, and how the dynamical properties change with network's topological characteristics. In this work, we first investigated these questions in random GRNs with different network sizes, connectivity, fraction of inhibitory links and transcription regulation rules. Then we searched for the core motifs that govern the dynamic behavior of large GRNs. We show that the stability of a random GRN is typically governed by a few embedding motifs of small sizes, and therefore can in general be understood in the context of these short motifs. Our results provide insights for the study and design of genetic networks.
Feasibility of Construction of the Continuously Operating Geodetic GPS Network of Sinaloa, Mexico
Vazquez, G. E.; Jacobo, C.
2011-12-01
This research is based on the study and analysis of feasibility for the construction of the geodetic network for GPS continuous operation for Sinaloa, hereafter called (RGOCSIN). A GPS network of continuous operation is defined as that materialized structure physically through permanent monuments where measurements to the systems of Global Positioning (GPS) is performed continuously throughout a region. The GPS measurements in this network are measurements of accuracy according to international standards to define its coordinates, thus constituting the basic structure of geodetic referencing for a country. In this context is that in the near future the RGOCSIN constitutes a system state only accurate and reliable georeferencing in real-time (continuous and permanent operation) and will be used for different purposes; i.e., in addition to being fundamental basis for any lifting topographic or geodetic survey, and other areas such as: (1) Different construction processes (control and monitoring of engineering works); (2) Studies of deformation of the Earth's crust (before and after a seismic event); (3) GPS meteorology (weather forecasting); (4) Demarcation projects (natural and political); (5) Establishment of bases to generate mapping (necessary for the economic and social development of the state); (6) Precision agriculture (optimization of economic resources to the various crops); (7) Geographic information systems (Organization and planning activities associated with the design and construction of public services); (8) Urban growth (possible settlements in the appropriate form and taking care of the environmental aspect), among others. However there are criteria and regulations according to the INEGI (Instituto Nacional de Estadística y Geografía, http://www.inegi.org.mx/) that must be met; even for this stage of feasibility of construction that sees this project as a first phase. The fundamental criterion to be taken into account according to INEGI is a
Pullback attractors for three-dimensional non-autonomous Navier–Stokes–Voigt equations
International Nuclear Information System (INIS)
García-Luengo, Julia; Marín-Rubio, Pedro; Real, José
2012-01-01
In this paper, we consider a non-autonomous Navier–Stokes–Voigt model, with which a continuous process can be associated. We study the existence and relationship between minimal pullback attractors for this process in two different frameworks, namely, for the universe of fixed bounded sets, and also for another universe given by a tempered condition. Since the model does not have a regularizing effect, obtaining asymptotic compactness for the process is a more involved task. We prove this in a relatively simple way just using an energy method. Our results simplify—and in some aspects generalize—some of those obtained previously for the autonomous and non-autonomous cases, since for example in section 4, regularity is not required for the boundary of the domain and the force may take values in V'. Under additional suitable assumptions, regularity results for these families of attractors are also obtained, via bootstrapping arguments. Finally, we also conclude some results concerning the attraction in the D(A) norm
Chaotic Attractor Crisis and Climate Sensitivity: a Transfer Operator Approach
Tantet, A.; Lucarini, V.; Lunkeit, F.; Dijkstra, H. A.
2015-12-01
The rough response to a smooth parameter change of some non-chaotic climate models, such as the warm to snowball-Earth transition in energy balance models due to the ice-albedo feedback, can be studied in the framework of bifurcation theory, in particular by analysing the Lyapunov spectrum of fixed points or periodic orbits. However, bifurcation theory is of little help to study the destruction of a chaotic attractor which can occur in high-dimensional General Circulation Models (GCM). Yet, one would expect critical slowing down to occur before the crisis, since, as the system becomes susceptible to the physical instability mechanism responsible for the crisis, it turns out to be less and less resilient to exogenous perturbations and to spontaneous fluctuations due to other types of instabilities on the attractor. The statistical physics framework, extended to nonequilibrium systems, is particularly well suited for the study of global properties of chaotic and stochastic systems. In particular, the semigroup of transfer operators governs the evolution of distributions in phase space and its spectrum characterises both the relaxation rate of distributions to a statistical steady-state and the stability of this steady-state to perturbations. If critical slowing down indeed occurs in the approach to an attractor crisis, the gap in the spectrum of the semigroup of transfer operators is expected to shrink. We show that the chaotic attractor crisis due to the ice-albedo feedback and resulting in a transition from a warm to a snowball-Earth in the Planet Simulator (PlaSim), a GCM of intermediate complexity, is associated with critical slowing down, as observed by the slower decay of correlations before the crisis (cf. left panel). In addition, we demonstrate that this critical slowing down can be traced back to the shrinkage of the gap between the leading eigenvalues of coarse-grained approximations of the transfer operators and that these eigenvalues capture the
International Nuclear Information System (INIS)
Njitacke, Z.T.; Kengne, J.; Fotsin, H.B.; Negou, A. Nguomkam; Tchiotsop, D.
2016-01-01
In the present paper, a new memristor based oscillator is obtained from the autonomous Jerk circuit [Kengne et al., Nonlinear Dynamics (2016) 83: 751̶765] by substituting the nonlinear element of the original circuit with a first order memristive diode bridge. The model is described by a continuous time four-dimensional autonomous system with smooth nonlinearities. Various nonlinear analysis tools such as phase portraits, time series, bifurcation diagrams, Poincaré section and the spectrum of Lyapunov exponents are exploited to characterize different scenarios to chaos in the novel circuit. It is found that the system experiences period doubling and crisis routes to chaos. One of the major results of this work is the finding of a window in the parameters’ space in which the circuit develops hysteretic behaviors characterized by the coexistence of four different (periodic and chaotic) attractors for the same values of the system parameters. Basins of attractions of various coexisting attractors are plotted showing complex basin boundaries. As far as the authors’ knowledge goes, the novel memristive jerk circuit represents one of the simplest electrical circuits (no analog multiplier chip is involved) capable of four disconnected coexisting attractors reported to date. Both PSpice simulations of the nonlinear dynamics of the oscillator and laboratory experimental measurements are carried out to validate the theoretical analysis.
Energy Technology Data Exchange (ETDEWEB)
Simpson, D.J.W., E-mail: d.j.w.simpson@massey.ac.nz
2016-09-07
An attractor of a piecewise-smooth continuous system of differential equations can bifurcate from a stable equilibrium to a more complicated invariant set when it collides with a switching manifold under parameter variation. Here numerical evidence is provided to show that this invariant set can be chaotic. The transition occurs locally (in a neighbourhood of a point) and instantaneously (for a single critical parameter value). This phenomenon is illustrated for the normal form of a boundary equilibrium bifurcation in three dimensions using parameter values adapted from of a piecewise-linear model of a chaotic electrical circuit. The variation of a secondary parameter reveals a period-doubling cascade to chaos with windows of periodicity. The dynamics is well approximated by a one-dimensional unimodal map which explains the bifurcation structure. The robustness of the attractor is also investigated by studying the influence of nonlinear terms. - Highlights: • A boundary equilibrium bifurcation involving stable and saddle foci is considered. • A two-dimensional return map is constructed and approximated by a one-dimensional map. • A trapping region and Smale horseshoe are identified for a Rössler-like attractor. • Bifurcation diagrams reveal period-doubling cascades and windows of periodicity.
Generating multi-double-scroll attractors via nonautonomous approach
Energy Technology Data Exchange (ETDEWEB)
Hong, Qinghui; Xie, Qingguo, E-mail: qgxie@mail.hust.edu.cn [Wuhan National Laboratory for Optoelectronics, Wuhan 430074 (China); Shen, Yi; Wang, Xiaoping [School of Automation, Huazhong University of Science and Technology, Wuhan 430074 (China)
2016-08-15
It is a common phenomenon that multi-scroll attractors are realized by introducing the various nonlinear functions with multiple breakpoints in double scroll chaotic systems. Differently, we present a nonautonomous approach for generating multi-double-scroll attractors (MDSA) without changing the original nonlinear functions. By using the multi-level-logic pulse excitation technique in double scroll chaotic systems, MDSA can be generated. A Chua's circuit, a Jerk circuit, and a modified Lorenz system are given as designed example and the Matlab simulation results are presented. Furthermore, the corresponding realization circuits are designed. The Pspice results are in agreement with numerical simulation results, which verify the availability and feasibility of this method.
Determining the flexibility of regular and chaotic attractors
International Nuclear Information System (INIS)
Marhl, Marko; Perc, Matjaz
2006-01-01
We present an overview of measures that are appropriate for determining the flexibility of regular and chaotic attractors. In particular, we focus on those system properties that constitute its responses to external perturbations. We deploy a systematic approach, first introducing the simplest measure given by the local divergence of the system along the attractor, and then develop more rigorous mathematical tools for estimating the flexibility of the system's dynamics. The presented measures are tested on the regular Brusselator and chaotic Hindmarsh-Rose model of an excitable neuron with equal success, thus indicating the overall effectiveness and wide applicability range of the proposed theory. Since responses of dynamical systems to external signals are crucial in several scientific disciplines, and especially in natural sciences, we discuss several important aspects and biological implications of obtained results
Generating multi-double-scroll attractors via nonautonomous approach.
Hong, Qinghui; Xie, Qingguo; Shen, Yi; Wang, Xiaoping
2016-08-01
It is a common phenomenon that multi-scroll attractors are realized by introducing the various nonlinear functions with multiple breakpoints in double scroll chaotic systems. Differently, we present a nonautonomous approach for generating multi-double-scroll attractors (MDSA) without changing the original nonlinear functions. By using the multi-level-logic pulse excitation technique in double scroll chaotic systems, MDSA can be generated. A Chua's circuit, a Jerk circuit, and a modified Lorenz system are given as designed example and the Matlab simulation results are presented. Furthermore, the corresponding realization circuits are designed. The Pspice results are in agreement with numerical simulation results, which verify the availability and feasibility of this method.
Non-Abelian magnetized blackholes and unstable attractors
International Nuclear Information System (INIS)
Mosaffa, A.E.; Randjbar-Daemi, S.; Sheikh-Jabbari, M.M.
2006-12-01
Fluctuations of non-Abelian gauge fields in a background magnetic flux contain tachyonic modes and hence the background is unstable. We extend these results to the cases where the background flux is coupled to Einstein gravity and show that the corresponding spherically symmetric geometries, which in the absence of a cosmological constant are of the form of Reissner-Nordstroem blackholes or the AdS 2 x S 2 , are also unstable. We discuss the relevance of these instabilities to several places in string theory including various string compactifications and the attractor mechanism. Our results for the latter imply that the attractor mechanism shown to work for the extremal Abelian charged blackholes, cannot be applied in a straightforward way to the extremal non-Abelian colored blackholes. (author)
Lifetime of chaotic attractors in a multidimensional laser system
International Nuclear Information System (INIS)
Pando L, C.L.; Cerdeira, H.A.
1995-01-01
We study the lifetimes of chaotic attractors at crises in a multidimensional laser system. This system describes the CO 2 laser with modulated losses and is known as the four-level model. The critical exponents which are related to the lifetimes of the attractors are estimated in terms of the corresponding eigenvalues and the measured characteristic lifetime in the model. The critical exponents in this model and those of its center manifold version are in good agreement. We conjecture that generically in the four-level model the critical exponents are close to 1/2 at crises. In addition, we compare predictions of a simpler and popular model known as the two-level model with those of the above mentioned models. (author). 21 refs, 2 figs, 3 tabs
Attractors of dissipative structure in three dissipative fluids
International Nuclear Information System (INIS)
Kondoh, Yoshiomi
1993-10-01
A general theory with use of auto-correlations for distributions is presented to derive that realization of coherent structures in general dissipative dynamic systems is equivalent to that of self-organized states with the minimum dissipation rate for instantaneously contained energy. Attractors of dissipative structure are shown to be given by eigenfunctions for dissipative dynamic operators of the dynamic system and to constitute the self-organized and self-similar decay phase. Three typical examples applied to incompressible viscous fluids, to incompressible viscous and resistive magnetohydrodynamic (MHD) fluids and to compressible resistive MHD plasmas are presented to lead to attractors in the three dissipative fluids and to describe a common physical picture of self-organization and bifurcation of the dissipative structure. (author)
Torus-doubling process via strange nonchaotic attractors
International Nuclear Information System (INIS)
Mitsui, Takahito; Uenohara, Seiji; Morie, Takashi; Horio, Yoshihiko; Aihara, Kazuyuki
2012-01-01
Torus-doubling bifurcations typically occur only a finite number of times. It has been assumed that torus-doubling bifurcations in quasiperiodically forced systems are interrupted by the appearance of strange nonchaotic attractors (SNAs). In the present Letter, we study a quasiperiodically forced noninvertible map and report the occurrence of a torus-doubling process via SNAs. The mechanism of this process is numerically clarified. Furthermore, this process is experimentally demonstrated in a switched-capacitor integrated circuit. -- Highlights: ► We report the occurrence of a torus-doubling process via strange nonchaotic attractors (SNAs). ► The process consists of the gradual fractalization of a torus and the Heagy–Hammel transition. ► The torus-doubling process via SNAs is also experimentally demonstrated in an electronic circuit.
Logical Attractors: a Boolean Approach to the Dynamics of Psychosis
Kupper, Z.; Hoffmann, H.
A Boolean modeling approach to attractors in the dynamics of psychosis is presented: Kinetic Logic, originating from R. Thomas, describes systems on an intermediate level between a purely verbal, qualitative description and a description using nonlinear differential equations. With this method we may model impact, feedback and temporal evolution, as well as analyze the resulting attractors. In our previous research the method has been applied to general and more specific questions in the dynamics of psychotic disorders. In this paper a model is introduced that describes different dynamical patterns of chronic psychosis in the context of vocational rehabilitation. It also shows to be useful in formulating and exploring possible treatment strategies. Finally, some of the limitations and benefits of Kinetic Logic as a modeling tool for psychology and psychiatry are discussed.
A Hyperchaotic Attractor with Multiple Positive Lyapunov Exponents
International Nuclear Information System (INIS)
Guo-Si, Hu
2009-01-01
There are many hyperchaotic systems, but few systems can generate hyperchaotic attractors with more than three PLEs (positive Lyapunov exponents). A new hyperchaotic system, constructed by adding an approximate time-delay state feedback to a five-dimensional hyperchaotic system, is presented. With the increasing number of phase-shift units used in this system, the number of PLEs also steadily increases. Hyperchaotic attractors with 25 PLEs can be generated by this system with 32 phase-shift units. The sum of the PLEs will reach the maximum value when 23 phase-shift units are used. A simple electronic circuit, consisting of 16 operational amplifiers and two analogy multipliers, is presented for confirming hyperchaos of order 5, i.e., with 5 PLEs
Attractor reconstruction for non-linear systems: a methodological note
Nichols, J.M.; Nichols, J.D.
2001-01-01
Attractor reconstruction is an important step in the process of making predictions for non-linear time-series and in the computation of certain invariant quantities used to characterize the dynamics of such series. The utility of computed predictions and invariant quantities is dependent on the accuracy of attractor reconstruction, which in turn is determined by the methods used in the reconstruction process. This paper suggests methods by which the delay and embedding dimension may be selected for a typical delay coordinate reconstruction. A comparison is drawn between the use of the autocorrelation function and mutual information in quantifying the delay. In addition, a false nearest neighbor (FNN) approach is used in minimizing the number of delay vectors needed. Results highlight the need for an accurate reconstruction in the computation of the Lyapunov spectrum and in prediction algorithms.
Sequences by Metastable Attractors: Interweaving Dynamical Systems and Experimental Data
Directory of Open Access Journals (Sweden)
Axel Hutt
2017-05-01
Full Text Available Metastable attractors and heteroclinic orbits are present in the dynamics of various complex systems. Although their occurrence is well-known, their identification and modeling is a challenging task. The present work reviews briefly the literature and proposes a novel combination of their identification in experimental data and their modeling by dynamical systems. This combination applies recurrence structure analysis permitting the derivation of an optimal symbolic representation of metastable states and their dynamical transitions. To derive heteroclinic sequences of metastable attractors in various experimental conditions, the work introduces a Hausdorff clustering algorithm for symbolic dynamics. The application to brain signals (event-related potentials utilizing neural field models illustrates the methodology.
Inflationary α -attractor cosmology: A global dynamical systems perspective
Alho, Artur; Uggla, Claes
2017-04-01
We study flat Friedmann-Lemaître-Robertson-Walker α -attractor E- and T-models by introducing a dynamical systems framework that yields regularized unconstrained field equations on two-dimensional compact state spaces. This results in both illustrative figures and a complete description of the entire solution spaces of these models, including asymptotics. In particular, it is shown that observational viability, which requires a sufficient number of e -folds, is associated with a particular solution given by a one-dimensional center manifold of a past asymptotic de Sitter state, where the center manifold structure also explains why nearby solutions are attracted to this "inflationary attractor solution." A center manifold expansion yields a description of the inflationary regime with arbitrary analytic accuracy, where the slow-roll approximation asymptotically describes the tangency condition of the center manifold at the asymptotic de Sitter state.
Coupled flare attractors – a discrete prototype for economic modelling
Directory of Open Access Journals (Sweden)
Georg C. Hartmann
1999-01-01
Full Text Available A chaotic environment can give rise to “flares” if an autocatalytic variable responds in a multiplicative, threshold-type fashion to the environmental forcing. An “economic unit” similarly depends in its growth behavior on the unpredictable (chaotic? buying habits of its customers, say. It turns out that coupled flare attractors are surprisingly robust in the sense that the resulting “economy” is largely independent of the extent of diffusive coupling used. Some simulations are presented.
Resonances in a Chaotic Attractor Crisis of the Lorenz Flow
Tantet, Alexis; Lucarini, Valerio; Dijkstra, Henk A.
2018-02-01
Local bifurcations of stationary points and limit cycles have successfully been characterized in terms of the critical exponents of these solutions. Lyapunov exponents and their associated covariant Lyapunov vectors have been proposed as tools for supporting the understanding of critical transitions in chaotic dynamical systems. However, it is in general not clear how the statistical properties of dynamical systems change across a boundary crisis during which a chaotic attractor collides with a saddle. This behavior is investigated here for a boundary crisis in the Lorenz flow, for which neither the Lyapunov exponents nor the covariant Lyapunov vectors provide a criterion for the crisis. Instead, the convergence of the time evolution of probability densities to the invariant measure, governed by the semigroup of transfer operators, is expected to slow down at the approach of the crisis. Such convergence is described by the eigenvalues of the generator of this semigroup, which can be divided into two families, referred to as the stable and unstable Ruelle-Pollicott resonances, respectively. The former describes the convergence of densities to the attractor (or escape from a repeller) and is estimated from many short time series sampling the state space. The latter is responsible for the decay of correlations, or mixing, and can be estimated from a long times series, invoking ergodicity. It is found numerically for the Lorenz flow that the stable resonances do approach the imaginary axis during the crisis, as is indicative of the loss of global stability of the attractor. On the other hand, the unstable resonances, and a fortiori the decay of correlations, do not flag the proximity of the crisis, thus questioning the usual design of early warning indicators of boundary crises of chaotic attractors and the applicability of response theory close to such crises.
Long time behavior and attractors for energetically insulated fluid systems
Czech Academy of Sciences Publication Activity Database
Feireisl, Eduard
2010-01-01
Roč. 27, č. 4 (2010), s. 1587-1609 ISSN 1078-0947 R&D Projects: GA ČR GA201/09/0917 Institutional research plan: CEZ:AV0Z10190503 Keywords : Navier-Stokes-Fourier system * attractor * long time behavior Subject RIV: BA - General Mathematics Impact factor: 0.986, year: 2010 http://www.aimsciences.org/journals/displayArticles.jsp?paperID=5040
Reduction of Dietrich-Ruina attractors to unimodal maps
Directory of Open Access Journals (Sweden)
S. Shkoller
1997-01-01
Full Text Available We present a geometric analysis of a quasi-static single degree of freedom elastic slider with a state and rate dependent friction law. In particular, we examine and characterize the regime of chaotic motions displayed by the Dieterich-Ruina model. We do so by numerically reducing the chaotic attractors to a family of unimodal maps and discuss why this suggests complex behaviour in the dynamical system.
Attractors of magnetohydrodynamic flows in an Alfvenic state
Energy Technology Data Exchange (ETDEWEB)
Nunez, Manuel; Sanz, Javier [Departamento de Analisis Matematico, Universidad de Valladolid, Valladolid (Spain)
1999-08-13
We present a simplified form of the magnetohydrodynamic system which describes the evolution of a plasma where the small-scale velocity and magnetic field are aligned in the form of Alfven waves, such as happens in several turbulent situations. Bounds on the dimension of the global attractor are found, and are shown to be an improvement of the standard ones for the full magnetohydrodynamic equations. (author)
Scherwath, M.; Heesemann, M.; Riedel, M.; Thomsen, L.; Roemer, M.; Chatzievangelou, D.; Purser, A.
2017-12-01
Since 2009 Ocean Networks Canada provides permanent access and continuous data in near real-time from two prominent gas hydrates research sites at the Northern Cascadia Margin, Barkley Canyon and Clayoquot Slope off Vancouver Island, through power and communication cables directly from shore. We show data highlights from the seafloor crawler Wally, the world's first internet operated vehicle, in a field of hydrate mounds and outcropping gas hydrates, and its co-located sonars and state-of-the-ocean sensors and Barkley Canyon. For example, spectacular views from the benthic communities and their changes over time are captured by video. At Clayoquot Slope highly active gas seep fields are monitored with a rotating multibeam sonar and various other environmental sensors. In addition, newly installed geodetic sensors as well as an instrumented borehole in that area are now online and provide additional data on subduction-related deformation and potential links to gas discharge. These show-case examples highlight the benefits of co-located experiments that enable interdisciplinary research and also the ability for high-power and -bandwidth long-term monitoring at remote seafloor locations, that over time will provide baselines for environmental monitoring together with natural variability and potential long-term trends.
Global attractors and extinction dynamics of cyclically competing species.
Rulands, Steffen; Zielinski, Alejandro; Frey, Erwin
2013-05-01
Transitions to absorbing states are of fundamental importance in nonequilibrium physics as well as ecology. In ecology, absorbing states correspond to the extinction of species. We here study the spatial population dynamics of three cyclically interacting species. The interaction scheme comprises both direct competition between species as in the cyclic Lotka-Volterra model, and separated selection and reproduction processes as in the May-Leonard model. We show that the dynamic processes leading to the transient maintenance of biodiversity are closely linked to attractors of the nonlinear dynamics for the overall species' concentrations. The characteristics of these global attractors change qualitatively at certain threshold values of the mobility and depend on the relative strength of the different types of competition between species. They give information about the scaling of extinction times with the system size and thereby the stability of biodiversity. We define an effective free energy as the negative logarithm of the probability to find the system in a specific global state before reaching one of the absorbing states. The global attractors then correspond to minima of this effective energy landscape and determine the most probable values for the species' global concentrations. As in equilibrium thermodynamics, qualitative changes in the effective free energy landscape indicate and characterize the underlying nonequilibrium phase transitions. We provide the complete phase diagrams for the population dynamics and give a comprehensive analysis of the spatio-temporal dynamics and routes to extinction in the respective phases.
On the renormalization group perspective of α-attractors
Energy Technology Data Exchange (ETDEWEB)
Narain, Gaurav, E-mail: gaunarain@itp.ac.cn [Kavli Institute for Theoretical Physics China (KITPC), Key Laboratory of Theoretical Physics, Institute of Theoretical Physics (ITP), Chinese Academy of Sciences -CAS, Beijing 100190 (China)
2017-10-01
In this short paper we outline a recipe for the reconstruction of F ( R ) gravity starting from single field inflationary potentials in the Einstein frame. For simple potentials one can compute the explicit form of F ( R ), whilst for more involved examples one gets a parametric form of F ( R ). The F ( R ) reconstruction algorithm is used to study various examples: power-law φ {sup n} , exponential and α -attractors. In each case it is seen that for large R (corresponding to large value of inflaton field), F ( R ) ∼ R {sup 2}. For the case of α -attractors F ( R ) ∼ R {sup 2} for all values of inflaton field (for all values of R ) as α → 0. For generic inflaton potential V (φ), it is seen that if V {sup '}/ V →0 (for some φ) then the corresponding F ( R ) ∼ R {sup 2}. We then study α-attractors in more detail using non-perturbative renormalisation group methods to analyse the reconstructed F ( R ). It is seen that α →0 is an ultraviolet stable fixed point of the renormalisation group trajectories.
Approximate convex hull of affine iterated function system attractors
International Nuclear Information System (INIS)
Mishkinis, Anton; Gentil, Christian; Lanquetin, Sandrine; Sokolov, Dmitry
2012-01-01
Highlights: ► We present an iterative algorithm to approximate affine IFS attractor convex hull. ► Elimination of the interior points significantly reduces the complexity. ► To optimize calculations, we merge the convex hull images at each iteration. ► Approximation by ellipses increases speed of convergence to the exact convex hull. ► We present a method of the output convex hull simplification. - Abstract: In this paper, we present an algorithm to construct an approximate convex hull of the attractors of an affine iterated function system (IFS). We construct a sequence of convex hull approximations for any required precision using the self-similarity property of the attractor in order to optimize calculations. Due to the affine properties of IFS transformations, the number of points considered in the construction is reduced. The time complexity of our algorithm is a linear function of the number of iterations and the number of points in the output approximate convex hull. The number of iterations and the execution time increases logarithmically with increasing accuracy. In addition, we introduce a method to simplify the approximate convex hull without loss of accuracy.
Topological and metric properties of Henon-type strange attractors
International Nuclear Information System (INIS)
Cvitanovic, P.; Gunaratne, G.H.; Procaccia, I.
1988-01-01
We use the set of all periodic points of Henon-type mappings to develop a theory of the topological and metric properties of their attractors. The topology of a Henon-type attractor is conveniently represented by a two-dimensional symbol plane, with the allowed and disallowed orbits cleanly separated by the ''pruning front.'' The pruning front is a function discontinuous on every binary rational number, but for maps with finite dissipation chemical bondbchemical bond<1, it is well approximated by a few steps, or, in the symbolic dynamics language, by a finite grammar. Thus equipped with the complete list of allowed periodic points, we reconstruct (to resolution of order b/sup n/) the physical attractor by piecing together the linearized neighborhoods of all periodic points of cycle length n. We use this representation to compute the singularity spectrum f(α). The description in terms of periodic points works very well in the ''hyperbolic phase,'' for α larger than some α/sub c/, where α/sub c/ is the value of α corresponding to the (conjectured) phase transition
Investigating parameters participating in the infant respiratory control system attractor.
Terrill, Philip I; Wilson, Stephen J; Suresh, Sadasivam; Cooper, David M; Dakin, Carolyn
2008-01-01
Theoretically, any participating parameter in a non-linear system represents the dynamics of the whole system. Taken's time delay embedding theory provides the fundamental basis for allowing non-linear analysis to be performed on physiological, time-series data. In practice, only one measurable parameter is required to be measured to convey an accurate representation of the system dynamics. In this paper, the infant respiratory control system is represented using three variables-a digitally sampled respiratory inductive plethysmography waveform, and the derived parameters tidal volume and inter-breath interval time series data. For 14 healthy infants, these data streams were analysed using recurrence plot analysis across one night of sleep. The measured attractor size of these variables followed the same qualitative trends across the nights study. Results suggest that the attractor size measures of the derived IBI and tidal volume are representative surrogates for the raw respiratory waveform. The extent to which the relative attractor sizes of IBI and tidal volume remain constant through changing sleep state could potentially be used to quantify pathology, or maturation of breathing control.
Entropies from Markov Models as Complexity Measures of Embedded Attractors
Directory of Open Access Journals (Sweden)
Julián D. Arias-Londoño
2015-06-01
Full Text Available This paper addresses the problem of measuring complexity from embedded attractors as a way to characterize changes in the dynamical behavior of different types of systems with a quasi-periodic behavior by observing their outputs. With the aim of measuring the stability of the trajectories of the attractor along time, this paper proposes three new estimations of entropy that are derived from a Markov model of the embedded attractor. The proposed estimators are compared with traditional nonparametric entropy measures, such as approximate entropy, sample entropy and fuzzy entropy, which only take into account the spatial dimension of the trajectory. The method proposes the use of an unsupervised algorithm to find the principal curve, which is considered as the “profile trajectory”, that will serve to adjust the Markov model. The new entropy measures are evaluated using three synthetic experiments and three datasets of physiological signals. In terms of consistency and discrimination capabilities, the results show that the proposed measures perform better than the other entropy measures used for comparison purposes.
Lemieux, Maxime; Josset, Nicolas; Roussel, Marie; Couraud, Sébastien; Bretzner, Frédéric
2016-01-01
Locomotion results from an interplay between biomechanical constraints of the muscles attached to the skeleton and the neuronal circuits controlling and coordinating muscle activities. Quadrupeds exhibit a wide range of locomotor gaits. Given our advances in the genetic identification of spinal and supraspinal circuits important to locomotion in the mouse, it is now important to get a better understanding of the full repertoire of gaits in the freely walking mouse. To assess this range, young adult C57BL/6J mice were trained to walk and run on a treadmill at different locomotor speeds. Instead of using the classical paradigm defining gaits according to their footfall pattern, we combined the inter-limb coupling and the duty cycle of the stance phase, thus identifying several types of gaits: lateral walk, trot, out-of-phase walk, rotary gallop, transverse gallop, hop, half-bound, and full-bound. Out-of-phase walk, trot, and full-bound were robust and appeared to function as attractor gaits (i.e., a state to which the network flows and stabilizes) at low, intermediate, and high speeds respectively. In contrast, lateral walk, hop, transverse gallop, rotary gallop, and half-bound were more transient and therefore considered transitional gaits (i.e., a labile state of the network from which it flows to the attractor state). Surprisingly, lateral walk was less frequently observed. Using graph analysis, we demonstrated that transitions between gaits were predictable, not random. In summary, the wild-type mouse exhibits a wider repertoire of locomotor gaits than expected. Future locomotor studies should benefit from this paradigm in assessing transgenic mice or wild-type mice with neurotraumatic injury or neurodegenerative disease affecting gait.
Directory of Open Access Journals (Sweden)
W. Li
2016-12-01
Full Text Available Ultra-violet (UV laser assisted stereolithography is used to print graded interpenetrating polymer networks (IPNs by controlling network formation. Unlike the traditional process where structural change in IPNs is achieved by varying the feeding ratio of monomers or polymer precursors, in this demonstration property is changed by controlled termination of network formation. A photo-initiated process is used to construct IPNs by a combination of radical and cationic network formation in an acrylate/epoxy system. The extent of the cationic network formation is used to control the final properties of the system. Rapid-Scan Fourier Transformation Infrared Spectroscopy (RS-FTIR is used to track the curing kinetics of the two networks and identify key parameters to control the final properties. Atomic force microscopy (AFM and differential scanning calorimetry (DSC confirm the formation of homogenous IPNs, whereas nano-indentation indicates that properties vary with the extent of cationic network formation. The curing characteristics are used to design and demonstrate printing of graded IPNs that show two orders of magnitude variation in mechanical properties in the millimeter scale.
Generating two simultaneously chaotic attractors with a switching piecewise-linear controller
International Nuclear Information System (INIS)
Zheng Zuohuan; Lue Jinhu; Chen Guanrong; Zhou Tianshou; Zhang Suochun
2004-01-01
It has been demonstrated that a piecewise-linear system can generate chaos under suitable conditions. This paper proposes a novel method for simultaneously creating two symmetrical chaotic attractor--an upper-attractor and a lower-attractor--in a 3D linear autonomous system. Basically dynamical behaviors of this new chaotic system are further investigated. Especially, the chaos formation mechanism is explored by analyzing the structure of fixed points and the system trajectories
Discontinuous bifurcation and coexistence of attractors in a piecewise linear map with a gap
International Nuclear Information System (INIS)
Qu Shixian; Lu Yongzhi; Zhang Lin; He Daren
2008-01-01
Coexistence of attractors with striking characteristics is observed in this work, where a stable period-5 attractor coexists successively with chaotic band-11, period-6, chaotic band-12 and band-6 attractors. They are induced by different mechanisms due to the interaction between the discontinuity and the non-invertibility. A characteristic boundary collision bifurcation, is observed. The critical conditions are obtained both analytically and numerically. (general)
Noise-induced attractor annihilation in the delayed feedback logistic map
International Nuclear Information System (INIS)
Pisarchik, A.N.; Martínez-Zérega, B.E.
2013-01-01
We study dynamics of the bistable logistic map with delayed feedback, under the influence of white Gaussian noise and periodic modulation applied to the variable. This system may serve as a model to describe population dynamics under finite resources in noisy environment with seasonal fluctuations. While a very small amount of noise has no effect on the global structure of the coexisting attractors in phase space, an intermediate noise totally eliminates one of the attractors. Slow periodic modulation enhances the attractor annihilation.
Continual observation on crop leaf area index using wireless sensors network
International Nuclear Information System (INIS)
Jiao, Sihong
2014-01-01
Crop structural parameter, i.e. leaf area index(LAI), is the main factor that can effect the solar energy re-assignment in the canopy. An automatic measuring system which is designed on the basis of wireless sensors network(WSN) is present in this paper. The system is comprised of two types of node. One is the measurement nodes which measured solar irradiance and were deployed beneath and above the canopy respectively, and another is a sink node which was used to collect data from the other measurement nodes. The measurement nodes also have ability to repeater data from one node to another and finally transfer signal to the sink node. Then the collected data of sink node are transferred to the data center through GPRS network. Using the field data collected by WSN, canopy structural parameters can be calculated using the direct transmittance which is the ratio of sun radiation captured by the measurement node beneath and above the canopy on different sun altitude angles. The proposed WSN measurement systems which is consisted of about 45 measurement node was deployed in the Heihe watershed to continually observe the crop canopy structural parameters from 25 June to 24 August 2012. To validate the performance of the WSN measured crop structural parameters, the LAI values were also measured by LAI2000. The field preliminary validation results show that the designed system can capture the varies of solar direct canopy transmittance on different time in a day, which is the basis to calculate the target canopy structural parameters. The validation results reveal that the measured LAI values derived from our propose measurement system have acceptable correlation coefficient(R2 from 0.27 to 0.96 and averaged value 0.42) with those derived from LAI2000. So it is a promising way in the agriculture application to utilize the proposed system and thus will be an efficient way to measure the crop structural parameters in the large spatial region and on the long time series
Application of fixed point theory to chaotic attractors of forced oscillators
International Nuclear Information System (INIS)
Stewart, H.B.
1990-11-01
A review of the structure of chaotic attractors of periodically forced second order nonlinear oscillators suggests that the theory of fixed points of transformations gives information about the fundamental topological structure of attractors. First a simple extension of the Levinson index formula is proved. Then numerical evidence is used to formulate plausible conjectures about absorbing regions containing chaotic attractors in forced oscillators. Applying the Levinson formula suggests a fundamental relation between the number of fixed points or periodic points in a section of the chaotic attractor on the one hand, and a topological invariant of an absorbing region on the other hand. (author)
Complicated basins and the phenomenon of amplitude death in coupled hidden attractors
Energy Technology Data Exchange (ETDEWEB)
Chaudhuri, Ushnish [Department of Physics, Sri Venkateswara College, University of Delhi, New Delhi 110021 (India); Department of Physics, National University of Singapore, Singapore 117551 (Singapore); Prasad, Awadhesh, E-mail: awadhesh@physics.du.ac.in [Department of Physics and Astrophysics, University of Delhi, Delhi 110007 (India)
2014-02-07
Understanding hidden attractors, whose basins of attraction do not contain the neighborhood of equilibrium of the system, are important in many physical applications. We observe riddled-like complicated basins of coexisting hidden attractors both in coupled and uncoupled systems. Amplitude death is observed in coupled hidden attractors with no fixed point using nonlinear interaction. A new route to amplitude death is observed in time-delay coupled hidden attractors. Numerical results are presented for systems with no or one stable fixed point. The applications are highlighted.
Toporov, Maria; Löhnert, Ulrich; Potthast, Roland; Cimini, Domenico; De Angelis, Francesco
2017-04-01
Short-term forecasts of current high-resolution numerical weather prediction models still have large deficits in forecasting the exact temporal and spatial location of severe, locally influenced weather such as summer-time convective storms or cool season lifted stratus or ground fog. Often, the thermodynamic instability - especially in the boundary layer - plays an essential role in the evolution of weather events. While the thermodynamic state of the atmosphere is well measured close to the surface (i.e. 2 m) by in-situ sensors and in the upper troposphere by satellite sounders, the planetary boundary layer remains a largely under-sampled region of the atmosphere where only sporadic information from radiosondes or aircraft observations is available. The major objective of the presented DWD-funded project ARON (Extramural Research Programme) is to overcome this observational gap and to design an optimized network of ground based microwave radiometers (MWR) and compact Differential Absorption Lidars (DIAL) for a continuous, near-real-time monitoring of temperature and humidity in the atmospheric boundary layer in order to monitor thermodynamic (in)stability. Previous studies showed, that microwave profilers are well suited for continuously monitoring the temporal development of atmospheric stability (i.e. Cimini et al., 2015) before the initiation of deep convection, especially in the atmospheric boundary layer. However, the vertical resolution of microwave temperature profiles is best in the lowest kilometer above the surface, decreasing rapidly with increasing height. In addition, humidity profile retrievals typically cannot be resolved with more than two degrees of freedom for signal, resulting in a rather poor vertical resolution throughout the troposphere. Typical stability indices used to assess the potential of convection rely on temperature and humidity values not only in the region of the boundary layer but also in the layers above. Therefore, satellite
Directory of Open Access Journals (Sweden)
Sina Waibel
2015-07-01
Full Text Available Background: Integrated health care networks (IHN are promoted in numerous countries as a response to fragmented care delivery by providing a coordinated continuum of services to a defined population. However, evidence on their effectiveness and outcome is scarce, particularly considering continuity across levels of care; that is the patient's experience of connected and coherent care received from professionals of the different care levels over time. The objective was to analyse the chronic obstructive pulmonary disease (COPD patients’ perceptions of continuity of clinical management and information across care levels and continuity of relation in IHN of the public health care system of Catalonia.Methods: A qualitative multiple case study was conducted, where the cases are COPD patients. A theoretical sample was selected in two stages: (1 study contexts: IHN and (2 study cases consisting of COPD patients. Data were collected by means of individual, semi-structured interviews to the patients, their general practitioners and pulmonologists and review of records. A thematic content analysis segmented by IHN and cases with a triangulation of sources and analysists was carried out.Results: COPD patients of all networks perceived that continuity of clinical management was existent due to clear distribution of roles for COPD care across levels, rapid access to care during exacerbations and referrals to secondary care when needed; nevertheless, patients of some networks highlighted too long waiting times to non-urgent secondary care. Physicians generally agreed with patients, however, also indicated unclear distribution of roles, some inadequate referrals and long waiting times to primary care in some networks. Concerning continuity of information, patients across networks considered that their clinical information was transferred across levels via computer and that physicians also used informal communication mechanisms (e-mail, telephone; whereas
Ambrogioni, Luca; Güçlü, Umut; van Gerven, Marcel A. J.; Maris, Eric
2017-01-01
This paper introduces the kernel mixture network, a new method for nonparametric estimation of conditional probability densities using neural networks. We model arbitrarily complex conditional densities as linear combinations of a family of kernel functions centered at a subset of training points. The weights are determined by the outer layer of a deep neural network, trained by minimizing the negative log likelihood. This generalizes the popular quantized softmax approach, which can be seen ...
Directory of Open Access Journals (Sweden)
Salih Börteçine Avci
2017-06-01
Full Text Available This study focuses on the impact of corporate governance, supply chain network governance and competencies such as sales and logistics competence on buyers’ intention to relationship continuity. A total number of 258 questionnaires were distributed to Turkish manufacturing firms, selected using cross-sectional sampling method from the Istanbul and Edirne Chamber of Commerce and Industry in Turkey. The data of survey was analysed using PLS-SEM model with WARP PLS 5.0 software. Our findings indicate that corporate governance and supply chain network governance seem to have a positive effect on sales competence and logistics competence, and together, they influence buyers’ intention to relationship continuity. In this respect, the outcomes of this study may provide valuable insights for the third-party logistics (3PL literature in terms of buyers’ intention to relationship continuity.
Chen, Xiaofeng; Song, Qiankun; Li, Zhongshan; Zhao, Zhenjiang; Liu, Yurong
2018-07-01
This paper addresses the problem of stability for continuous-time and discrete-time quaternion-valued neural networks (QVNNs) with linear threshold neurons. Applying the semidiscretization technique to the continuous-time QVNNs, the discrete-time analogs are obtained, which preserve the dynamical characteristics of their continuous-time counterparts. Via the plural decomposition method of quaternion, homeomorphic mapping theorem, as well as Lyapunov theorem, some sufficient conditions on the existence, uniqueness, and global asymptotical stability of the equilibrium point are derived for the continuous-time QVNNs and their discrete-time analogs, respectively. Furthermore, a uniform sufficient condition on the existence, uniqueness, and global asymptotical stability of the equilibrium point is obtained for both continuous-time QVNNs and their discrete-time version. Finally, two numerical examples are provided to substantiate the effectiveness of the proposed results.
1984-12-01
3. It is assuied that the network software design as J,!veloed functions properly. Sum.mary of Current Knowlede [re aost tip to late sumfnary of the...conversations with the program management staff regarding multi-user and multi-level security issues related to the Integrated-Service/Agency Automated
Ibrahim, K. M.; Jamal, R. K.; Ali, F. H.
2018-05-01
The behaviour of certain dynamical nonlinear systems are described in term as chaos, i.e., systems’ variables change with the time, displaying very sensitivity to initial conditions of chaotic dynamics. In this paper, we study archetype systems of ordinary differential equations in two-dimensional phase spaces of the Rössler model. A system displays continuous time chaos and is explained by three coupled nonlinear differential equations. We study its characteristics and determine the control parameters that lead to different behavior of the system output, periodic, quasi-periodic and chaos. The time series, attractor, Fast Fourier Transformation and bifurcation diagram for different values have been described.
Plykin type attractor in electronic device simulated in MULTISIM
Kuznetsov, Sergey P.
2011-12-01
An electronic device is suggested representing a non-autonomous dynamical system with hyperbolic chaotic attractor of Plykin type in the stroboscopic map, and the results of its simulation with software package NI MULTISIM are considered in comparison with numerical integration of the underlying differential equations. A main practical advantage of electronic devices of this kind is their structural stability that means insensitivity of the chaotic dynamics in respect to variations of functions and parameters of elements constituting the system as well as to interferences and noises.
Multistability and hidden attractors in a relay system with hysteresis
DEFF Research Database (Denmark)
Zhusubaliyev, Zhanybai T.; Mosekilde, Erik; Rubanov, Vasily G.
2015-01-01
with the neighborhood of that cycle. We show how the equilibrium point of a relay system disappears in a boundary-equilibrium bifurcation as the system enters the region of autonomous switching dynamics and demonstrate experimentally how a relay system can exhibit large amplitude chaotic oscillations at high values...... of the supply voltage. By investigating a four-dimensional model of the experimental relay system we finally show how a variety of hidden periodic, quasiperiodic and chaotic attractors arise, transform and disappear through different bifurcations. (C) 2015 Elsevier B.V. All rights reserved....
Generalized pole inflation: Hilltop, natural, and chaotic inflationary attractors
Energy Technology Data Exchange (ETDEWEB)
Terada, Takahiro, E-mail: takahiro.terada@apctp.org [Department of Physics, The University of Tokyo, Tokyo 113-0033 (Japan); Asia Pacific Center for Theoretical Physics, Pohang 37673 (Korea, Republic of)
2016-09-10
A reformulation of inflationary model analyses appeared recently, in which inflationary observables are determined by the structure of a pole in the inflaton kinetic term rather than the shape of the inflaton potential. We comprehensively study this framework with an arbitrary order of the pole taking into account possible additional poles in the kinetic term or in the potential. Depending on the setup, the canonical potential becomes the form of hilltop or plateau models, variants of natural inflation, power-law inflation, or monomial/polynomial chaotic inflation. We demonstrate attractor behaviors of these models and compute corrections from the additional poles to the inflationary observables.
Some statistical properties of strange attractors: engineering view
International Nuclear Information System (INIS)
Mijangos, M; Kontorovich, V; Aguilar-Torrentera, J
2008-01-01
In this paper, the statistical characterization of strange attractors is investigated via the so-called 'model distribution' approach. It is shown that in order to calculate the first four cumulants, which are necessary to create a model distribution of kurtosis approximation, a systematic method for the calculus of the variance needs to be considered. Correspondently, an analytical method based on the Kolmogorov-Sinai (K-S) entropy for variance approximation is herein proposed. The methodology is of interest for its application in the statistical analysis of chaotic systems that model physical phenomena found in some areas of electrical (communication) engineering
Pullback attractors for a singularly nonautonomous plate equation
Directory of Open Access Journals (Sweden)
Vera Lucia Carbone
2011-06-01
Full Text Available We consider the family of singularly nonautonomous plate equations with structural damping $$ u_{tt} + a(t,xu_t - Delta u_t + (-Delta^2 u + lambda u = f(u, $$ in a bounded domain $Omega subset mathbb{R}^n$, with Navier boundary conditions. When the nonlinearity f is dissipative we show that this problem is globally well posed in $H^2_0(Omega imes L^2(Omega$ and has a family of pullback attractors which is upper-semicontinuous under small perturbations of the damping a.
Energy Technology Data Exchange (ETDEWEB)
Dmitriev, Alexander S.; Yemelyanov, Ruslan Yu. [V.A. Kotelnikov Institute of Radio Engineering and Electronics of the RAS Mokhovaya 11-7, Moscow, 125009 (Russian Federation); Moscow Institute of Physics and Technology (State University) 9 Institutskiy per., Dolgoprudny, Moscow, 141700 (Russian Federation); Gerasimov, Mark Yu. [V.A. Kotelnikov Institute of Radio Engineering and Electronics of the RAS Mokhovaya 11-7, Moscow, 125009 (Russian Federation); Itskov, Vadim V. [Moscow Institute of Physics and Technology (State University) 9 Institutskiy per., Dolgoprudny, Moscow, 141700 (Russian Federation)
2016-06-08
The paper deals with a new multi-element processor platform assigned for modelling the behaviour of interacting dynamical systems, i.e., active wireless network. Experimentally, this ensemble is implemented in an active network, the active nodes of which include direct chaotic transceivers and special actuator boards containing microcontrollers for modelling the dynamical systems and an information display unit (colored LEDs). The modelling technique and experimental results are described and analyzed.
Lorenz-like attractors in a nonholonomic model of a rattleback
International Nuclear Information System (INIS)
Gonchenko, A S; Gonchenko, S V
2015-01-01
We study chaotic dynamics in a nonholonomic model of a rattleback stone. We show that, for certain values of parameters that characterise geometrical and physical properties of the stone, a strange Lorenz-like attractor is observed in the model. We also study bifurcation scenarios for the appearance and break-down of this attractor. (paper)
Shift of critical points in the parametrically modulated Henon map with coexisting attractors
International Nuclear Information System (INIS)
Saucedo-Solorio, J.M.; Pisarchik, A.N.; Aboites, V.
2002-01-01
We study how the critical point positions change in the parametrically modulated Henon map with coexisting period-1 and period-3 attractors. In particular, a new type of scaling law is found coinciding with that evidenced by laser experiments. We show that resonance phenomena play a crucial role in deformation of attractors and their basins of attraction
Using periodic modulation to control coexisting attractors induced by delayed feedback
International Nuclear Information System (INIS)
Martinez-Zerega, B.E.; Pisarchik, A.N.; Tsimring, L.S.
2003-01-01
A delay in feedback can stabilize simultaneously several unstable periodic orbits embedded in a chaotic attractor. We show that by modulating the feedback variable it is possible to lock one of these states and eliminate other coexisting periodic attractors. The method is demonstrated with both a logistic map and a CO 2 laser model
International Nuclear Information System (INIS)
Zhou Tiejun; Chen Anping; Zhou Yuyuan
2005-01-01
By using the continuation theorem of coincidence degree theory and Liapunov function, we obtain some sufficient criteria to ensure the existence and global exponential stability of periodic solution to the bidirectional associative memory (BAM) neural networks with periodic coefficients and continuously distributed delays. These results improve and generalize the works of papers [J. Cao, L. Wang, Phys. Rev. E 61 (2000) 1825] and [Z. Liu, A. Chen, J. Cao, L. Huang, IEEE Trans. Circuits Systems I 50 (2003) 1162]. An example is given to illustrate that the criteria are feasible
Zhou, distributed delays [rapid communication] T.; Chen, A.; Zhou, Y.
2005-08-01
By using the continuation theorem of coincidence degree theory and Liapunov function, we obtain some sufficient criteria to ensure the existence and global exponential stability of periodic solution to the bidirectional associative memory (BAM) neural networks with periodic coefficients and continuously distributed delays. These results improve and generalize the works of papers [J. Cao, L. Wang, Phys. Rev. E 61 (2000) 1825] and [Z. Liu, A. Chen, J. Cao, L. Huang, IEEE Trans. Circuits Systems I 50 (2003) 1162]. An example is given to illustrate that the criteria are feasible.
Directory of Open Access Journals (Sweden)
Maria Cristina Lima Paniago Lopes
2013-04-01
Full Text Available This research aims to analyze continuous training of teachers indigenous and non-indigenous, mediated by a social network on Ning called Internet under an intercultural perspective. This social network has come up as a virtual community as they have been established emotional ties, webs of connections and relationships between its participants. This is a qualitative research and collaborative in the sense that the experiences of researchers and teachers are valued and shared within a social context. The results show that participants in the group continuing of education, despite their difficulties using the technology itself and with little technological infrastructure, they see these virtual spaces as a possibility for new discoveries, creations and knowledge production, not forsaking the customs, traditions and their own culture.
Generation and control of multi-scroll chaotic attractors in fractional order systems
International Nuclear Information System (INIS)
Ahmad, Wajdi M.
2005-01-01
The objective of this paper is twofold: on one hand we demonstrate the generation of multi-scroll attractors in fractional order chaotic systems. Then, we design state feedback controllers to eliminate chaos from the system trajectories. It is demonstrated that modifying the underlying nonlinearity of the fractional chaotic system results in the birth of multiple chaotic attractors, thus forming the so called multi-scroll attractors. The presence of chaotic behavior is evidenced by a positive largest Lyapunov exponent computed for the output time series. We investigate generation and control of multi-scroll attractors in two different models, both of which are fractional order and chaotic: an electronic oscillator, and a mechanical 'jerk' model. The current findings extend previously reported results on generation of n-scroll attractors from the domain of integer order to the domain of fractional order chaotic systems, and addresses the issue of controlling such chaotic behaviors. Our investigations are validated through numerical simulations
Non-Abelian magnetized blackholes and unstable attractors
Energy Technology Data Exchange (ETDEWEB)
Mosaffa, A.E. [Institute for Studies in Theoretical Physics and Mathematics (IPM), PO Box 19395-5531, Tehran (Iran, Islamic Republic of)], E-mail: mosaffa@theory.ipm.ac.ir; Randjbar-Daemi, S. [The Abdus Salam International Centre for Theoretical Physics, Strada Costiera 11 34014, Trieste (Italy)], E-mail: seif@ictp.trieste.it; Sheikh-Jabbari, M.M. [Institute for Studies in Theoretical Physics and Mathematics (IPM), PO Box 19395-5531, Tehran (Iran, Islamic Republic of)], E-mail: jabbari@theory.ipm.ac.ir
2008-01-21
Fluctuations of non-Abelian gauge fields in a background magnetic charge contain 'tachyonic' modes which as we will show cause an instability of the background. We extend this result to the cases where the background charge (flux) is coupled to four-dimensional Einstein gravity and show that the corresponding spherically symmetric geometries, which in the absence of a cosmological constant are of the form of (colored) Reissner-Nordstroem blackholes or the AdS{sub 2}xS{sup 2}, are also unstable unless the flux assumes its smallest allowed value, in which case the configuration is stable. We discuss the relevance of these instabilities to several places in string theory including various string compactifications and the attractor mechanism. Our results for the latter imply that the attractor mechanism shown to work for the extremal Abelian charged blackholes, cannot be applied in a straightforward way to the extremal non-Abelian colored blackholes, with the exception of the minimally charged stable ones.
Universality of multi-field α-attractors
Achúcarro, Ana; Kallosh, Renata; Linde, Andrei; Wang, Dong-Gang; Welling, Yvette
2018-04-01
We study a particular version of the theory of cosmological α-attractors with α=1/3, in which both the dilaton (inflaton) field and the axion field are light during inflation. The kinetic terms in this theory originate from maximal Script N=4 superconformal symmetry and from maximal Script N=8 supergravity. We show that because of the underlying hyperbolic geometry of the moduli space in this theory, it exhibits double attractor behavior: their cosmological predictions are stable not only with respect to significant modifications of the dilaton potential, but also with respect to significant modifications of the axion potential: nssimeq1‑2/N, rsimeq4/N2. We also show that the universality of predictions extends to other values of α lesssim Script O(1) with general two-field potentials that may or may not have an embedding in supergravity. Our results support the idea that inflation involving multiple, not stabilized, light fields on a hyperbolic manifold may be compatible with current observational constraints for a broad class of potentials.
Reconstructing a f ( R ) theory from the α-Attractors
Energy Technology Data Exchange (ETDEWEB)
Miranda, T.; Fabris, J. C.; Piattella, O. F., E-mail: tays.andrade@aluno.ufes.br, E-mail: oliver.piattella@pq.cnpq.br, E-mail: fabris@pq.cnpq.br [Department of Physics, Universidade Federal do Espírito Santo, avenida Fernando Ferrari 514, 29075-910 Vitória, Espírito Santo (Brazil)
2017-09-01
We show an analogy at high curvature between a f ( R ) = R + aR {sup n} {sup −} {sup 1} + bR {sup 2} theory and the α-Attractors. We calculate the expressions of the parameters a , b and n as functions of α and the predictions of the model f ( R ) = R + aR {sup n} {sup −} {sup 1} + bR {sup 2} on the scalar spectral index n {sub s} and the tensor-to-scalar ratio r . We find that the power law correction R {sup n} {sup −} {sup 1} allows for a production of gravitational waves enhanced with respect to the one in the Starobinsky model, while maintaining a viable prediction on n {sub s}. We numerically reconstruct the full α-Attractors class of models testing the goodness of our high-energy approximation f ( R ) = R + aR {sup n} {sup −} {sup 1} + bR {sup 2}. Moreover, we also investigate the case of a single power law f ( R ) = γ R {sup 2} {sup −} {sup δ} theory, with γ and δ free parameters. We calculate analytically the predictions of this model on the scalar spectral index n {sub s} and the tensor-to-scalar ratio r and the values of δ which are allowed from the current observational results. We find that −0.015 < δ < 0.016, confirming once again the excellent agreement between the Starobinsky model and observation.
Neuronal Networks in Children with Continuous Spikes and Waves during Slow Sleep
Siniatchkin, Michael; Groening, Kristina; Moehring, Jan; Moeller, Friederike; Boor, Rainer; Brodbeck, Verena; Michel, Christoph M.; Rodionov, Roman; Lemieux, Louis; Stephani, Ulrich
2010-01-01
Epileptic encephalopathy with continuous spikes and waves during slow sleep is an age-related disorder characterized by the presence of interictal epileptiform discharges during at least greater than 85% of sleep and cognitive deficits associated with this electroencephalography pattern. The pathophysiological mechanisms of continuous spikes and…
Local Dynamics in Trained Recurrent Neural Networks.
Rivkind, Alexander; Barak, Omri
2017-06-23
Learning a task induces connectivity changes in neural circuits, thereby changing their dynamics. To elucidate task-related neural dynamics, we study trained recurrent neural networks. We develop a mean field theory for reservoir computing networks trained to have multiple fixed point attractors. Our main result is that the dynamics of the network's output in the vicinity of attractors is governed by a low-order linear ordinary differential equation. The stability of the resulting equation can be assessed, predicting training success or failure. As a consequence, networks of rectified linear units and of sigmoidal nonlinearities are shown to have diametrically different properties when it comes to learning attractors. Furthermore, a characteristic time constant, which remains finite at the edge of chaos, offers an explanation of the network's output robustness in the presence of variability of the internal neural dynamics. Finally, the proposed theory predicts state-dependent frequency selectivity in the network response.
Local Dynamics in Trained Recurrent Neural Networks
Rivkind, Alexander; Barak, Omri
2017-06-01
Learning a task induces connectivity changes in neural circuits, thereby changing their dynamics. To elucidate task-related neural dynamics, we study trained recurrent neural networks. We develop a mean field theory for reservoir computing networks trained to have multiple fixed point attractors. Our main result is that the dynamics of the network's output in the vicinity of attractors is governed by a low-order linear ordinary differential equation. The stability of the resulting equation can be assessed, predicting training success or failure. As a consequence, networks of rectified linear units and of sigmoidal nonlinearities are shown to have diametrically different properties when it comes to learning attractors. Furthermore, a characteristic time constant, which remains finite at the edge of chaos, offers an explanation of the network's output robustness in the presence of variability of the internal neural dynamics. Finally, the proposed theory predicts state-dependent frequency selectivity in the network response.
Jacomy, Mathieu; Venturini, Tommaso; Heymann, Sebastien; Bastian, Mathieu
2014-01-01
Gephi is a network visualization software used in various disciplines (social network analysis, biology, genomics...). One of its key features is the ability to display the spatialization process, aiming at transforming the network into a map, and ForceAtlas2 is its default layout algorithm. The latter is developed by the Gephi team as an all-around solution to Gephi users' typical networks (scale-free, 10 to 10,000 nodes). We present here for the first time its functioning and settings. ForceAtlas2 is a force-directed layout close to other algorithms used for network spatialization. We do not claim a theoretical advance but an attempt to integrate different techniques such as the Barnes Hut simulation, degree-dependent repulsive force, and local and global adaptive temperatures. It is designed for the Gephi user experience (it is a continuous algorithm), and we explain which constraints it implies. The algorithm benefits from much feedback and is developed in order to provide many possibilities through its settings. We lay out its complete functioning for the users who need a precise understanding of its behaviour, from the formulas to graphic illustration of the result. We propose a benchmark for our compromise between performance and quality. We also explain why we integrated its various features and discuss our design choices.
The Vague Plague -The continual innovation and spread of BPR and IT in Enterprise Networks
DEFF Research Database (Denmark)
Koch, Christian
1998-01-01
The empirical point of departure of this article is the erosion of enterprise boundaries, which create new conditions for enterprise actors, i.e. they are to an increasing extent forced to operate in networks. They are confronted with a number of unstable and developing change drivers. The focus ...... as a "plague" like SAP R/3, are actually reshaped by the enterprises....
Middel, H.G.A.; Groen, Arend J.; Fisscher, O.A.M.
2004-01-01
More than ever, companies are challenged to improve their performance and respond quickly and accurately to changes within the market. As competitive battlefield is moving towards the level of networks of organisations, the individual firm is an inadequate entity for identifying improvements.
Lai, Qiang; Zhao, Xiao-Wen; Rajagopal, Karthikeyan; Xu, Guanghui; Akgul, Akif; Guleryuz, Emre
2018-01-01
This paper considers the generation of multi-butterfly chaotic attractors from a generalised Sprott C system with multiple non-hyperbolic equilibria. The system is constructed by introducing an additional variable whose derivative has a switching function to the Sprott C system. It is numerically found that the system creates two-, three-, four-, five-butterfly attractors and any other multi-butterfly attractors. First, the dynamic analyses of multi-butterfly chaotic attractors are presented. Secondly, the field programmable gate array implementation, electronic circuit realisation and random number generator are done with the multi-butterfly chaotic attractors.
Controlled perturbation-induced switching in pulse-coupled oscillator networks
International Nuclear Information System (INIS)
Schittler Neves, Fabio; Timme, Marc
2009-01-01
Pulse-coupled systems such as spiking neural networks exhibit nontrivial invariant sets in the form of attracting yet unstable saddle periodic orbits where units are synchronized into groups. Heteroclinic connections between such orbits may in principle support switching processes in these networks and enable novel kinds of neural computations. For small networks of coupled oscillators, we here investigate under which conditions and how system symmetry enforces or forbids certain switching transitions that may be induced by perturbations. For networks of five oscillators, we derive explicit transition rules that for two cluster symmetries deviate from those known from oscillators coupled continuously in time. A third symmetry yields heteroclinic networks that consist of sets of all unstable attractors with that symmetry and the connections between them. Our results indicate that pulse-coupled systems can reliably generate well-defined sets of complex spatiotemporal patterns that conform to specific transition rules. We briefly discuss possible implications for computation with spiking neural systems.
Controlled perturbation-induced switching in pulse-coupled oscillator networks
Energy Technology Data Exchange (ETDEWEB)
Schittler Neves, Fabio; Timme, Marc [Network Dynamics Group, Max Planck Institute for Dynamics and Self-Organization, Goettingen, D-37073 (Germany); Bernstein Center for Computational Neuroscience (BCCN), Goettingen (Germany)], E-mail: neves@nld.ds.mpg.de, E-mail: timme@nld.ds.mpg.de
2009-08-28
Pulse-coupled systems such as spiking neural networks exhibit nontrivial invariant sets in the form of attracting yet unstable saddle periodic orbits where units are synchronized into groups. Heteroclinic connections between such orbits may in principle support switching processes in these networks and enable novel kinds of neural computations. For small networks of coupled oscillators, we here investigate under which conditions and how system symmetry enforces or forbids certain switching transitions that may be induced by perturbations. For networks of five oscillators, we derive explicit transition rules that for two cluster symmetries deviate from those known from oscillators coupled continuously in time. A third symmetry yields heteroclinic networks that consist of sets of all unstable attractors with that symmetry and the connections between them. Our results indicate that pulse-coupled systems can reliably generate well-defined sets of complex spatiotemporal patterns that conform to specific transition rules. We briefly discuss possible implications for computation with spiking neural systems.
Chwala, Christian; Boose, Yvonne; Smiatek, Gerhard; Kunstmann, Harald
2017-04-01
Commercial microwave link (CML) networks have proven to be a valuable source for rainfall information over the last years. However, up to now, analysis of CML data was always limited to certain snapshots of data for historic periods due to limited data access. With the real-time availability of CML data in Germany (Chwala et al. 2016) this situation has improved significantly. We are continuously acquiring and processing data from 3000 CMLs in Germany in near real-time with one minute temporal resolution. Currently the data acquisition system is extended to 10000 CMLs so that the whole of Germany is covered and a continuous country-wide rainfall product can be provided. In this contribution we will elaborate on the challenges and solutions regarding data acquisition, data management and robust processing. We will present the details of our data acquisition system that we run operationally at the network of the CML operator Ericsson Germany to solve the problem of limited data availability. Furthermore we will explain the implementation of our data base, its web-frontend for easy data access and present our data processing algorithms. Finally we will showcase an application of our data in hydrological modeling and its potential usage to improve radar QPE. Bibliography: Chwala, C., Keis, F., and Kunstmann, H.: Real-time data acquisition of commercial microwave link networks for hydrometeorological applications, Atmos. Meas. Tech., 9, 991-999, doi:10.5194/amt-9-991-2016, 2016
Wang, Chunhua; Liu, Xiaoming; Xia, Hu
2017-03-01
In this paper, two kinds of novel ideal active flux-controlled smooth multi-piecewise quadratic nonlinearity memristors with multi-piecewise continuous memductance function are presented. The pinched hysteresis loop characteristics of the two memristor models are verified by building a memristor emulator circuit. Using the two memristor models establish a new memristive multi-scroll Chua's circuit, which can generate 2N-scroll and 2N+1-scroll chaotic attractors without any other ordinary nonlinear function. Furthermore, coexisting multi-scroll chaotic attractors are found in the proposed memristive multi-scroll Chua's circuit. Phase portraits, Lyapunov exponents, bifurcation diagrams, and equilibrium point analysis have been used to research the basic dynamics of the memristive multi-scroll Chua's circuit. The consistency of circuit implementation and numerical simulation verifies the effectiveness of the system design.
Inferring network structure in non-normal and mixed discrete-continuous genomic data.
Bhadra, Anindya; Rao, Arvind; Baladandayuthapani, Veerabhadran
2018-03-01
Inferring dependence structure through undirected graphs is crucial for uncovering the major modes of multivariate interaction among high-dimensional genomic markers that are potentially associated with cancer. Traditionally, conditional independence has been studied using sparse Gaussian graphical models for continuous data and sparse Ising models for discrete data. However, there are two clear situations when these approaches are inadequate. The first occurs when the data are continuous but display non-normal marginal behavior such as heavy tails or skewness, rendering an assumption of normality inappropriate. The second occurs when a part of the data is ordinal or discrete (e.g., presence or absence of a mutation) and the other part is continuous (e.g., expression levels of genes or proteins). In this case, the existing Bayesian approaches typically employ a latent variable framework for the discrete part that precludes inferring conditional independence among the data that are actually observed. The current article overcomes these two challenges in a unified framework using Gaussian scale mixtures. Our framework is able to handle continuous data that are not normal and data that are of mixed continuous and discrete nature, while still being able to infer a sparse conditional sign independence structure among the observed data. Extensive performance comparison in simulations with alternative techniques and an analysis of a real cancer genomics data set demonstrate the effectiveness of the proposed approach. © 2017, The International Biometric Society.
You, Hongzhi; Wang, Da-Hui
2017-01-01
Neural networks configured with winner-take-all (WTA) competition and N-methyl-D-aspartate receptor (NMDAR)-mediated synaptic dynamics are endowed with various dynamic characteristics of attractors underlying many cognitive functions. This paper presents a novel method for neuromorphic implementation of a two-variable WTA circuit with NMDARs aimed at implementing decision-making, working memory and hysteresis in visual perceptions. The method proposed is a dynamical system approach of circuit synthesis based on a biophysically plausible WTA model. Notably, slow and non-linear temporal dynamics of NMDAR-mediated synapses was generated. Circuit simulations in Cadence reproduced ramping neural activities observed in electrophysiological recordings in experiments of decision-making, the sustained activities observed in the prefrontal cortex during working memory, and classical hysteresis behavior during visual discrimination tasks. Furthermore, theoretical analysis of the dynamical system approach illuminated the underlying mechanisms of decision-making, memory capacity and hysteresis loops. The consistence between the circuit simulations and theoretical analysis demonstrated that the WTA circuit with NMDARs was able to capture the attractor dynamics underlying these cognitive functions. Their physical implementations as elementary modules are promising for assembly into integrated neuromorphic cognitive systems.
Bijeljic, B.
2008-05-01
This talk will describe and highlight the advantages offered by a methodology that unifies pore network modeling, CTRW theory and experiment in description of solute dispersion in porous media. Solute transport in a porous medium is characterized by the interplay of advection and diffusion (described by Peclet number, Pe) that cause spreading of solute particles. This spreading is traditionally described by dispersion coefficients, D, defined by σ 2 = 2Dt, where σ 2 is the variance of the solute position and t is the time. Using a pore-scale network model based on particle tracking, the rich Peclet- number dependence of dispersion coefficient is predicted from first principles and is shown to compare well with experimental data for restricted diffusion, transition, power-law and mechanical dispersion regimes in the asymptotic limit. In the asymptotic limit D is constant and can be used in an averaged advection-dispersion equation. However, it is highly important to recognize that, until the velocity field is fully sampled, the particle transport is non-Gaussian and D possesses temporal or spatial variation. Furthermore, temporal probability density functions (PDF) of tracer particles are studied in pore networks and an excellent agreement for the spectrum of transition times for particles from pore to pore is obtained between network model results and CTRW theory. Based on the truncated power-law interpretation of PDF-s, the physical origin of the power-law scaling of dispersion coefficient vs. Peclet number has been explained for unconsolidated porous media, sands and a number of sandstones, arriving at the same conclusion from numerical network modelling, analytic CTRW theory and experiment. Future directions for further applications of the methodology presented are discussed in relation to the scale- dependent solute dispersion and reactive transport. Significance of pre-asymptotic dispersion in porous media is addressed from pore-scale upwards and the impact
Wang, Xian-Jia; Quan, Ji; Liu, Wei-Bing
2012-05-01
This paper studies the continuous prisoner's dilemma games (CPDG) on Barabasi—Albert (BA) networks. In the model, each agent on a vertex of the networks makes an investment and interacts with all of his neighboring agents. Making an investment is costly, but which benefits its neighboring agents, where benefit and cost depend on the level of investment made. The payoff of each agent is given by the sum of payoffs it receives in its interactions with all its neighbors. Not only payoff, individual's guilty emotion in the games has also been considered. The negative guilty emotion produced in comparing with its neighbors can reduce the utility of individuals directly. We assume that the reduction amount depends on the individual's degree and a baseline level parameter. The group's cooperative level is characterized by the average investment of the population. Each player makes his investment in the next step based on a convex combination of the investment of his best neighbors in the last step, his best history strategies in the latest steps which number is controlled by a memory length parameter, and a uniformly distributed random number. Simulation results show that this degree-dependent guilt mechanism can promote the evolution of cooperation dramatically comparing with degree-independent guilt or no guilt cases. Imitation, memory, uncertainty coefficients and network structure also play determinant roles in the cooperation level of the population. All our results may shed some new light on studying the evolution of cooperation based on network reciprocity mechanisms.
Emergence of unstable itinerant orbits in a recurrent neural network model
International Nuclear Information System (INIS)
Suemitsu, Yoshikazu; Nara, Shigetoshi
2005-01-01
A recurrent neural network model with time delay is investigated by numerical methods. The model functions as both conventional associative memory and also enables us to embed a new kind of memory attractor that cannot be realized in models without time delay, for example chain-ring attractors. This is attributed to the fact that the time delay extends the available state space dimension. The difference between the basin structures of chain-ring attractors and of isolated cycle attractors is investigated with respect to the two attractor pattern sets, random memory patterns and designed memory patterns with intended structures. Compared to isolated attractors with random memory patterns, the basins of chain-ring attractors are reduced considerably. Computer experiments confirm that the basin volume of each embedded chain-ring attractor shrinks and the emergence of unstable itinerant orbits in the outer state space of the memory attractor basins is discovered. The instability of such itinerant orbits is investigated. Results show that a 1-bit difference in initial conditions does not exceed 10% of a total dimension within 100 updating steps
Energy Technology Data Exchange (ETDEWEB)
Wolk, P.J. van der; Wang, J. [Delft Univ. of Technology (Netherlands); Sietsma, J.; Zwaag, S. van der [Delft Univ. of Technology, Lab. for Materials Science (Netherlands)
2002-12-01
The neural network model of Van der Wolk et al. (2002) describes the effect of composition on the phase regions of the continuous cooling transformation (CCT) diagram, yet does not consider the fractions of microstructural components and the hardness data that are often quoted in CCT diagrams. In the present paper, the construction of two more neural network models, one for the fractions of ferrite, pearlite, bainite and martensite in the microstructure, and one for the hardness after cooling, using the data of 338 and 412 diagrams, respectively. The accuracy of each model was found to be similar to the expected experimental error; moreover, the models were found to be mutually consistent, although they have been constructed independently. Furthermore, the trends in these properties for alloying elements can be quantified with the models, and are largely in line with metallurgical expectations. (orig.)
Lu, Weizhao; Huang, Chunhui; Hou, Kun; Shi, Liting; Zhao, Huihui; Li, Zhengmei; Qiu, Jianfeng
2018-05-01
In continuous-variable quantum key distribution (CV-QKD), weak signal carrying information transmits from Alice to Bob; during this process it is easily influenced by unknown noise which reduces signal-to-noise ratio, and strongly impacts reliability and stability of the communication. Recurrent quantum neural network (RQNN) is an artificial neural network model which can perform stochastic filtering without any prior knowledge of the signal and noise. In this paper, a modified RQNN algorithm with expectation maximization algorithm is proposed to process the signal in CV-QKD, which follows the basic rule of quantum mechanics. After RQNN, noise power decreases about 15 dBm, coherent signal recognition rate of RQNN is 96%, quantum bit error rate (QBER) drops to 4%, which is 6.9% lower than original QBER, and channel capacity is notably enlarged.
Fast convergence of spike sequences to periodic patterns in recurrent networks
International Nuclear Information System (INIS)
Jin, Dezhe Z.
2002-01-01
The dynamical attractors are thought to underlie many biological functions of recurrent neural networks. Here we show that stable periodic spike sequences with precise timings are the attractors of the spiking dynamics of recurrent neural networks with global inhibition. Almost all spike sequences converge within a finite number of transient spikes to these attractors. The convergence is fast, especially when the global inhibition is strong. These results support the possibility that precise spatiotemporal sequences of spikes are useful for information encoding and processing in biological neural networks
Explosive attractor solutions to a universal cubic delay equation
Sanz-Orozco, D.; Berk, H. L.
2017-05-01
New explosive attractor solutions have been found in a universal cubic delay equation that has been studied in both the plasma and the fluid mechanics literature. Through computational simulations and analytic approximations, it is found that the oscillatory component of the explosive mode amplitude solutions are described through multi-frequency Fourier expansions with respect to a pseudo-time variable. The spectral dependence of these solutions as a function of a system parameter, ϕ , is studied. The mode amplitude that is described in the explosive regime has two main features: a well-known envelope ( t 0 - t ) - 5 / 2 , with t0 the blow-up time of the amplitude, and a spectrum of discrete oscillations with ever-increasing frequencies, which may give experimental information about the properties of a system's equilibrium.
Strange attractor of Henon map and its basin
Institute of Scientific and Technical Information of China (English)
曹永罗
1995-01-01
In this paper, Henon map is considered. For a positive measure set of parameters (a, b), we construct a trapping region G of topologically transitive strange attractor Aa,b for Ta,b, and prove that Aa,b= ∩n≥0Ta,bnG, and the basin B(Aa,b) of Aa,b is exactly the union of domain whose boundary is contained in w5(p) ∪wu(p) and ws(p). Therefore, that the conjecture posed by Benedicks and Carleson about the basin of strange attactor is true is proved. Furthermore, B(Aa,b) is simply connected and path-connected, w4(p2) is contained in the attainable boundary set of B(Aa,b) (where p2 is another hyperbolic fixed point of Ta,b).
Noether symmetry approach in the cosmological alpha-attractors
Kaewkhao, Narakorn; Kanesom, Thanyagamon; Channuie, Phongpichit
2018-06-01
In cosmological framework, Noether symmetry technique has revealed a useful tool in order to examine exact solutions. In this work, we first introduce the Jordan-frame Lagrangian and apply the conformal transformation in order to obtain the Lagrangian equivalent to Einstein-frame form. We then analyze the dynamics of the field in the cosmological alpha-attractors using the Noether symmetry approach by focusing on the single field scenario in the Einstein-frame form. We show that with a Noether symmetry the corresponding dynamical system can be completely integrated and the potential exhibited by the symmetry can be exactly obtained. With the proper choice of parameters, the behavior of the scale factor displays an exponential (de Sitter) behavior at the present epoch. Moreover, we discover that the Hubble parameters strongly depends on the initial values of parameters exhibited by the Noether symmetry. Interestingly, it can retardedly evolve and becomes a constant in the present epoch in all cases.
Detection of generalized synchronization using echo state networks
Ibáñez-Soria, D.; Garcia-Ojalvo, J.; Soria-Frisch, A.; Ruffini, G.
2018-03-01
Generalized synchronization between coupled dynamical systems is a phenomenon of relevance in applications that range from secure communications to physiological modelling. Here, we test the capabilities of reservoir computing and, in particular, echo state networks for the detection of generalized synchronization. A nonlinear dynamical system consisting of two coupled Rössler chaotic attractors is used to generate temporal series consisting of time-locked generalized synchronized sequences interleaved with unsynchronized ones. Correctly tuned, echo state networks are able to efficiently discriminate between unsynchronized and synchronized sequences even in the presence of relatively high levels of noise. Compared to other state-of-the-art techniques of synchronization detection, the online capabilities of the proposed Echo State Network based methodology make it a promising choice for real-time applications aiming to monitor dynamical synchronization changes in continuous signals.
International Nuclear Information System (INIS)
Aguirre-Hernández, B.; Campos-Cantón, E.; López-Renteria, J.A.; Díaz González, E.C.
2015-01-01
In this paper, we consider characteristic polynomials of n-dimensional systems that determine a segment of polynomials. One parameter is used to characterize this segment of polynomials in order to determine the maximal interval of dissipativity and unstability. Then we apply this result to the generation of a family of attractors based on a class of unstable dissipative systems (UDS) of type affine linear systems. This class of systems is comprised of switched linear systems yielding strange attractors. A family of these chaotic switched systems is determined by the maximal interval of perturbation of the matrix that governs the dynamics for still having scroll attractors
Novel four-wing and eight-wing attractors using coupled chaotic Lorenz systems
International Nuclear Information System (INIS)
Grassi, Giuseppe
2008-01-01
This paper presents the problem of generating four-wing (eight-wing) chaotic attractors. The adopted method consists in suitably coupling two (three) identical Lorenz systems. In analogy with the original Lorenz system, where the two wings of the butterfly attractor are located around the two equilibria with the unstable pair of complex-conjugate eigenvalues, this paper shows that the four wings (eight wings) of these novel attractors are located around the four (eight) equilibria with two (three) pairs of unstable complex-conjugate eigenvalues. (general)
Implementation of a novel two-attractor grid multi-scroll chaotic system
International Nuclear Information System (INIS)
Xiao-Hua, Luo; Zheng-Wei, Tu; Xi-Rui, Liu; Chang, Cai; Pu, Gong; Yi-Long, Liang
2010-01-01
This paper proposed a method of generating two attractors in a novel grid multi-scroll chaotic system. Based on a newly generated three-dimensional system, a two-attractor grid multi-scroll attractor system can be generated by adding two triangular waves and a sign function. Some basic dynamical properties, such as equilibrium points, bifurcations, and phase diagrams, were studied. Furthermore, the system was experimentally confirmed by an electronic circuit. The circuit simulation results and numerical simulation results verified the feasibility of this method. (general)
Wang, Xiaohu; Lu, Kening; Wang, Bixiang
2018-01-01
In this paper, we study the Wong-Zakai approximations given by a stationary process via the Wiener shift and their associated long term behavior of the stochastic reaction-diffusion equation driven by a white noise. We first prove the existence and uniqueness of tempered pullback attractors for the Wong-Zakai approximations of stochastic reaction-diffusion equation. Then, we show that the attractors of Wong-Zakai approximations converges to the attractor of the stochastic reaction-diffusion equation for both additive and multiplicative noise.
How organisms do the right thing: The attractor hypothesis
Emlen, J.M.; Freeman, D.C.; Mills, A.; Graham, J.H.
1998-01-01
Neo-Darwinian theory is highly successful at explaining the emergence of adaptive traits over successive generations. However, there are reasons to doubt its efficacy in explaining the observed, impressively detailed adaptive responses of organisms to day-to-day changes in their surroundings. Also, the theory lacks a clear mechanism to account for both plasticity and canalization. In effect, there is a growing sentiment that the neo-Darwinian paradigm is incomplete, that something more than genetic structure, mutation, genetic drift, and the action of natural selection is required to explain organismal behavior. In this paper we extend the view of organisms as complex self-organizing entities by arguing that basic physical laws, coupled with the acquisitive nature of organisms, makes adaptation all but tautological. That is, much adaptation is an unavoidable emergent property of organisms' complexity and, to some a significant degree, occurs quite independently of genomic changes wrought by natural selection. For reasons that will become obvious, we refer to this assertion as the attractor hypothesis. The arguments also clarify the concept of "adaptation." Adaptation across generations, by natural selection, equates to the (game theoretic) maximization of fitness (the success with which one individual produces more individuals), while self-organizing based adaptation, within generations, equates to energetic efficiency and the matching of intake and biosynthesis to need. Finally, we discuss implications of the attractor hypothesis for a wide variety of genetical and physiological phenomena, including genetic architecture, directed mutation, genetic imprinting, paramutation, hormesis, plasticity, optimality theory, genotype-phenotype linkage and puncuated equilibrium, and present suggestions for tests of the hypothesis. ?? 1998 American Institute of Physics.
Directory of Open Access Journals (Sweden)
Franco Davoli
2008-10-01
Full Text Available The increasing interest in systems able to provide users with immersive services (e.g., domotics, context-aware applications, and immersive distance learning tools has encouraged the development of cheap and effective platforms aimed at tracking objects and people within a certain space. In this context, wireless sensor networks (WSNs can play a very important role, since specialized sensors can be fruitfully exploited in order to generate/receive signals by means of which the WSN can derive the position of nodes joined to the objects to be tracked. The paper presents an original localization platform that exploits a single-hop WSN, based on a Microchip MCU and a Cypress RF device, to track its moving nodes. Specifically, the nodes of the network are divided into three sets: the first set consists of anchor nodes that, according to the commands from the sink (the central node of the WSN, generate ultrasonic pulses. These pulses are received by the second set of (moving nodes, which estimate the pulse time trip and communicate it to the sink. Finally, the last set is constituted by general purpose nodes that collect any kind of data from the surrounding field. The sink gathers all the data, computes the position of moving nodes, and transfers information to external users on the Internet. The algorithms adopted to manage the network and to localize moving nodes are discussed. A working prototype based upon the hardware platform, software, and protocol described in this paper has been deployed and tested, and some results are shown. Simulation results of the localization system are presented to show system scalability.
International Nuclear Information System (INIS)
Wang Shen-Quan; Feng Jian; Zhao Qing
2012-01-01
In this paper, the problem of delay-distribution-dependent stability is investigated for continuous-time recurrent neural networks (CRNNs) with stochastic delay. Different from the common assumptions on time delays, it is assumed that the probability distribution of the delay taking values in some intervals is known a priori. By making full use of the information concerning the probability distribution of the delay and by using a tighter bounding technique (the reciprocally convex combination method), less conservative asymptotic mean-square stable sufficient conditions are derived in terms of linear matrix inequalities (LMIs). Two numerical examples show that our results are better than the existing ones. (general)
Directory of Open Access Journals (Sweden)
F. Hamzezadeh
2014-01-01
Full Text Available In many systems such as computer network, fuel distribution, and transportation system, it is necessary to change the capacity of some arcs in order to increase maximum flow value from source s to sink t, while the capacity change incurs minimum cost. In real-time networks, some factors cause loss of arc’s flow. For example, in some flow distribution systems, evaporation, erosion or sediment in pipes waste the flow. Here we define a real capacity, or the so-called functional capacity, which is the operational capacity of an arc. In other words, the functional capacity of an arc equals the possible maximum flow that may pass through the arc. Increasing the functional arcs capacities incurs some cost. There is a certain resource available to cover the costs. First, we construct a mathematical model to minimize the total cost of expanding the functional capacities to the required levels. Then, we consider the loss of flow on each arc as a stochastic variable and compute the system reliability.
Zhu, Wei; Wang, Dandan; Liu, Lu; Feng, Gang
2017-08-18
This paper investigates exponential stabilization of continuous-time dynamic systems (CDSs) via event-based impulsive control (EIC) approaches, where the impulsive instants are determined by certain state-dependent triggering condition. The global exponential stability criteria via EIC are derived for nonlinear and linear CDSs, respectively. It is also shown that there is no Zeno-behavior for the concerned closed loop control system. In addition, the developed event-based impulsive scheme is applied to the synchronization problem of master and slave memristive neural networks. Furthermore, a self-triggered impulsive control scheme is developed to avoid continuous communication between the master system and slave system. Finally, two numerical simulation examples are presented to illustrate the effectiveness of the proposed event-based impulsive controllers.
Emergent properties of gene evolution: Species as attractors in phenotypic space
Reuveni, Eli; Giuliani, Alessandro
2012-02-01
The question how the observed discrete character of the phenotype emerges from a continuous genetic distance metrics is the core argument of two contrasted evolutionary theories: punctuated equilibrium (stable evolution scattered with saltations in the phenotype) and phyletic gradualism (smooth and linear evolution of the phenotype). Identifying phenotypic saltation on the molecular levels is critical to support the first model of evolution. We have used DNA sequences of ∼1300 genes from 6 isolated populations of the budding yeast Saccharomyces cerevisiae. We demonstrate that while the equivalent measure of the genetic distance show a continuum between lineage distance with no evidence of discrete states, the phenotypic space illustrates only two (discrete) possible states that can be associated with a saltation of the species phenotype. The fact that such saltation spans large fraction of the genome and follows by continuous genetic distance is a proof of the concept that the genotype-phenotype relation is not univocal and may have severe implication when looking for disease related genes and mutations. We used this finding with analogy to attractor-like dynamics and show that punctuated equilibrium could be explained in the framework of non-linear dynamics systems.
van der Maas, H.L.J.; Newell, K.; Molenaar, P.C.M.
1998-01-01
Cognitive developmental psychology is faced with new developments in the mathematical theory of nonlinear dynamic systems and in psychometrics. This chapter addresses: the relation between the strategy concept in cognitive developmental psychology and the concept of attractor in nonlinear dynamic
Random Attractors for the Stochastic Navier-Stokes Equations on the 2D Unit Sphere
Brzeźniak, Z.; Goldys, B.; Le Gia, Q. T.
2018-03-01
In this paper we prove the existence of random attractors for the Navier-Stokes equations on 2 dimensional sphere under random forcing irregular in space and time. We also deduce the existence of an invariant measure.
Directory of Open Access Journals (Sweden)
Qiang Lai
2017-12-01
Full Text Available This paper reports about a novel three-dimensional chaotic system with three nonlinearities. The system has one stable equilibrium, two stable equilibria and one saddle node, two saddle foci and one saddle node for different parameters. One salient feature of this novel system is its multiple attractors caused by different initial values. With the change of parameters, the system experiences mono-stability, bi-stability, mono-periodicity, bi-periodicity, one strange attractor, and two coexisting strange attractors. The complex dynamic behaviors of the system are revealed by analyzing the corresponding equilibria and using the numerical simulation method. In addition, an electronic circuit is given for implementing the chaotic attractors of the system. Using the new chaotic system, an S-Box is developed for cryptographic operations. Moreover, we test the performance of this produced S-Box and compare it to the existing S-Box studies.
Hidden Attractors in a Model of a Bubble Contrast Agent Oscillating Near an Elastic Wall
Garashchuk, Ivan; Sinelshchikov, Dmitry; Kudryashov, Nikolay
2018-02-01
A model describing the dynamics of a spherical gas bubble in a compressible viscous liquid is studied. The bubble is oscillating close to an elastic wall of finite thickness under the influence of an external pressure field which simulates a contrast agent oscillating close to a blood vessel wall. Here we investigate numerically the coexistence of chaotic and periodic attractors in this model. One of the tools applied for seeking coexisting attractors is the perpetual points method. This method can be helpful for localizing coexisting attractors, occurring in various physically realistic ranges of variation of the control parameters. We provide some examples of coexisting attractors to demonstrate the importance of the multistability problem for the applications.
Cancer as quasi-attractor in the gene expression phase space
Giuliani, A.
2017-09-01
It takes no more than 250 tissue types to build up a metazoan, and each tissue has a specific and largely invariant gene expression signature. This implies the `viable configurations' correspondent to a given activated/inactivated expression pattern over the entire genome are very few. This points to the presence of few `low energy deep valleys' correspondent to the allowed states of the system and is a direct consequence of the fact genes do not work by alone but embedded into genetic expression networks. Statistical thermodynamics formalism focusing on the changes in the degree of correlation of the studied systems allows to detect transition behavior in gene expression phase space resembling the phase transition of physical-chemistry studies. In this realm cancer can be intended as a sort of `parasite' sub-attractor of the corresponding healthy tissue that, in the case of disease, is `kinetically entrapped' into a sub-optimal solution. The consequences of such a state of affair for cancer therapies are potentially huge.
Study of the attractor structure of an agent-based sociological model
Energy Technology Data Exchange (ETDEWEB)
Timpanaro, Andre M; Prado, Carmen P C, E-mail: timpa@if.usp.br, E-mail: prado@if.usp.br [Instituto de Fisica da Universidade de Sao Paulo, Sao Paulo (Brazil)
2011-03-01
The Sznajd model is a sociophysics model that is based in the Potts model, and used for describing opinion propagation in a society. It employs an agent-based approach and interaction rules favouring pairs of agreeing agents. It has been successfully employed in modeling some properties and scale features of both proportional and majority elections (see for instance the works of A. T. Bernardes and R. N. Costa Filho), but its stationary states are always consensus states. In order to explain more complicated behaviours, we have modified the bounded confidence idea (introduced before in other opinion models, like the Deffuant model), with the introduction of prejudices and biases (we called this modification confidence rules), and have adapted it to the discrete Sznajd model. This generalized Sznajd model is able to reproduce almost all of the previous versions of the Sznajd model, by using appropriate choices of parameters. We solved the attractor structure of the resulting model in a mean-field approach and made Monte Carlo simulations in a Barabasi-Albert network. These simulations show great similarities with the mean-field, for the tested cases of 3 and 4 opinions. The dynamical systems approach that we devised allows for a deeper understanding of the potential of the Sznajd model as an opinion propagation model and can be easily extended to other models, like the voter model. Our modification of the bounded confidence rule can also be readily applied to other opinion propagation models.
Structures of twilight patrol in the "Churyumov's Unified network" to ensure continuous monitoring
Churyumov, K. I.; Steklov, A. F.; Vidmachenko, A. P.; Dashkiev, G. N.; Steklov, E. A.; Slipchenko, A. S.; Romaniuk, Ya. O.; Nevodovskyi, P. V.
2016-10-01
calibrating control of facts and traces of all kinds of dangerous invasions. 3. Twilight patrol of "Churyumov Unified Network" and the study of invasions of fragments of cometary nuclei in the Earth's atmosphere. The costs of the study of the comet Churyumov-Gerasimenko 67P and its nuclei, on all mission of Rosetta-Philae, amounted to about EUR 2 billion [6]. Its results have significantly improved our understanding of the physics of cometary phenomena have further exacerbated problems of asteroid and comet hazard. In 2016, astronomers a lot of effort and time allocated for study of the disintegration of cometary nucleus of Ikeya - Murakami (P / 2010 V1) at least 17 of fragments. The authors have created a twilight patrol of "United Network Churyumov" to implement of daytime and twilight observations
Co-existing hidden attractors in a radio-physical oscillator system
DEFF Research Database (Denmark)
Kuznetsov, A. P.; Kuznetsov, S. P.; Mosekilde, Erik
2015-01-01
The term `hidden attractor' relates to a stable periodic, quasiperiodic or chaotic state whose basin of attraction does not overlap with the neighborhood of an unstable equilibrium point. Considering a three-dimensional oscillator system that does not allow for the existence of an equilibrium point...... frequency, describe the bifurcations through which hidden attractors of different type arise and disappear, and illustrate the form of the basins of attraction....
Finite-dimensional global attractors for parabolic nonlinear equations with state-dependent delay
Czech Academy of Sciences Publication Activity Database
Chueshov, I.; Rezunenko, Oleksandr
2015-01-01
Roč. 14, č. 5 (2015), s. 1685-1704 ISSN 1534-0392 R&D Projects: GA ČR GAP103/12/2431 Institutional support: RVO:67985556 Keywords : Parabolic evolution equations * state-dependent delay * global attractor * finite-dimension * exponential attractor Subject RIV: BC - Control Systems Theory Impact factor: 0.926, year: 2015 http://library.utia.cas.cz/separaty/2015/AS/rezunenko-0444705.pdf
Fu, Wei; Cao, Lei; Zhang, Yanming; Huo, Su; Du, JuBao; Zhu, Lin; Song, Weiqun
2017-05-01
Visuospatial neglect (VSN) is devastating and common after stroke, and is thought to involve functional disturbance of the attention network. Non-invasive theta-burst stimulation (TBS) may help restore the normal function of attention network, therefore facilitating recovery from VSN. This study investigated the effects of continuous TBS on resting-state functional connectivity (RSFC) in the attention network, and behavioral performances of patients with VSN after stroke. Twelve patients were randomly assigned to receive 10-day cTBS of the left posterior parietal cortex delivered at 80% (the cTBS group), or 40% (the active control group) of the resting motor threshold. Both groups received daily visual scanning training and motor function treatment. Resting-state functional MRI (fMRI) and behavioral tests including line bisection test and star cancelation test were conducted at baseline and after the treatment. At baseline, the two groups showed comparable results in the resting-state fMRI experiments and behavioral tests. After treatment, the cTBS group showed lower functional connectivity between right temporoparietal junction (TPJ) and right anterior insula, and between right superior temporal sulcus and right anterior insula, as compared with the active control group; both groups showed improvement in the behavioral tests, with the cTBS group showing larger changes from baseline than the active control group. cTBS of the left posterior parietal cortex in patients with VSN may induce changes in inter-regional RSFC in the right ventral attention network. These changes may be associated with improved recovery of behavioral deficits after behavioral training. The TPJ and superior temporal sulcus may play crucial roles in recovery from VSN.
International Nuclear Information System (INIS)
Wang Xianjia; Quan Ji; Liu Weibing
2012-01-01
This paper studies the continuous prisoner's dilemma games (CPDG) on Barabasi-Albert (BA) networks. In the model, each agent on a vertex of the networks makes an investment and interacts with all of his neighboring agents. Making an investment is costly, but which benefits its neighboring agents, where benefit and cost depend on the level of investment made. The payoff of each agent is given by the sum of payoffs it receives in its interactions with all its neighbors. Not only payoff, individual's guilty emotion in the games has also been considered. The negative guilty emotion produced in comparing with its neighbors can reduce the utility of individuals directly. We assume that the reduction amount depends on the individual's degree and a baseline level parameter. The group's cooperative level is characterized by the average investment of the population. Each player makes his investment in the next step based on a convex combination of the investment of his best neighbors in the last step, his best history strategies in the latest steps which number is controlled by a memory length parameter, and a uniformly distributed random number. Simulation results show that this degree-dependent guilt mechanism can promote the evolution of cooperation dramatically comparing with degree-independent guilt or no guilt cases. Imitation, memory, uncertainty coefficients and network structure also play determinant roles in the cooperation level of the population. All our results may shed some new light on studying the evolution of cooperation based on network reciprocity mechanisms. (interdisciplinary physics and related areas of science and technology)
Global attractor and asymptotic dynamics in the Kuramoto model for coupled noisy phase oscillators
International Nuclear Information System (INIS)
Giacomin, Giambattista; Pakdaman, Khashayar; Pellegrin, Xavier
2012-01-01
We study the dynamics of the large N limit of the Kuramoto model of coupled phase oscillators, subject to white noise. We introduce the notion of shadow inertial manifold and we prove their existence for this model, supporting the fact that the long-term dynamics of this model is finite dimensional. Following this, we prove that the global attractor of this model takes one of two forms. When coupling strength is below a critical value, the global attractor is a single equilibrium point corresponding to an incoherent state. Otherwise, when coupling strength is beyond this critical value, the global attractor is a two-dimensional disc composed of radial trajectories connecting a saddle-point equilibrium (the incoherent state) to an invariant closed curve of locally stable equilibria (partially synchronized state). Our analysis hinges, on the one hand, upon sharp existence and uniqueness results and their consequence for the existence of a global attractor, and, on the other hand, on the study of the dynamics in the vicinity of the incoherent and coherent (or synchronized) equilibria. We prove in particular nonlinear stability of each synchronized equilibrium, and normal hyperbolicity of the set of such equilibria. We explore mathematically and numerically several properties of the global attractor, in particular we discuss the limit of this attractor as noise intensity decreases to zero
Counterexamples to regularity of Mañé projections in the theory of attractors
International Nuclear Information System (INIS)
Eden, Al'p; Zelik, Sergey V; Kalantarov, Varga K
2013-01-01
This paper is a study of global attractors of abstract semilinear parabolic equations and their embeddings in finite-dimensional manifolds. As is well known, a sufficient condition for the existence of smooth (at least C 1 -smooth) finite-dimensional inertial manifolds containing a global attractor is the so-called spectral gap condition for the corresponding linear operator. There are also a number of examples showing that if there is no gap in the spectrum, then a C 1 -smooth inertial manifold may not exist. On the other hand, since an attractor usually has finite fractal dimension, by Mañé's theorem it projects bijectively and Hölder-homeomorphically into a finite-dimensional generic plane if its dimension is large enough. It is shown here that if there are no gaps in the spectrum, then there exist attractors that cannot be embedded in any Lipschitz or even log-Lipschitz finite-dimensional manifold. Thus, if there are no gaps in the spectrum, then in the general case the inverse Mañé projection of the attractor cannot be expected to be Lipschitz or log-Lipschitz. Furthermore, examples of attractors with finite Hausdorff and infinite fractal dimension are constructed in the class of non-linearities of finite smoothness. Bibliography: 35 titles.
International Nuclear Information System (INIS)
Negarestani, A.; Namvaran, M.; Hashemi, S.M.; Shahpasandzadeh, M.; Fatemi, S.J.; Alavi, S.A.; Mokhtari, M.
2014-01-01
Earthquakes usually occur after some preliminary anomalies in the physical and chemical characteristics of environment and earth interior. Construction of the models which can explain these anomalies, prompt scientists to monitor geophysical and geochemical characteristics in the seismic areas for earthquake prediction. A review of studies has been done so far, denoted that radon gas shows more sensitivity than other geo-gas as a precursor. Based on previous researches, radon is a short-term precursor of earthquake from time point of view. There are equal experimental equations about the relation between earthquake magnitude and its effective distance on radon concentration variations. In this work, an algorithm based on Dobrovolsky equation (D=10 0.43M ) with defining the Expectation and Investigation circles for great Tehran has been used. Radon concentration was measured with RAD7 detector in the more than 40 springs. Concentration of radon in spring, spring discharge, water temperature and the closeness of spring location to active faults, have been considered as the significant factors to select the best spring for a radon continuous monitoring site implementation. According to these factors, thirteen springs have been selected as follow: Bayjan, Mahallat-Hotel, Avaj, Aala, Larijan, Delir, Lavij, Ramsar, Semnan, Lavieh, Legahi, Kooteh-Koomeh and Sarein. (author)
Altamirano-Bustamante, Myriam M; Altamirano-Bustamante, Nelly F; Lifshitz, Alberto; Mora-Magaña, Ignacio; de Hoyos, Adalberto; Avila-Osorio, María Teresa; Quintana-Vargas, Silvia; Aguirre, Jorge A; Méndez, Jorge; Murata, Chiharu; Nava-Diosdado, Rodrigo; Martínez-González, Oscar; Calleja, Elisa; Vargas, Raúl; Mejía-Arangure, Juan Manuel; Cortez-Domínguez, Araceli; Vedrenne-Gutiérrez, Fernand; Sueiras, Perla; Garduño, Juan; Islas-Andrade, Sergio; Salamanca, Fabio; Kumate-Rodríguez, Jesús; Reyes-Fuentes, Alejandro
2013-02-15
In recent years, medical practice has followed two different paradigms: evidence-based medicine (EBM) and values-based medicine (VBM). There is an urgent need to promote medical education that strengthens the relationship between these two paradigms. This work is designed to establish the foundations for a continuing medical education (CME) program aimed at encouraging the dialogue between EBM and VBM by determining the values relevant to everyday medical activities. A quasi-experimental, observational, comparative, prospective and qualitative study was conducted by analyzing through a concurrent triangulation strategy the correlation between healthcare personnel-patient relationship, healthcare personnel's life history, and ethical judgments regarding dilemmas that arise in daily clinical practice.In 2009, healthcare personnel working in Mexico were invited to participate in a free, online clinical ethics course. Each participant responded to a set of online survey instruments before and after the CME program. Face-to-face semi-structured interviews were conducted with healthcare personnel, focusing on their views and representations of clinical practice. The healthcare personnel's core values were honesty and respect. There were significant differences in the clinical practice axiology before and after the course (P ethical discernment, the CME program had an impact on autonomy (P ≤0.0001). Utilitarian autonomy was reinforced in the participants (P ≤0.0001). Regarding work values, significant differences due to the CME intervention were found in openness to change (OC) (P ethical discernment and healthcare personnel-patient relation were beneficence, respect and compassion, respectively. The healthcare personnel participating in a CME intervention in clinical ethics improved high-order values: Openness to change (OC) and Self Transcendence (ST), which are essential to fulfilling the healing ends of medicine. The CME intervention strengthened the role of
Diffusion of intrinsic localized modes by attractor hopping
International Nuclear Information System (INIS)
Meister, Matthias; Vazquez, Luis
2003-01-01
Propagating intrinsic localized modes exist in the damped-driven discrete sine-Gordon chain as attractors of the dynamics. The equations of motion of the system are augmented with Gaussian white noise in order to model the effects of temperature on the system. The noise induces random transitions between attracting configurations corresponding to opposite signs of the propagation velocity of the mode, which leads to a diffusive motion of the excitation. The Heun method is used to numerically generate the stochastic time-evolution of the configuration. We also present a theoretical model for the diffusion which contains two parameters, a transition probability θ and a delay time τ A . The mean value and the variance of the position of the intrinsic localized mode, obtained from simulations, can be fitted well with the predictions of our model, θ and τ A being used as parameters in the fit. After a transition period following the switching on of the noise, the variance shows a linear behaviour as a function of time and the mean value remains constant. An increase in the strength of the noise lowers the variance, leads to an increase in θ, a decrease in τ A and reduces the average distance a mode travels during the transition period
Octodon Degus: A Strong Attractor for Alzheimer Research
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Rafael Castro-Fuentes
2013-01-01
Full Text Available The most popular animal models of Alzheimer’s disease (AD are transgenic mice expressing human genes with known mutations which do not represent the most abundant sporadic form of the disease. An increasing number of genetic, vascular and psychosocial data strongly support that the Octodon degus, a moderate-sized and diurnal precocial rodent, provides a naturalistic model for the study of the early neurodegenerative process associated with sporadic AD. In this minireview we describe and analyze the risk factors that contribute to Alzheimer-like characteristics in the degus, following recent publications, and establish some guidelines for future studies in this model of natural aging associated with the disease. Given the heterogeneity of current data derived from the diverse transgenic animal models of AD, now may be the time for the degus to become a strong attractor for academic research labs and companies involved with AD. This may help to understand the mechanisms responsible for the early neurodegenerative process associated with this devastating disease.
Octodon Degus: A Strong Attractor for Alzheimer Research
Directory of Open Access Journals (Sweden)
Rafael Castro-Fuentes
2013-02-01
Full Text Available The most popular animal models of Alzheimer’s disease (AD are transgenic mice expressing human genes with known mutations which do not represent the most abundant sporadic form of the disease. An increasing number of genetic, vascular and psychosocial data strongly support that the Octodon degus, a moderate-sized and diurnal precocial rodent, provides a naturalistic model for the study of the early neurodegenerative process associated with sporadic AD. In this minireview we describe and analyze the risk factors that contribute to Alzheimer-like characteristics in the degus, following recent publications, and establish some guidelines for future studies in this model of natural aging associated with the disease. Given the heterogeneity of current data derived from the diverse transgenic animal models of AD, now may be the time for the degus to become a strong attractor for academic research labs and companies involved with AD. This may help to understand the mechanisms responsible for the early neurodegenerative process associated with this devastating disease.
Minimality of invariant laminations for partially hyperbolic attractors
International Nuclear Information System (INIS)
Nobili, Felipe
2015-01-01
Let f : M → M be a C 1 -diffeomorphism over a compact boundaryless Riemannian manifold M, and Λ a compact f-invariant subset of M admitting a partially hyperbolic spliting T f Λ = E s ⊕ E c ⊕ E u over the tangent bundle T f Λ. It's known from the Hirsch–Pugh–Shub theory that Λ admits two invariant laminations associated to the extremal bundles E s and E u . These laminations are families of dynamically defined immersed submanifolds of the M tangent, respectively, to the bundles E s and E u at every point in Λ. In this work, we prove that at least one of the invariant laminations of a transitive partially hyperbolic attractor with a one-dimensional center bundle is minimal: the orbit of every leaf intersects Λ densely. This result extends those in Bonatti et al (2002 J. Inst. Math. Jussieu 1 513–41) and Hertz et al (2007 Fields Institute Communications vol 51 (Providence, RI: American Mathematical Society) pp 103–9) about minimal foliations for robustly transitive diffeomorphisms. (paper)
Structural alphabets derived from attractors in conformational space
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Kleinjung Jens
2010-02-01
Full Text Available Abstract Background The hierarchical and partially redundant nature of protein structures justifies the definition of frequently occurring conformations of short fragments as 'states'. Collections of selected representatives for these states define Structural Alphabets, describing the most typical local conformations within protein structures. These alphabets form a bridge between the string-oriented methods of sequence analysis and the coordinate-oriented methods of protein structure analysis. Results A Structural Alphabet has been derived by clustering all four-residue fragments of a high-resolution subset of the protein data bank and extracting the high-density states as representative conformational states. Each fragment is uniquely defined by a set of three independent angles corresponding to its degrees of freedom, capturing in simple and intuitive terms the properties of the conformational space. The fragments of the Structural Alphabet are equivalent to the conformational attractors and therefore yield a most informative encoding of proteins. Proteins can be reconstructed within the experimental uncertainty in structure determination and ensembles of structures can be encoded with accuracy and robustness. Conclusions The density-based Structural Alphabet provides a novel tool to describe local conformations and it is specifically suitable for application in studies of protein dynamics.
Resurgence and hydrodynamic attractors in Gauss-Bonnet holography
Casalderrey-Solana, Jorge; Gushterov, Nikola I.; Meiring, Ben
2018-04-01
We study the convergence of the hydrodynamic series in the gravity dual of Gauss-Bonnet gravity in five dimensions with negative cosmological constant via holography. By imposing boost invariance symmetry, we find a solution to the Gauss-Bonnet equation of motion in inverse powers of the proper time, from which we can extract high order corrections to Bjorken flow for different values of the Gauss-Bonnet parameter λGB. As in all other known examples the gradient expansion is, at most, an asymptotic series which can be understood through applying the techniques of Borel-Padé summation. As expected from the behaviour of the quasi-normal modes in the theory, we observe that the singularities in the Borel plane of this series show qualitative features that interpolate between the infinitely strong coupling limit of N=4 Super Yang Mills theory and the expectation from kinetic theory. We further perform the Borel resummation to constrain the behaviour of hydrodynamic attractors beyond leading order in the hydrodynamic expansion. We find that for all values of λGB considered, the convergence of different initial conditions to the resummation and its hydrodynamization occur at large and comparable values of the pressure anisotropy.
Diffusion of intrinsic localized modes by attractor hopping
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Meister, Matthias [Dpto FIsica de la Materia Condensada, Facultad de Ciencias, Universidad de Zaragoza, 50009 Zaragoza (Spain); Instituto de Biocomputacion y FIsica de Sistemas Complejos, Universidad de Zaragoza, 50009 Zaragoza (Spain); Vazquez, Luis [Dpto Matematica Aplicada, Facultad de Informatica, Universidad Complutense de Madrid, 28040 Madrid (Spain); Centro de AstrobiologIa (CSIC-INTA), 28850 Torrejon de Ardoz (Spain)
2003-11-28
Propagating intrinsic localized modes exist in the damped-driven discrete sine-Gordon chain as attractors of the dynamics. The equations of motion of the system are augmented with Gaussian white noise in order to model the effects of temperature on the system. The noise induces random transitions between attracting configurations corresponding to opposite signs of the propagation velocity of the mode, which leads to a diffusive motion of the excitation. The Heun method is used to numerically generate the stochastic time-evolution of the configuration. We also present a theoretical model for the diffusion which contains two parameters, a transition probability {theta} and a delay time {tau}{sub A}. The mean value and the variance of the position of the intrinsic localized mode, obtained from simulations, can be fitted well with the predictions of our model, {theta} and {tau}{sub A} being used as parameters in the fit. After a transition period following the switching on of the noise, the variance shows a linear behaviour as a function of time and the mean value remains constant. An increase in the strength of the noise lowers the variance, leads to an increase in {theta}, a decrease in {tau}{sub A} and reduces the average distance a mode travels during the transition period.
Directory of Open Access Journals (Sweden)
Mindaugas Snipas
2015-01-01
Full Text Available The primary goal of this work was to study advantages of numerical methods used for the creation of continuous time Markov chain models (CTMC of voltage gating of gap junction (GJ channels composed of connexin protein. This task was accomplished by describing gating of GJs using the formalism of the stochastic automata networks (SANs, which allowed for very efficient building and storing of infinitesimal generator of the CTMC that allowed to produce matrices of the models containing a distinct block structure. All of that allowed us to develop efficient numerical methods for a steady-state solution of CTMC models. This allowed us to accelerate CPU time, which is necessary to solve CTMC models, ∼20 times.
Pranevicius, Henrikas; Pranevicius, Mindaugas; Pranevicius, Osvaldas; Bukauskas, Feliksas F.
2015-01-01
The primary goal of this work was to study advantages of numerical methods used for the creation of continuous time Markov chain models (CTMC) of voltage gating of gap junction (GJ) channels composed of connexin protein. This task was accomplished by describing gating of GJs using the formalism of the stochastic automata networks (SANs), which allowed for very efficient building and storing of infinitesimal generator of the CTMC that allowed to produce matrices of the models containing a distinct block structure. All of that allowed us to develop efficient numerical methods for a steady-state solution of CTMC models. This allowed us to accelerate CPU time, which is necessary to solve CTMC models, ∼20 times. PMID:25705700
Vanacore, E. A.; Baez-Sanchez, G.; Huerfano, V.; Lopez, A. M.; Lugo, J.
2017-12-01
The Puerto Rico Seismic Network (PRSN) is an integral part of earthquake and tsunami monitoring in Puerto Rico and the Virgin Islands. The PRSN conducts scientific research as part of the University of Puerto Rico Mayaguez, conducts the earthquake monitoring for the region, runs extensive earthquake and tsunami education and outreach programs, and acts as a Tsunami Warning Focal Point Alternate for Puerto Rico. During and in the immediate aftermath of Hurricane Maria, the PRSN duties and responsibilities evolved from a seismic network to a major information and communications center for the western side of Puerto Rico. Hurricane Maria effectively destroyed most communications on island, critically between the eastern side of the island where Puerto Rico's Emergency Management's (PREMA) main office and the National Weather Service (NWS) is based and the western side of the island. Additionally, many local emergency management agencies on the western side of the island lost a satellite based emergency management information system called EMWIN which provides critical tsunami and weather information. PRSN's EMWIN system remained functional and consequently via this system and radio communications PRSN became the only information source for NWS warnings and bulletins, tsunami alerts, and earthquake information for western Puerto Rico. Additionally, given the functional radio and geographic location of the PRSN, the network became a critical communications relay for local emergency management. Here we will present the PRSN response in relation to Hurricane Maria including the activation of the PRSN devolution plan, adoption of duties, experiences and lessons learned for continuity of operations and adoption of responsibilities during future catastrophic events.
Bartés-Serrallonga, M; Adan, A; Solé-Casals, J; Caldú, X; Falcón, C; Pérez-Pàmies, M; Bargalló, N; Serra-Grabulosa, J M
2014-04-01
One of the most used paradigms in the study of attention is the Continuous Performance Test (CPT). The identical pairs version (CPT-IP) has been widely used to evaluate attention deficits in developmental, neurological and psychiatric disorders. However, the specific locations and the relative distribution of brain activation in networks identified with functional imaging, varies significantly with differences in task design. To design a task to evaluate sustained attention using functional magnetic resonance imaging (fMRI), and thus to provide data for research concerned with the role of these functions. Forty right-handed, healthy students (50% women; age range: 18-25 years) were recruited. A CPT-IP implemented as a block design was used to assess sustained attention during the fMRI session. The behavioural results from the CPT-IP task showed a good performance in all subjects, higher than 80% of hits. fMRI results showed that the used CPT-IP task activates a network of frontal, parietal and occipital areas, and that these are related to executive and attentional functions. In relation to the use of the CPT to study of attention and working memory, this task provides normative data in healthy adults, and it could be useful to evaluate disorders which have attentional and working memory deficits.
Directory of Open Access Journals (Sweden)
Chiara eMastropasqua
2014-08-01
Full Text Available We combined continuous theta burst stimulation (cTBS and resting state (RS -fMRI approaches to investigate changes in functional connectivity (FC induced by right dorso-lateral prefrontal cortex (DLPFC cTBS at rest in a group of healthy subjects. Seed based fMRI analysis revealed a specific pattern of correlation between the right prefrontal cortex and several brain regions: based on these results, we defined a 29-node network to assess changes in each network connection before and after, respectively, DLPFC-cTBS and sham sessions. A decrease of correlation between the right prefrontal cortex and right parietal cortex (Brodmann areas 46 and 40 respectively was detected after cTBS, while no significant result was found when analyzing sham-session data. To our knowledge, this is the first study that demonstrates within-subject changes in FC induced by cTBS applied on prefrontal area. The possibility to induce selective changes in a specific region without interfering with functionally correlated area could have several implications for the study of functional properties of the brain, and for the emerging therapeutic strategies based on transcranial stimulation.
Sicard, Pierre; Martin-lauzer, François-regis
2017-04-01
In the context of global climate change and adjustment/resilience policies' design and implementation, there is a need not only i. for environmental monitoring, e.g. through a range of Earth Observations (EO) land "products" but ii. for a precise assessment of uncertainties of the aforesaid information that feed environmental decision-making (to be introduced in the EO metadata) and also iii. for a perfect handing of the thresholds which help translate "environment tolerance limits" to match detected EO changes through ecosystem modelling. Uncertainties' insight means precision and accuracy's knowledge and subsequent ability of setting thresholds for change detection systems. Traditionally, the validation of satellite-derived products has taken the form of intensive field campaigns to sanction the introduction of data processors in Payload Data Ground Segments chains. It is marred by logistical challenges and cost issues, reason why it is complemented by specific surveys at ground-based monitoring sites which can provide near-continuous observations at a high temporal resolution (e.g. RadCalNet). Unfortunately, most of the ground-level monitoring sites, in the number of 100th or 1000th, which are part of wider observation networks (e.g. FLUXNET, NEON, IMAGINES) mainly monitor the state of the atmosphere and the radiation exchange at the surface, which are different to the products derived from EO data. In addition they are "point-based" compared to the EO cover to be obtained from Sentinel-2 or Sentinel-3. Yet, data from these networks, processed by spatial extrapolation models, are well-suited to the bottom-up approach and relevant to the validation of vegetation parameters' consistency (e.g. leaf area index, fraction of absorbed photosynthetically active radiation). Consistency means minimal errors on spatial and temporal gradients of EO products. Test of the procedure for land-cover products' consistency assessment with field measurements delivered by worldwide
Directory of Open Access Journals (Sweden)
Takashi Kanamaru
Full Text Available Corticopetal acetylcholine (ACh is released transiently from the nucleus basalis of Meynert (NBM into the cortical layers and is associated with top-down attention. Recent experimental data suggest that this release of ACh disinhibits layer 2/3 pyramidal neurons (PYRs via muscarinic presynaptic effects on inhibitory synapses. Together with other possible presynaptic cholinergic effects on excitatory synapses, this may result in dynamic and temporal modifications of synapses associated with top-down attention. However, the system-level consequences and cognitive relevance of such disinhibitions are poorly understood. Herein, we propose a theoretical possibility that such transient modifications of connectivity associated with ACh release, in addition to top-down glutamatergic input, may provide a neural mechanism for the temporal reactivation of attractors as neural correlates of memories. With baseline levels of ACh, the brain returns to quasi-attractor states, exhibiting transitive dynamics between several intrinsic internal states. This suggests that top-down attention may cause the attention-induced deformations between two types of attractor landscapes: the quasi-attractor landscape (Q-landscape, present under low-ACh, non-attentional conditions and the attractor landscape (A-landscape, present under high-ACh, top-down attentional conditions. We present a conceptual computational model based on experimental knowledge of the structure of PYRs and interneurons (INs in cortical layers 1 and 2/3 and discuss the possible physiological implications of our results.
How additive noise generates a phantom attractor in a model with cubic nonlinearity
Energy Technology Data Exchange (ETDEWEB)
Bashkirtseva, Irina; Ryashko, Lev, E-mail: lev.ryashko@urfu.ru
2016-10-07
Two-dimensional nonlinear system forced by the additive noise is studied. We show that an increasing noise shifts random states and localizes them in a zone far from deterministic attractors. This phenomenon of the generation of the new “phantom” attractor is investigated on the base of probability density functions, mean values and variances of random states. We show that increasing noise results in the qualitative changes of the form of pdf, sharp shifts of mean values, and spikes of the variance. To clarify this phenomenon mathematically, we use the fast–slow decomposition and averaging over the fast variable. For the dynamics of the mean value of the slow variable, a deterministic equation is derived. It is shown that equilibria and the saddle-node bifurcation point of this deterministic equation well describe the stochastic phenomenon of “phantom” attractor in the initial two-dimensional stochastic system. - Highlights: • Two-dimensional nonlinear system with cubic nonlinearity is studied. • Additive noise generates a new phantom attractor. • By averaging over the fast variable one-dimensional equation is derived. • Phantom attractor appearance is analyzed by bifurcation analysis of this equation.
Far-from-equilibrium attractors and nonlinear dynamical systems approach to the Gubser flow
Behtash, Alireza; Cruz-Camacho, C. N.; Martinez, M.
2018-02-01
The nonequilibrium attractors of systems undergoing Gubser flow within relativistic kinetic theory are studied. In doing so we employ well-established methods of nonlinear dynamical systems which rely on finding the fixed points, investigating the structure of the flow diagrams of the evolution equations, and characterizing the basin of attraction using a Lyapunov function near the stable fixed points. We obtain the attractors of anisotropic hydrodynamics, Israel-Stewart (IS) and transient fluid (DNMR) theories and show that they are indeed nonplanar and the basin of attraction is essentially three dimensional. The attractors of each hydrodynamical model are compared with the one obtained from the exact Gubser solution of the Boltzmann equation within the relaxation time approximation. We observe that the anisotropic hydrodynamics is able to match up to high numerical accuracy the attractor of the exact solution while the second-order hydrodynamical theories fail to describe it. We show that the IS and DNMR asymptotic series expansions diverge and use resurgence techniques to perform the resummation of these divergences. We also comment on a possible link between the manifold of steepest descent paths in path integrals and the basin of attraction for the attractors via Lyapunov functions that opens a new horizon toward an effective field theory description of hydrodynamics. Our findings indicate that the reorganization of the expansion series carried out by anisotropic hydrodynamics resums the Knudsen and inverse Reynolds numbers to all orders and thus, it can be understood as an effective theory for the far-from-equilibrium fluid dynamics.
Generation of multi-wing chaotic attractor in fractional order system
International Nuclear Information System (INIS)
Zhang Chaoxia; Yu Simin
2011-01-01
Highlights: → We investigate a novel approach for generating multi-wing chaotic attractors. → We introduce a fundamental fractional differential nominal linear system. → A proper nonlinear state feedback controller is designed. → The controlled system can generate fractional-order multi-wing chaotic attractors. - Abstract: In this paper, a novel approach is proposed for generating multi-wing chaotic attractors from the fractional linear differential system via nonlinear state feedback controller equipped with a duality-symmetric multi-segment quadratic function. The main idea is to design a proper nonlinear state feedback controller by using four construction criterions from a fundamental fractional differential nominal linear system, so that the controlled fractional differential system can generate multi-wing chaotic attractors. It is the first time in the literature to report the multi-wing chaotic attractors from an uncoupled fractional differential system. Furthermore, some basic dynamical analysis and numerical simulations are also given, confirming the effectiveness of the proposed method.
Kalauzi, Aleksandar; Vuckovic, Aleksandra; Bojić, Tijana
2015-03-01
Organization of resting state cortical networks is of fundamental importance for the phenomenon of awareness, which is altered in the first part of hypnagogic period (Hori stages 1-4). Our aim was to investigate the change in brain topography pattern of EEG alpha attractor correlation dimension (CD) in the period of transition from Hori stage 1 to 4. EEG of ten healthy adult individuals was recorded in the wake and drowsy states, using a 14 channel average reference montage, from which 91 bipolar channels were derived and filtered in the wider alpha (6-14 Hz) range. Sixty 1s long epochs of each state and individual were subjected to CD calculation according to the Grassberger-Procaccia method. For such a collection of signals, two embedding dimensions, d={5, 10}, and 22 time delays τ=2-23 samples were explored. Optimal values were d=10 and τ=18, where both saturation and second zero crossing of the autocorrelation function occurred. Bipolar channel CD underwent a significant decrease during the transition and showed a positive linear correlation with electrode distance, stronger in the wake individuals. Topographic distribution of bipolar channels with above median CD changed from longitudinal anterior-posterior pattern (awake) to a more diagonal pattern, with localization in posterior regions (drowsiness). Our data are in line with the literature reporting functional segregation of neuronal assemblies in anterior and posterior regions during this transition. Our results should contribute to understanding of complex reorganization of the cortical part of alpha generators during the wake/drowsy transition. Copyright © 2014 Elsevier B.V. All rights reserved.
The Existence of Weak D-Pullback Exponential Attractor for Nonautonomous Dynamical System
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Yongjun Li
2016-01-01
Full Text Available First, for a process U(t,τ∣t≥τ, we introduce a new concept, called the weak D-pullback exponential attractor, which is a family of sets M(t∣t≤T, for any T∈R, satisfying the following: (i M(t is compact, (ii M(t is positively invariant, that is, U(t,τM(τ⊂M(t, and (iii there exist k,l>0 such that dist(U(t,τB(τ,M(t≤ke-(t-τ; that is, M(t pullback exponential attracts B(τ. Then we give a method to obtain the existence of weak D-pullback exponential attractors for a process. As an application, we obtain the existence of weak D-pullback exponential attractor for reaction diffusion equation in H01 with exponential growth of the external force.
Architecture of chaotic attractors for flows in the absence of any singular point
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Letellier, Christophe [CORIA-UMR 6614 Normandie Université, CNRS-Université et INSA de Rouen, Campus Universitaire du Madrillet, F-76800 Saint-Etienne du Rouvray (France); Malasoma, Jean-Marc [Université de Lyon, ENTPE, Laboratoire Génie Civil et Bâtiment, 3 Rue Maurice Audin, F-69518 Vaulx-en-Velin Cedex (France)
2016-06-15
Some chaotic attractors produced by three-dimensional dynamical systems without any singular point have now been identified, but explaining how they are structured in the state space remains an open question. We here want to explain—in the particular case of the Wei system—such a structure, using one-dimensional sets obtained by vanishing two of the three derivatives of the flow. The neighborhoods of these sets are made of points which are characterized by the eigenvalues of a 2 × 2 matrix describing the stability of flow in a subspace transverse to it. We will show that the attractor is spiralling and twisted in the neighborhood of one-dimensional sets where points are characterized by a pair of complex conjugated eigenvalues. We then show that such one-dimensional sets are also useful in explaining the structure of attractors produced by systems with singular points, by considering the case of the Lorenz system.
Finite-dimensional attractor for a composite system of wave/plate equations with localized damping
International Nuclear Information System (INIS)
Bucci, Francesca; Toundykov, Daniel
2010-01-01
The long-term behaviour of solutions to a model for acoustic–structure interactions is addressed; the system consists of coupled semilinear wave (3D) and plate equations with nonlinear damping and critical sources. The questions of interest are the existence of a global attractor for the dynamics generated by this composite system as well as dimensionality and regularity of the attractor. A distinct and challenging feature of the problem is the geometrically restricted dissipation on the wave component of the system. It is shown that the existence of a global attractor of finite fractal dimension—established in a previous work by Bucci et al (2007 Commun. Pure Appl. Anal. 6 113–40) only in the presence of full-interior acoustic damping—holds even in the case of localized dissipation. This nontrivial generalization is inspired by, and consistent with, the recent advances in the study of wave equations with nonlinear localized damping
Controllable V-Shape Multi-Scroll Butterfly Attractor: System and Circuit Implementation
Zidan, Mohammed A.
2012-07-23
In this paper, a new controllable V-shape multiscroll attractor is presented, where a variety of symmetrical and unsymmetrical attractors with a variable number of scrolls can be controlled using new staircase nonlinear function and the parameters of the system. This attractor can be used to generate random signals with a variety of symbol distribution. Digital implementation of the proposed generator is also presented using a Xilinx Virtex® 4 Field Programmable Gate Array and experimental results are provided. The digital realization easily fits into a small area (<1.5% of the total area) and expresses a high throughput (4.3 Gbit/sec per state variable). © 2012 World Scientific Publishing Company.
Controllable V-Shape Multi-Scroll Butterfly Attractor: System and Circuit Implementation
Zidan, Mohammed A.; Radwan, Ahmed G.; Salama, Khaled N.
2012-01-01
In this paper, a new controllable V-shape multiscroll attractor is presented, where a variety of symmetrical and unsymmetrical attractors with a variable number of scrolls can be controlled using new staircase nonlinear function and the parameters of the system. This attractor can be used to generate random signals with a variety of symbol distribution. Digital implementation of the proposed generator is also presented using a Xilinx Virtex® 4 Field Programmable Gate Array and experimental results are provided. The digital realization easily fits into a small area (<1.5% of the total area) and expresses a high throughput (4.3 Gbit/sec per state variable). © 2012 World Scientific Publishing Company.
On the control of the chaotic attractors of the 2-d Navier-Stokes equations.
Smaoui, Nejib; Zribi, Mohamed
2017-03-01
The control problem of the chaotic attractors of the two dimensional (2-d) Navier-Stokes (N-S) equations is addressed in this paper. First, the Fourier Galerkin method based on a reduced-order modelling approach developed by Chen and Price is applied to the 2-d N-S equations to construct a fifth-order system of nonlinear ordinary differential equations (ODEs). The dynamics of the fifth-order system was studied by analyzing the system's attractor for different values of Reynolds number, R e . Then, control laws are proposed to drive the states of the ODE system to a desired attractor. Finally, an adaptive controller is designed to synchronize two reduced order ODE models having different Reynolds numbers and starting from different initial conditions. Simulation results indicate that the proposed control schemes work well.
Affine fractal functions as bases of continuous funtions | Navascues ...
African Journals Online (AJOL)
The objective of the present paper is the study of affine transformations of the plane, which provide self-affine curves as attractors. The properties of these curves depend decisively of the coefficients of the system of affinities involved. The corresponding functions are continuous on a compact interval. If the scale factors are ...
[Extraction and recognition of attractors in three-dimensional Lorenz plot].
Hu, Min; Jang, Chengfan; Wang, Suxia
2018-02-01
Lorenz plot (LP) method which gives a global view of long-time electrocardiogram signals, is an efficient simple visualization tool to analyze cardiac arrhythmias, and the morphologies and positions of the extracted attractors may reveal the underlying mechanisms of the onset and termination of arrhythmias. But automatic diagnosis is still impossible because it is lack of the method of extracting attractors by now. We presented here a methodology of attractor extraction and recognition based upon homogeneously statistical properties of the location parameters of scatter points in three dimensional LP (3DLP), which was constructed by three successive RR intervals as X , Y and Z axis in Cartesian coordinate system. Validation experiments were tested in a group of RR-interval time series and tags data with frequent unifocal premature complexes exported from a 24-hour Holter system. The results showed that this method had excellent effective not only on extraction of attractors, but also on automatic recognition of attractors by the location parameters such as the azimuth of the points peak frequency ( A PF ) of eccentric attractors once stereographic projection of 3DLP along the space diagonal. Besides, A PF was still a powerful index of differential diagnosis of atrial and ventricular extrasystole. Additional experiments proved that this method was also available on several other arrhythmias. Moreover, there were extremely relevant relationships between 3DLP and two dimensional LPs which indicate any conventional achievement of LPs could be implanted into 3DLP. It would have a broad application prospect to integrate this method into conventional long-time electrocardiogram monitoring and analysis system.
Energy Technology Data Exchange (ETDEWEB)
Wang, Yan [MOE Key Laboratory of Fundamental Physical Quantities Measurements, School of Physics, Huazhong University of Science and Technology, 1037 Luoyu Road, Wuhan, Hubei Province 430074 (China); Mohanty, Soumya D.; Jenet, Fredrick A., E-mail: ywang12@hust.edu.cn [Department of Physics, University of Texas Rio Grande Valley, 1 West University Boulevard, Brownsville, TX 78520 (United States)
2015-12-20
Supermassive black hole binaries are one of the primary targets of gravitational wave (GW) searches using pulsar timing arrays (PTAs). GW signals from such systems are well represented by parameterized models, allowing the standard Generalized Likelihood Ratio Test (GLRT) to be used for their detection and estimation. However, there is a dichotomy in how the GLRT can be implemented for PTAs: there are two possible ways in which one can split the set of signal parameters for semi-analytical and numerical extremization. The straightforward extension of the method used for continuous signals in ground-based GW searches, where the so-called pulsar phase parameters are maximized numerically, was addressed in an earlier paper. In this paper, we report the first study of the performance of the second approach where the pulsar phases are maximized semi-analytically. This approach is scalable since the number of parameters left over for numerical optimization does not depend on the size of the PTA. Our results show that for the same array size (9 pulsars), the new method performs somewhat worse in parameter estimation, but not in detection, than the previous method where the pulsar phases were maximized numerically. The origin of the performance discrepancy is likely to be in the ill-posedness that is intrinsic to any network analysis method. However, the scalability of the new method allows the ill-posedness to be mitigated by simply adding more pulsars to the array. This is shown explicitly by taking a larger array of pulsars.
Directory of Open Access Journals (Sweden)
YuKang Jia
2017-01-01
Full Text Available Long Short-Term Memory (LSTM is a kind of Recurrent Neural Networks (RNN relating to time series, which has achieved good performance in speech recogniton and image recognition. Long Short-Term Memory Projection (LSTMP is a variant of LSTM to further optimize speed and performance of LSTM by adding a projection layer. As LSTM and LSTMP have performed well in pattern recognition, in this paper, we combine them with Connectionist Temporal Classification (CTC to study piano’s continuous note recognition for robotics. Based on the Beijing Forestry University music library, we conduct experiments to show recognition rates and numbers of iterations of LSTM with a single layer, LSTMP with a single layer, and Deep LSTM (DLSTM, LSTM with multilayers. As a result, the single layer LSTMP proves performing much better than the single layer LSTM in both time and the recognition rate; that is, LSTMP has fewer parameters and therefore reduces the training time, and, moreover, benefiting from the projection layer, LSTMP has better performance, too. The best recognition rate of LSTMP is 99.8%. As for DLSTM, the recognition rate can reach 100% because of the effectiveness of the deep structure, but compared with the single layer LSTMP, DLSTM needs more training time.
Meng, Tianhui; Li, Xiaofan; Zhang, Sha; Zhao, Yubin
2016-09-28
Wireless sensor networks (WSNs) have recently gained popularity for a wide spectrum of applications. Monitoring tasks can be performed in various environments. This may be beneficial in many scenarios, but it certainly exhibits new challenges in terms of security due to increased data transmission over the wireless channel with potentially unknown threats. Among possible security issues are timing attacks, which are not prevented by traditional cryptographic security. Moreover, the limited energy and memory resources prohibit the use of complex security mechanisms in such systems. Therefore, balancing between security and the associated energy consumption becomes a crucial challenge. This paper proposes a secure scheme for WSNs while maintaining the requirement of the security-performance tradeoff. In order to proceed to a quantitative treatment of this problem, a hybrid continuous-time Markov chain (CTMC) and queueing model are put forward, and the tradeoff analysis of the security and performance attributes is carried out. By extending and transforming this model, the mean time to security attributes failure is evaluated. Through tradeoff analysis, we show that our scheme can enhance the security of WSNs, and the optimal rekeying rate of the performance and security tradeoff can be obtained.
Directory of Open Access Journals (Sweden)
Alberto Pascual-García
2009-03-01
Full Text Available Structural classifications of proteins assume the existence of the fold, which is an intrinsic equivalence class of protein domains. Here, we test in which conditions such an equivalence class is compatible with objective similarity measures. We base our analysis on the transitive property of the equivalence relationship, requiring that similarity of A with B and B with C implies that A and C are also similar. Divergent gene evolution leads us to expect that the transitive property should approximately hold. However, if protein domains are a combination of recurrent short polypeptide fragments, as proposed by several authors, then similarity of partial fragments may violate the transitive property, favouring the continuous view of the protein structure space. We propose a measure to quantify the violations of the transitive property when a clustering algorithm joins elements into clusters, and we find out that such violations present a well defined and detectable cross-over point, from an approximately transitive regime at high structure similarity to a regime with large transitivity violations and large differences in length at low similarity. We argue that protein structure space is discrete and hierarchic classification is justified up to this cross-over point, whereas at lower similarities the structure space is continuous and it should be represented as a network. We have tested the qualitative behaviour of this measure, varying all the choices involved in the automatic classification procedure, i.e., domain decomposition, alignment algorithm, similarity score, and clustering algorithm, and we have found out that this behaviour is quite robust. The final classification depends on the chosen algorithms. We used the values of the clustering coefficient and the transitivity violations to select the optimal choices among those that we tested. Interestingly, this criterion also favours the agreement between automatic and expert classifications
INFN-Laboratori Nazionali di Frascati School on the Attractor Mechanism 2009
4th School on Attractor Mechanism : Supersymmetric Gravity and Black Holes
2013-01-01
This book is based upon lectures presented in the summer of 2009 at the INFN-Laboratori Nazionali di Frascati School on Attractor Mechanism, directed by Stefano Bellucci. The symposium included such prestigious lecturers as S. Ferrara, G. Dall'Agata, J.F. Morales, J. Simón and M. Trigiante. All lectures were given at a pedagogical, introductory level, which is reflected in the specific "flavor" of this volume. The book also benefits from extensive discussions about, and the related reworking of, the various contributions. It is the fifth volume in a series of books on the general topics of supersymmetry, supergravity, black holes and the attractor mechanism.
Rank One Strange Attractors in Periodically Kicked Predator-Prey System with Time-Delay
Yang, Wenjie; Lin, Yiping; Dai, Yunxian; Zhao, Huitao
2016-06-01
This paper is devoted to the study of the problem of rank one strange attractor in a periodically kicked predator-prey system with time-delay. Our discussion is based on the theory of rank one maps formulated by Wang and Young. Firstly, we develop the rank one chaotic theory to delayed systems. It is shown that strange attractors occur when the delayed system undergoes a Hopf bifurcation and encounters an external periodic force. Then we use the theory to the periodically kicked predator-prey system with delay, deriving the conditions for Hopf bifurcation and rank one chaos along with the results of numerical simulations.
Multistability and hidden attractors in a multilevel DC/DC converter
DEFF Research Database (Denmark)
Zhusubaliyev, Zhanybai T.; Mosekilde, Erik
2015-01-01
An attracting periodic, quasiperiodic or chaotic set of a smooth, autonomous system may be referred to as a "hidden attractor" if its basin of attraction does not overlap with the neighborhood of an unstable equilibrium point. Historically, this condition has implied that the basin of attraction...... produce complicated structures of attracting and repelling states organized around the basic switching cycle. This leads us to suggest the existence of hidden attractors in such systems as well. In this case, the condition will be that the basin of attraction does not overlap with the fixed point...
Exponential attractors for a Cahn-Hilliard model in bounded domains with permeable walls
Directory of Open Access Journals (Sweden)
Ciprian G. Gal
2006-11-01
Full Text Available In a previous article [7], we proposed a model of phase separation in a binary mixture confined to a bounded region which may be contained within porous walls. The boundary conditions were derived from a mass conservation law and variational methods. In the present paper, we study the problem further. Using a Faedo-Galerkin method, we obtain the existence and uniqueness of a global solution to our problem, under more general assumptions than those in [7]. We then study its asymptotic behavior and prove the existence of an exponential attractor (and thus of a global attractor with finite dimension.
A New Chaotic Flow with Hidden Attractor: The First Hyperjerk System with No Equilibrium
Ren, Shuili; Panahi, Shirin; Rajagopal, Karthikeyan; Akgul, Akif; Pham, Viet-Thanh; Jafari, Sajad
2018-02-01
Discovering unknown aspects of non-equilibrium systems with hidden strange attractors is an attractive research topic. A novel quadratic hyperjerk system is introduced in this paper. It is noteworthy that this non-equilibrium system can generate hidden chaotic attractors. The essential properties of such systems are investigated by means of equilibrium points, phase portrait, bifurcation diagram, and Lyapunov exponents. In addition, a fractional-order differential equation of this new system is presented. Moreover, an electronic circuit is also designed and implemented to verify the feasibility of the theoretical model.
On the New Scenario of Annihilation of the Cross-Well Chaotic Attractor in a Nonlinear Oscillator
International Nuclear Information System (INIS)
Szemplinska, W.; Zubrzycki, A.; Tyrkiel, E.
1999-01-01
The twin-well potential Duffing oscillator is considered and the investigations are focused on a new scenario of destruction of the cross-well chaotic attractor. The new phenomenon belongs to the category of subduction bifurcation and consists in replacement of the cross-well chaotic attractor by a pair of unsymmetric 2T-periodic attractors. It is shown that the new scenario forms a transition zone in the system control parameter plane, the zone, which separates the two known scenarios of annihilation of the cross-well chaotic attractor: the boundary crisis, and the subduction in which the two single-well T-periodic attractors are born in a saddle-node bifurcation. (author)
Daniel J. Isaak; Russell F. Thurow
2006-01-01
Spatially continuous sampling designs, when temporally replicated, provide analytical flexibility and are unmatched in their ability to provide a dynamic system view. We have compiled such a data set by georeferencing the network-scale distribution of Chinook salmon (Oncorhynchus tshawytscha) redds across a large wilderness basin (7330 km2) in...
Random attractors for stochastic lattice reversible Gray-Scott systems with additive noise
Directory of Open Access Journals (Sweden)
Hongyan Li
2015-10-01
Full Text Available In this article, we prove the existence of a random attractor of the stochastic three-component reversible Gray-Scott system on infinite lattice with additive noise. We use a transformation of addition involved with Ornstein-Uhlenbeck process, for proving the pullback absorbing property and the pullback asymptotic compactness of the reaction diffusion system with cubic nonlinearity.
Decay of Correlations, Quantitative Recurrence and Logarithm Law for Contracting Lorenz Attractors
Galatolo, Stefano; Nisoli, Isaia; Pacifico, Maria Jose
2018-03-01
In this paper we prove that a class of skew products maps with non uniformly hyperbolic base has exponential decay of correlations. We apply this to obtain a logarithm law for the hitting time associated to a contracting Lorenz attractor at all the points having a well defined local dimension, and a quantitative recurrence estimation.
Particle Swarm Optimization Based on Local Attractors of Ordinary Differential Equation System
Directory of Open Access Journals (Sweden)
Wenyu Yang
2014-01-01
Full Text Available Particle swarm optimization (PSO is inspired by sociological behavior. In this paper, we interpret PSO as a finite difference scheme for solving a system of stochastic ordinary differential equations (SODE. In this framework, the position points of the swarm converge to an equilibrium point of the SODE and the local attractors, which are easily defined by the present position points, also converge to the global attractor. Inspired by this observation, we propose a class of modified PSO iteration methods (MPSO based on local attractors of the SODE. The idea of MPSO is to choose the next update state near the present local attractor, rather than the present position point as in the original PSO, according to a given probability density function. In particular, the quantum-behaved particle swarm optimization method turns out to be a special case of MPSO by taking a special probability density function. The MPSO methods with six different probability density functions are tested on a few benchmark problems. These MPSO methods behave differently for different problems. Thus, our framework not only gives an interpretation for the ordinary PSO but also, more importantly, provides a warehouse of PSO-like methods to choose from for solving different practical problems.
New explicit spike solutions-non-local component of the generalized Mixmaster attractor
International Nuclear Information System (INIS)
Lim, Woei Chet
2008-01-01
By applying a standard solution-generating transformation to an arbitrary vacuum Bianchi type II solution, one generates a new solution with spikes commonly observed in numerical simulations. It is conjectured that the spike solutions are part of the generalized Mixmaster attractor
The necessity for a time local dimension in systems with time-varying attractors
DEFF Research Database (Denmark)
Særmark, Knud H; Ashkenazy, Y; Levitan, J
1997-01-01
We show that a simple non-linear system for ordinary differential equations may possess a time-varying attractor dimension. This indicates that it is infeasible to characterize EEG and MEG time series with a single time global dimension. We suggest another measure for the description of non...
Nonlinear attractor dynamics in the fundamental and extended prism adaptation paradigm
International Nuclear Information System (INIS)
Frank, T.D.; Blau, Julia J.C.; Turvey, M.T.
2009-01-01
Adaptation and re-adaptation processes are studied in terms of dynamic attractors that evolve and devolve. In doing so, a theoretical account is given for the fundamental observation that adaptation and re-adaptation processes do not exhibit one-trial learning. Moreover, the emergence of the latent aftereffect in the extended prism paradigm is addressed
Multiple attractors and crisis route to chaos in a model food-chain
International Nuclear Information System (INIS)
Upadhyay, Ranjit Kumar
2003-01-01
An attempt has been made to identify the mechanism, which is responsible for the existence of chaos in narrow parameter range in a realistic ecological model food-chain. Analytical and numerical studies of a three species food-chain model similar to a situation likely to be seen in terrestrial ecosystems has been carried out. The study of the model food chain suggests that the existence of chaos in narrow parameter ranges is caused by the crisis-induced sudden death of chaotic attractors. Varying one of the critical parameters in its range while keeping all the others constant, one can monitor the changes in the dynamical behaviour of the system, thereby fixing the regimes in which the system exhibits chaotic dynamics. The computed bifurcation diagrams and basin boundary calculations indicate that crisis is the underlying factor which generates chaotic dynamics in this model food-chain. We investigate sudden qualitative changes in chaotic dynamical behaviour, which occur at a parameter value a 1 =1.7804 at which the chaotic attractor destroyed by boundary crisis with an unstable periodic orbit created by the saddle-node bifurcation. Multiple attractors with riddled basins and fractal boundaries are also observed. If ecological systems of interacting species do indeed exhibit multiple attractors etc., the long term dynamics of such systems may undergo vast qualitative changes following epidemics or environmental catastrophes due to the system being pushed into the basin of a new attractor by the perturbation. Coupled with stochasticity, such complex behaviours may render such systems practically unpredictable
Interpolating from Bianchi attractors to Lifshitz and AdS spacetimes
International Nuclear Information System (INIS)
Kachru, Shamit; Kundu, Nilay; Saha, Arpan; Samanta, Rickmoy; Trivedi, Sandip P.
2014-01-01
We construct classes of smooth metrics which interpolate from Bianchi attractor geometries of Types II, III, VI and IX in the IR to Lifshitz or AdS 2 ×S 3 geometries in the UV. While we do not obtain these metrics as solutions of Einstein gravity coupled to a simple matter field theory, we show that the matter sector stress-energy required to support these geometries (via the Einstein equations) does satisfy the weak, and therefore also the null, energy condition. Since Lifshitz or AdS 2 ×S 3 geometries can in turn be connected to AdS 5 spacetime, our results show that there is no barrier, at least at the level of the energy conditions, for solutions to arise connecting these Bianchi attractor geometries to AdS 5 spacetime. The asymptotic AdS 5 spacetime has no non-normalizable metric deformation turned on, which suggests that furthermore, the Bianchi attractor geometries can be the IR geometries dual to field theories living in flat space, with the breaking of symmetries being either spontaneous or due to sources for other fields. Finally, we show that for a large class of flows which connect two Bianchi attractors, a C-function can be defined which is monotonically decreasing from the UV to the IR as long as the null energy condition is satisfied. However, except for special examples of Bianchi attractors (including AdS space), this function does not attain a finite and non-vanishing constant value at the end points
Energy Technology Data Exchange (ETDEWEB)
Howell, J.A.; Eccleston, G.W.; Halbig, J.K.; Klosterbuer, S.F. [Los Alamos National Lab., NM (United States); Larson, T.W. [California Polytechnic State Univ., San Luis Obispo, CA (US)
1993-08-01
Automated analysis using pattern recognition and neural network software can help interpret data, call attention to potential anomalies, and improve safeguards effectiveness. Automated software analysis, based on pattern recognition and neural networks, was applied to data collected from a radiation core discharge monitor system located adjacent to an on-load reactor core. Unattended radiation sensors continuously collect data to monitor on-line refueling operations in the reactor. The huge volume of data collected from a number of radiation channels makes it difficult for a safeguards inspector to review it all, check for consistency among the measurement channels, and find anomalies. Pattern recognition and neural network software can analyze large volumes of data from continuous, unattended measurements, thereby improving and automating the detection of anomalies. The authors developed a prototype pattern recognition program that determines the reactor power level and identifies the times when fuel bundles are pushed through the core during on-line refueling. Neural network models were also developed to predict fuel bundle burnup to calculate the region on the on-load reactor face from which fuel bundles were discharged based on the radiation signals. In the preliminary data set, which was limited and consisted of four distinct burnup regions, the neural network model correctly predicted the burnup region with an accuracy of 92%.
Park, Bong-Won; Lee, Kun Chang
Recent surge of social networking websites in the world supports a widely accepted assumption that people aspires to be recognized online by sharing information with others, perceive enjoyment and keeps to use their social networking site continuously. Different from traditional social networking sites (SNSs) like Cyworld and Facebook, Twitter is famous for its short message and ease of sharing knowledge with others in a prompt manner. Therefore, Twitter is preferred most by many people who seem innovative generically. In this sense, Twitter accumulates its fame as the most influential SNS media among users. However, there is no study to investigate why people holds continuous intention to use the Twitter from the perspective of knowledge-sharing and social presence. To resolve this research issue, this paper adopts six constructs such as personal innovativeness, knowledge-sharing intention, perceived ease of use, perceived enjoyment, social presence, and intention to continuously use. Empirical results with 105 valid questionnaires revealed that the proposed research model is statistically significant, and people's intention to use the Twitter continuously is influenced by social presence, perceived enjoyment, and perceived ease of use.
International Nuclear Information System (INIS)
Petkov, V; Le Messurier, D
2010-01-01
The atomic-scale structure of germanium diselenide (GeSe 2 ) glass has been revisited using a combination of high-energy x-ray diffraction and constrained reverse Monte Carlo simulations. The study shows that the glass structure may be very well described in terms of a continuous network of corner- and edge-sharing Ge-Se 4 tetrahedra. The result is in contrast to other recent studies asserting that the chemical order and, hence, network integrity in GeSe 2 glass are intrinsically broken. It is suggested that more elaborate studies are necessary to resolve the controversy.
Replication of chaos in neural networks, economics and physics
Akhmet, Marat
2016-01-01
This book presents detailed descriptions of chaos for continuous-time systems. It is the first-ever book to consider chaos as an input for differential and hybrid equations. Chaotic sets and chaotic functions are used as inputs for systems with attractors: equilibrium points, cycles and tori. The findings strongly suggest that chaos theory can proceed from the theory of differential equations to a higher level than previously thought. The approach selected is conducive to the in-depth analysis of different types of chaos. The appearance of deterministic chaos in neural networks, economics and mechanical systems is discussed theoretically and supported by simulations. As such, the book offers a valuable resource for mathematicians, physicists, engineers and economists studying nonlinear chaotic dynamics.
Fractional Hopfield Neural Networks: Fractional Dynamic Associative Recurrent Neural Networks.
Pu, Yi-Fei; Yi, Zhang; Zhou, Ji-Liu
2017-10-01
This paper mainly discusses a novel conceptual framework: fractional Hopfield neural networks (FHNN). As is commonly known, fractional calculus has been incorporated into artificial neural networks, mainly because of its long-term memory and nonlocality. Some researchers have made interesting attempts at fractional neural networks and gained competitive advantages over integer-order neural networks. Therefore, it is naturally makes one ponder how to generalize the first-order Hopfield neural networks to the fractional-order ones, and how to implement FHNN by means of fractional calculus. We propose to introduce a novel mathematical method: fractional calculus to implement FHNN. First, we implement fractor in the form of an analog circuit. Second, we implement FHNN by utilizing fractor and the fractional steepest descent approach, construct its Lyapunov function, and further analyze its attractors. Third, we perform experiments to analyze the stability and convergence of FHNN, and further discuss its applications to the defense against chip cloning attacks for anticounterfeiting. The main contribution of our work is to propose FHNN in the form of an analog circuit by utilizing a fractor and the fractional steepest descent approach, construct its Lyapunov function, prove its Lyapunov stability, analyze its attractors, and apply FHNN to the defense against chip cloning attacks for anticounterfeiting. A significant advantage of FHNN is that its attractors essentially relate to the neuron's fractional order. FHNN possesses the fractional-order-stability and fractional-order-sensitivity characteristics.
Dynamical networks with topological self-organization
Zak, M.
2001-01-01
Coupled evolution of state and topology of dynamical networks is introduced. Due to the well organized tensor structure, the governing equations are presented in a canonical form, and required attractors as well as their basins can be easily implanted and controlled.
Rinsky-Halivni, Lilah; Lerman, Yehuda
2018-04-01
Despite their legal rights, individuals with disabilities face numerous obstacles to integration in the workplace which can result in their discharge from the labor force. Currently occupational physicians have few resources to help decide whether to integrate disabled workers in pre-placement, or in cases of return-to-work. A network of 13 discussion groups comprised of the occupational physicians of each regional clinic of a large Health Maintenance Organization (HMO) in Israel was created to deal with disability management dilemmas. A moderator compiles and shares the physicians' opinions and experiences with all network members thus assisting the consulting physician in decision-making. Successful management of three representative cases is described to illustrate real-life implementations of this network. The network enables both the consulting and other physicians to tap a large knowledge base and decision-making experience concerning cases of occupational disability management, contributing to professional development and improved service delivery. © 2018 Wiley Periodicals, Inc.
Directory of Open Access Journals (Sweden)
Wen-Xiang Wu
2014-01-01
Full Text Available The cost-based system optimum problem in networks with continuously distributed value of time is formulated as a path-based form, which cannot be solved by the Frank-Wolfe algorithm. In light of magnitude improvement in the availability of computer memory in recent years, path-based algorithms have been regarded as a viable approach for traffic assignment problems with reasonably large network sizes. We develop a path-based gradient projection algorithm for solving the cost-based system optimum model, based on Goldstein-Levitin-Polyak method which has been successfully applied to solve standard user equilibrium and system optimum problems. The Sioux Falls network tested is used to verify the effectiveness of the algorithm.
Pierotti, Lisa; Cioni, Roberto
2010-05-01
Since late 2002, a continuous automatic monitoring network (CAMN) was designed, built and installed in Tuscany (Italy), in order to investigate and define the geochemical response of the aquifers to the local seismic activity. The purpose of the investigation was to identify eventual earthquake precursors. The CAMN is constituted by two groups of five measurement stations each. A first group has been installed in the Serchio and Magra graben (Garfagnana and Lunigiana Valleys, Northern Tuscany), while the second one, in the area of Mt. Amiata (Southern Tuscany), an extinct volcano. Garfagnana, Lunigiana and Mt. Amiata regions belong to the inner zone of the Northern Apennine fold-and-thrust belt. This zone has been involved in the post-collision extensional tectonics since the Upper Miocene-Pliocene. Such tectonic activity has produced horst and graben structures oriented from N-S to NW-SE that are transferred by NE-SW system. Both Garfagnana (Serchio graben) and Lunigiana (Magra graben) belong to the most inner sector of the belt where the seismic sources, responsible for the strongest earthquakes of the northern Apennine, are located (e.g. the M=6.5 earthquake of September 1920). The extensional processes in southern Tuscany have been accompanied by magmatic activity since the Upper Miocene, developing effusive and intrusive products traditionally attributed to the so-called Tuscan Magmatic Province. Mt. Amiata, whose magmatic activity ceased about 0.3 M.y. ago, belongs to the extensive Tyrrhenian sector that is characterized by high heat flow and crustal thinning. The whole zone is characterized by wide-spread but moderate seismicity (the maximum recorded magnitude has been 5.1 with epicentre in Piancastagnaio, 1919). The extensional regime in both the Garfagnana-Lunigiana and Mt. Amiata area is confirmed by the focal mechanisms of recent earthquakes. An essential phase of the monitoring activities has been the selection of suitable sites for the installation of
Laboratory and numerical simulation of internal wave attractors and their instability.
Brouzet, Christophe; Dauxois, Thierry; Ermanyuk, Evgeny; Joubaud, Sylvain; Sibgatullin, Ilias
2015-04-01
Internal wave attractors are formed as result of focusing of internal gravity waves in a confined domain of stably stratified fluid due to peculiarities of reflections properties [1]. The energy injected into domain due to external perturbation, is concentrated along the path formed by the attractor. The existence of attractors was predicted theoretically and proved both experimentally and numerically [1-4]. Dynamics of attractors is greatly influenced by geometrical focusing, viscous dissipation and nonlinearity. The experimental setup features Schmidt number equal to 700 which impose constraints on resolution in numerical schemes. Also for investigation of stability on large time intervals (about 1000 periods of external forcing) numerical viscosity may have significant impact. For these reasons, we have chosen spectral element method for investigation of this problem, what allows to carefully follow the nonlinear dynamics. We present cross-comparison of experimental observations and numerical simulations of long-term behavior of wave attractors. Fourier analysis and subsequent application of Hilbert transform are used for filtering of spatial components of internal-wave field [5]. The observed dynamics shows a complicated coupling between the effects of local instability and global confinement of the fluid domain. The unstable attractor is shown to act as highly efficient mixing box providing the efficient energy pathway from global-scale excitation to small-scale wave motions and mixing. Acknowledgement, IS has been partially supported by Russian Ministry of Education and Science (agreement id RFMEFI60714X0090) and Russian Foundation for Basic Research, grant N 15-01-06363. EVE gratefully acknowledges his appointment as a Marie Curie incoming fellow at Laboratoire de physique ENS de Lyon. This work has been partially supported by the ONLITUR grant (ANR-2011-BS04-006-01) and achieved thanks to the resources of PSMN from ENS de Lyon 1. Maas, L. R. M. & Lam, F
Crisis of the chaotic attractor of a climate model: a transfer operator approach
Tantet, Alexis; Lucarini, Valerio; Lunkeit, Frank; Dijkstra, Henk A.
2018-05-01
The destruction of a chaotic attractor leading to rough changes in the dynamics of a dynamical system is studied. Local bifurcations are known to be characterised by a single or a pair of characteristic exponents crossing the imaginary axis. As a result, the approach of such bifurcations in the presence of noise can be inferred from the slowing down of the decay of correlations (Held and Kleinen 2004 Geophys. Res. Lett. 31 1–4). On the other hand, little is known about global bifurcations involving high-dimensional attractors with several positive Lyapunov exponents. It is known that the global stability of chaotic attractors may be characterised by the spectral properties of the Koopman (Mauroy and Mezić 2016 IEEE Trans. Autom. Control 61 3356–69) or the transfer operators governing the evolution of statistical ensembles. Accordingly, it has recently been shown (Tantet 2017 J. Stat. Phys. 1–33) that a boundary crisis in the Lorenz flow coincides with the approach to the unit circle of the eigenvalues of these operators associated with motions about the attractor, the stable resonances. A second class of resonances, the unstable resonances, are responsible for the decay of correlations and mixing on the attractor. In the deterministic case, these cannot be expected to be affected by general boundary crises. Here, however, we give an example of a chaotic system in which slowing down of the decay of correlations of some observables does occur at the approach of a boundary crisis. The system considered is a high-dimensional, chaotic climate model of physical relevance. Moreover, coarse-grained approximations of the transfer operators on a reduced space, constructed from a long time series of the system, give evidence that this behaviour is due to the approach of unstable resonances to the unit circle. That the unstable resonances are affected by the crisis can be physically understood from the fact that the process responsible for the instability, the ice
Kinetic attractor phase diagrams of active nematic suspensions: the dilute regime.
Forest, M Gregory; Wang, Qi; Zhou, Ruhai
2015-08-28
Large-scale simulations by the authors of the kinetic-hydrodynamic equations for active polar nematics revealed a variety of spatio-temporal attractors, including steady and unsteady, banded (1d) and cellular (2d) spatial patterns. These particle scale activation-induced attractors arise at dilute nanorod volume fractions where the passive equilibrium phase is isotropic, whereas all previous model simulations have focused on the semi-dilute, nematic equilibrium regime and mostly on low-moment orientation tensor and polarity vector models. Here we extend our previous results to complete attractor phase diagrams for active nematics, with and without an explicit polar potential, to map out novel spatial and dynamic transitions, and to identify some new attractors, over the parameter space of dilute nanorod volume fraction and nanorod activation strength. The particle-scale activation parameter corresponds experimentally to a tunable force dipole strength (so-called pushers with propulsion from the rod tail) generated by active rod macromolecules, e.g., catalysis with the solvent phase, ATP-induced propulsion, or light-activated propulsion. The simulations allow 2d spatial variations in all flow and orientational variables and full spherical orientational degrees of freedom; the attractors correspond to numerical integration of a coupled system of 125 nonlinear PDEs in 2d plus time. The phase diagrams with and without the polar interaction potential are remarkably similar, implying that polar interactions among the rodlike particles are not essential to long-range spatial and temporal correlations in flow, polarity, and nematic order. As a general rule, above a threshold, low volume fractions induce 1d banded patterns, whereas higher yet still dilute volume fractions yield 2d patterns. Again as a general rule, varying activation strength at fixed volume fraction induces novel dynamic transitions. First, stationary patterns saturate the instability of the isotropic
International Nuclear Information System (INIS)
Guo Boling
1994-01-01
We prove the existence of the global attractors for the generalized Landau-Lifshitz equation on compact manifold M, and give the upper and lower estimates of their Hausdorff and fractal dimensions. (author). 18 refs
On convergence of trajectory attractors of the 3D Navier-Stokes-α model as α approaches 0
International Nuclear Information System (INIS)
Vishik, M I; Chepyzhov, V V; Titi, E S
2007-01-01
We study the relations between the long-time dynamics of the Navier-Stokes-α model and the exact 3D Navier-Stokes system. We prove that bounded sets of solutions of the Navier-Stokes-α model converge to the trajectory attractor A 0 of the 3D Navier-Stokes system as the time approaches infinity and α approaches zero. In particular, we show that the trajectory attractor A α of the Navier-Stokes-α model converges to the trajectory attractor A 0 of the 3D Navier-Stokes system as α→0+. We also construct the minimal limit A min (subset or equal A 0 ) of the trajectory attractor A α as α→0+ and prove that the set A min is connected and strictly invariant. Bibliography: 35 titles.
Suppes, Trisha; Kelly, Dorothy I.; Keck, Paul E.; McElroy, Susan L.; Altshuler, Lori L.; Mintz, Jim; Frye, Mark A.; Nolen, Willem A.; Luckenbaugh, David A.; Post, Robert M.; Leverich, Gabriele S.; Kupka, Ralph W.; Grunze, Heinz
Continuation treatment for bipolar disorder often consists of a mood stabilizer and a second-generation antipsychotic. Quetiapine has been shown to be an effective treatment for acute mania and acute bipolar depression, but there are limited data for its use in continuation treatment. This study
Periodic dynamics in queuing networks
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Addabbo, Tommaso [Information Engineering Department, University of Siena, Via Roma 56, 53100 Siena (Italy)], E-mail: addabbo@dii.unisi.it; Kocarev, Ljupco [Macedonian Academy of Sciences and Arts, bul. Krste Misirkov 2, P.O. Box 428, 1000 Skopje, Republic of Macedonia (Macedonia, The Former Yugoslav Republic of)], E-mail: lkocarev@ucsd.edu
2009-08-30
This paper deals with state-dependent open Markovian (or exponential) queuing networks, for which arrival and service rates, as well as routing probabilities, may depend on the queue lengths. For a network of this kind, following Mandelbaum and Pats, we provide a formal definition of its associated fluid model, and we focus on the relationships which may occur between the network stochastic dynamics and the deterministic dynamics of its corresponding fluid model, particularly focusing on queuing networks whose fluid models have global periodic attractors.
You, Bo; Li, Fang
2016-01-01
This paper is concerned with the long-time behavior of solutions for the three dimensional viscous primitive equations of large-scale moist atmosphere. We prove the existence of a global attractor for the three dimensional viscous primitive equations of large-scale moist atmosphere by asymptotic a priori estimate and construct an exponential attractor by using the smoothing property of the semigroup generated by the three dimensional viscous primitive equations of large-scale moist atmosphere...
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Márquez, Bicky A., E-mail: bmarquez@ivic.gob.ve; Suárez-Vargas, José J., E-mail: jjsuarez@ivic.gob.ve; Ramírez, Javier A. [Centro de Física, Instituto Venezolano de Investigaciones Científicas, km. 11 Carretera Panamericana, Caracas 1020-A (Venezuela, Bolivarian Republic of)
2014-09-01
Controlled transitions between a hierarchy of n-scroll attractors are investigated in a nonlinear optoelectronic oscillator. Using the system's feedback strength as a control parameter, it is shown experimentally the transition from Van der Pol-like attractors to 6-scroll, but in general, this scheme can produce an arbitrary number of scrolls. The complexity of every state is characterized by Lyapunov exponents and autocorrelation coefficients.
Geirsson, Halldor; d'Oreye, Nicolas; Mashagiro, Niche; Syauswa, Muhindo; Celli, Gilles; Kadufu, Benjamin; Smets, Benoît; Kervyn, François
2017-10-01
We present an overview of the installation, operation, and initial results of the 15-station KivuGNet (Kivu Geodetic Network) in the Kivu Region, Central Africa. The network serves primarily as a research and monitoring tool for active volcanic, earthquake, and plate boundary processes in the region. Continuous operation of in-situ measurement networks in naturally and politically harsh environments is challenging, but has proven fruitful in this case. During the operation of the network since 2009, KivuGNet has captured: co-eruptive deformation from two eruptions of Nyamulagira (in 2010 and 2011-2012); inter-eruptive deformation, which we interpret as a combination of plate motion across the Western - East Africa Rift, and decreasing deep-seated magma accumulation under the Nyiragongo-Nyamulagira region; co-seismic deformation from the Mw5.8 August 7, 2015 Lwiro earthquake at the western border of Lake Kivu. We hope that this study will serve as a motivation for further implementation of in-situ geodetic networks in under-monitored and under-studied sections of the East African Rift.
Structural health monitoring based on sensitivity vector fields and attractor morphing.
Yin, Shih-Hsun; Epureanu, Bogdan I
2006-09-15
The dynamic responses of a thermo-shielding panel forced by unsteady aerodynamic loads and a classical Duffing oscillator are investigated to detect structural damage. A nonlinear aeroelastic model is obtained for the panel by using third-order piston theory to model the unsteady supersonic flow, which interacts with the panel. To identify damage, we analyse the morphology (deformation and movement) of the attractor of the dynamics of the aeroelastic system and the Duffing oscillator. Damages of various locations, extents and levels are shown to be revealed by the attractor-based analysis. For the panel, the type of damage considered is a local reduction in the bending stiffness. For the Duffing oscillator, variations in the linear and nonlinear stiffnesses and damping are considered as damage. Present studies of such problems are based on linear theories. In contrast, the presented approach using nonlinear dynamics has the potential of enhancing accuracy and sensitivity of detection.
Regularity of random attractors for fractional stochastic reaction-diffusion equations on Rn
Gu, Anhui; Li, Dingshi; Wang, Bixiang; Yang, Han
2018-06-01
We investigate the regularity of random attractors for the non-autonomous non-local fractional stochastic reaction-diffusion equations in Hs (Rn) with s ∈ (0 , 1). We prove the existence and uniqueness of the tempered random attractor that is compact in Hs (Rn) and attracts all tempered random subsets of L2 (Rn) with respect to the norm of Hs (Rn). The main difficulty is to show the pullback asymptotic compactness of solutions in Hs (Rn) due to the noncompactness of Sobolev embeddings on unbounded domains and the almost sure nondifferentiability of the sample paths of the Wiener process. We establish such compactness by the ideas of uniform tail-estimates and the spectral decomposition of solutions in bounded domains.
The de Sitter spacetime as an attractor solution in fourth-order gravity
International Nuclear Information System (INIS)
Schmidt, H.-J.
1988-01-01
We investigate the general vacuum solution of fourth-order gravity, and include the Bach tensor. For L 2 = 1.3μR 2 + 1/2αC 2 the expanding de Sitter spacetime is an attractor in the set of axially symmetric Bianchi type-I models if and only if αμ ≤ 0 or α > 4μ holds. It will be argued that this result holds true for a large class of inhomogeneous models. As a byproduct, a new closed-form cosmological solution, is obtained. It is also shown that the de Sitter spacetime is an attractor for the Bach-Einstein gravity with a minimally coupled scalar field φ. Specialised to Einstein gravity (i.e. α = 0 above) this conformal equivalence remains a non-trivial one. (author)
6d → 5d → 4d reduction of BPS attractors in flat gauged supergravities
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Kiril Hristov
2015-08-01
This is achieved starting from the BPS black string in 6d with an AdS3×S3 attractor and taking two different routes to arrive at a 1/2 BPS AdS2×S2 attractor of a non-BPS black hole in 4d N=2 flat gauged supergravity. The two inequivalent routes interchange the order of KK reduction on AdS3 and SS reduction on S3. We also find the commutator between the two operations after performing a duality transformation: on the level of the theory the result is the exchange of electric with magnetic gaugings; on the level of the solution we find a flip of the quartic invariant I4 to −I4.
A birational mapping with a strange attractor: post-critical set and covariant curves
International Nuclear Information System (INIS)
Bouamra, M; Hassani, S; Maillard, J-M
2009-01-01
We consider some two-dimensional birational transformations. One of them is a birational deformation of the Henon map. For some of these birational mappings, the post-critical set (i.e. the iterates of the critical set) is infinite and we show that this gives straightforwardly the algebraic covariant curves of the transformation when they exist. These covariant curves are used to build the preserved meromorphic 2-form. One may also have an infinite post-critical set yielding a covariant curve which is not algebraic (transcendental). For two of the birational mappings considered, the post-critical set is finite and we claim that there is no algebraic covariant curve and no preserved meromorphic 2-form. For these two mappings with finite post-critical sets, attracting sets occur and we show that they pass the usual tests (Lyapunov exponents and the fractal dimension) for being strange attractors. The strange attractor of one of these two mappings is unbounded.
Attractors of relaxation discrete-time systems with chaotic dynamics on a fast time scale
International Nuclear Information System (INIS)
Maslennikov, Oleg V.; Nekorkin, Vladimir I.
2016-01-01
In this work, a new type of relaxation systems is considered. Their prominent feature is that they comprise two distinct epochs, one is slow regular motion and another is fast chaotic motion. Unlike traditionally studied slow-fast systems that have smooth manifolds of slow motions in the phase space and fast trajectories between them, in this new type one observes, apart the same geometric objects, areas of transient chaos. Alternating periods of slow regular motions and fast chaotic ones as well as transitions between them result in a specific chaotic attractor with chaos on a fast time scale. We formulate basic properties of such attractors in the framework of discrete-time systems and consider several examples. Finally, we provide an important application of such systems, the neuronal electrical activity in the form of chaotic spike-burst oscillations.
STRANGE ATTRACTORS IN SYMMETRIC UNFOLDINGS OF A SINGULARITY WITH THREE-FOLD ZERO EIGENVALUE
Institute of Scientific and Technical Information of China (English)
Qinghua Zhou
2009-01-01
In this paper, we study the Sil'nikov heteroclinic bifurcations, which display strange attractors, for the symmetric versal unfoldings of the singularity at the origin with a nilpotent Linear part and 3-jet, using the normal form, the blow-up and the ge-neralized Mel'nikov methods of heteroclinic orbits to two hyperbolic or nonhyperbolic equilibria in a high-dimensional space.
Solving Stochastic Büchi Games on Infinite Arenas with a Finite Attractor
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Nathalie Bertrand
2013-06-01
Full Text Available We consider games played on an infinite probabilistic arena where the first player aims at satisfying generalized Büchi objectives almost surely, i.e., with probability one. We provide a fixpoint characterization of the winning sets and associated winning strategies in the case where the arena satisfies the finite-attractor property. From this we directly deduce the decidability of these games on probabilistic lossy channel systems.
Amplification and displacement of chaotic attractors by means of unidirectional chaotic driving
González-Miranda, J. M.
1998-06-01
Chaotic systems, when used to drive copies of themselves (or parts of themselves) may induce interesting behaviors in the driven system. In case the later exhibits invariance under amplification or translation, they may show amplification (reduction), or displacement of the attractor. It is shown how the behavior to be obtained is implied by the symmetries involved. Two explicit examples are studied to show how these phenomena manifest themselves under perfect and imperfect coupling.
Shen, Xu; Tian, Xinmei; Liu, Tongliang; Xu, Fang; Tao, Dacheng
2017-10-03
Dropout has been proven to be an effective algorithm for training robust deep networks because of its ability to prevent overfitting by avoiding the co-adaptation of feature detectors. Current explanations of dropout include bagging, naive Bayes, regularization, and sex in evolution. According to the activation patterns of neurons in the human brain, when faced with different situations, the firing rates of neurons are random and continuous, not binary as current dropout does. Inspired by this phenomenon, we extend the traditional binary dropout to continuous dropout. On the one hand, continuous dropout is considerably closer to the activation characteristics of neurons in the human brain than traditional binary dropout. On the other hand, we demonstrate that continuous dropout has the property of avoiding the co-adaptation of feature detectors, which suggests that we can extract more independent feature detectors for model averaging in the test stage. We introduce the proposed continuous dropout to a feedforward neural network and comprehensively compare it with binary dropout, adaptive dropout, and DropConnect on Modified National Institute of Standards and Technology, Canadian Institute for Advanced Research-10, Street View House Numbers, NORB, and ImageNet large scale visual recognition competition-12. Thorough experiments demonstrate that our method performs better in preventing the co-adaptation of feature detectors and improves test performance.
On dynamics analysis of a new chaotic attractor
International Nuclear Information System (INIS)
Zhou Wuneng; Xu Yuhua; Lu Hongqian; Pan Lin
2008-01-01
In this Letter, a new chaotic system is discussed. Some basic dynamical properties, such as Lyapunov exponents, Poincare mapping, fractal dimension, bifurcation diagram, continuous spectrum and chaotic dynamical behaviors of the new chaotic system are studied, either numerically or analytically. The obtained results show clearly that the system discussed in this Letter is a new chaotic system and deserves a further detailed investigation
Impact of the updating scheme on stationary states of networks
International Nuclear Information System (INIS)
Radicchi, F; Ahn, Y Y; Meyer-Ortmanns, H
2008-01-01
From Boolean networks it is well known that the number of attractors as a function of the system size depends on the updating scheme which is chosen either synchronously or asynchronously. In this contribution, we report on a systematic interpolation between synchronous and asynchronous updating in a one-dimensional chain of Ising spins. The stationary state for fully synchronous updating is antiferromagnetic. The interpolation allows us to locate a phase transition between phases with an absorbing and a fluctuating stationary state. The associated universality class is that of parity conservation. We also report on a more recent study of asynchronous updates applied to the yeast cell-cycle network. Compared to the synchronous update, the basin of attraction of the largest attractor considerably shrinks and the convergence to the biological pathway slows down and is less dominant. Both examples illustrate how sensitively the stationary states and the properties of attractors can depend on the updating mode of the algorithm
Stochastic inflation in phase space: is slow roll a stochastic attractor?
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Grain, Julien [Institut d' Astrophysique Spatiale, UMR8617, CNRS, Univ. Paris Sud, Université Paris-Saclay, Bt. 121, Orsay, F-91405 (France); Vennin, Vincent, E-mail: julien.grain@ias.u-psud.fr, E-mail: vincent.vennin@port.ac.uk [Institute of Cosmology and Gravitation, University of Portsmouth, Dennis Sciama Building, Burnaby Road, Portsmouth, PO13FX (United Kingdom)
2017-05-01
An appealing feature of inflationary cosmology is the presence of a phase-space attractor, ''slow roll'', which washes out the dependence on initial field velocities. We investigate the robustness of this property under backreaction from quantum fluctuations using the stochastic inflation formalism in the phase-space approach. A Hamiltonian formulation of stochastic inflation is presented, where it is shown that the coarse-graining procedure—where wavelengths smaller than the Hubble radius are integrated out—preserves the canonical structure of free fields. This means that different sets of canonical variables give rise to the same probability distribution which clarifies the literature with respect to this issue. The role played by the quantum-to-classical transition is also analysed and is shown to constrain the coarse-graining scale. In the case of free fields, we find that quantum diffusion is aligned in phase space with the slow-roll direction. This implies that the classical slow-roll attractor is immune to stochastic effects and thus generalises to a stochastic attractor regardless of initial conditions, with a relaxation time at least as short as in the classical system. For non-test fields or for test fields with non-linear self interactions however, quantum diffusion and the classical slow-roll flow are misaligned. We derive a condition on the coarse-graining scale so that observational corrections from this misalignment are negligible at leading order in slow roll.
Phase-space analysis of the cosmological 3-fluid problem: families of attractors and repellers
International Nuclear Information System (INIS)
Azreg-Aïnou, Mustapha
2013-01-01
We perform a phase-space analysis of the cosmological 3-fluid problem consisting of a barotropic fluid with an equation-of-state parameter γ − 1, a pressureless dark matter fluid, plus a scalar field ϕ (representing dark energy) coupled to an exponential potential V = V 0 exp ( − κλϕ). Besides the potential–kinetic scaling solutions, which are not the unique late-time attractors whenever they exist for λ 2 ⩾ 3γ, we derive new attractors where both dark energy and dark matter coexist and the final density is shared in a way independent of the value of γ > 1. The case of a pressureless barotropic fluid (γ = 1) has a one-parameter family of attractors where all components coexist. New one-parameter families of matter–dark matter saddle points and kinetic–matter repellers exist. We investigate the stability of the ten critical points by linearization and/or Lyapunov's theorems and a variant of the theorems formulated in this paper. A solution with two transient periods of acceleration and two transient periods of deceleration is derived. (paper)
Supersymmetric mechanics. Vol. 2. The attractor mechanism and space time singularities
International Nuclear Information System (INIS)
Bellucci, S.; Marrani, A.; Ferrara, S.
2006-01-01
This is the second volume in a series of books on the general theme of Supersymmetric Mechanics; the series is based on lectures and discussions held in 2005 and 2006 at the INFN-Laboratori Nazionali di Frascati. The first volume appears as Lect. Notes Physics, Vol. 698 ''Supersymmetric Mechanics, Vol.1: Supersymmetry, Noncommutativity and Matrix Models'' (2006) ISBN: 3-540-33313-4. The present extensive lecture supplies a pedagogical introduction, at the non-expert level, to the attractor mechanism in space-time singularities. In such a framework, supersymmetry seems to be related to dynamical systems with fixed points, describing the equilibrium state and the stability features of the thermodynamics of black holes. After a qualitative overview, explicit examples realizing the attractor mechanism are treated at some length; they include relevant cases of asymptotically flat, maximal and non-maximal, extended supergravities in 4 and 5 dimensions. A number of recent advances along various directions of research on the attractor mechanism are also given. (orig.)
Attractor States in Teaching and Learning Processes: A Study of Out-of-School Science Education.
Geveke, Carla H; Steenbeek, Henderien W; Doornenbal, Jeannette M; Van Geert, Paul L C
2017-01-01
In order for out-of-school science activities that take place during school hours but outside the school context to be successful, instructors must have sufficient pedagogical content knowledge (PCK) to guarantee high-quality teaching and learning. We argue that PCK is a quality of the instructor-pupil system that is constructed in real-time interaction. When PCK is evident in real-time interaction, we define it as Expressed Pedagogical Content Knowledge (EPCK). The aim of this study is to empirically explore whether EPCK shows a systematic pattern of variation, and if so whether the pattern occurs in recurrent and temporary stable attractor states as predicted in the complex dynamic systems theory. This study concerned nine out-of-school activities in which pupils of upper primary school classes participated. A multivariate coding scheme was used to capture EPCK in real time. A principal component analysis of the time series of all the variables reduced the number of components. A cluster revealed general descriptions of the components across all cases. Cluster analyses of individual cases divided the time series into sequences, revealing High-, Low-, and Non-EPCK states. High-EPCK attractor states emerged at particular moments during activities, rather than being present all the time. Such High-EPCK attractor states were only found in a few cases, namely those where the pupils were prepared for the visit and the instructors were trained.
Hypercrater Bifurcations, Attractor Coexistence, and Unfolding in a 5D Model of Economic Dynamics
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Toichiro Asada
2011-01-01
Full Text Available Complex dynamical features are explored in a discrete interregional macrodynamic model proposed by Asada et al., using numerical methods. The model is five-dimensional with four parameters. The results demonstrate patterns of dynamical behaviour, such as bifurcation processes and coexistence of attractors, generated by high-dimensional discrete systems. In three cases of two-dimensional parameter subspaces the stability of equilibrium region is determined and its boundaries, the flip and Neimark-Hopf bifurcation curves, are identified by means of necessary coefficient criteria. In the first case closed invariant curves (CICs are found to occur through 5D-crater-type bifurcations, and for certain ranges of parameter values a stable equilibrium coexists with an unstable CIC associated with the subcritical bifurcation, as well as with an outer stable CIC. A remarkable feature of the second case is the coexistence of two attracting CICs outside the stability region. In both these cases the related hysteresis effects are illustrated by numerical simulations. In the third case a remarkable feature is the apparent unfolding of an attracting CIC before it evolves to a chaotic attractor. Examples of CICs and chaotic attractors are given in subspaces of phase space.
Learning rate and attractor size of the single-layer perceptron
International Nuclear Information System (INIS)
Singleton, Martin S.; Huebler, Alfred W.
2007-01-01
We study the simplest possible order one single-layer perceptron with two inputs, using the delta rule with online learning, in order to derive closed form expressions for the mean convergence rates. We investigate the rate of convergence in weight space of the weight vectors corresponding to each of the 14 out of 16 linearly separable rules. These vectors follow zigzagging lines through the piecewise constant vector field to their respective attractors. Based on our studies, we conclude that a single-layer perceptron with N inputs will converge in an average number of steps given by an Nth order polynomial in (t/l), where t is the threshold, and l is the size of the initial weight distribution. Exact values for these averages are provided for the five linearly separable classes with N=2. We also demonstrate that the learning rate is determined by the attractor size, and that the attractors of a single-layer perceptron with N inputs partition R N +R N
Griffin: A Tool for Symbolic Inference of Synchronous Boolean Molecular Networks
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Stalin Muñoz
2018-03-01
Full Text Available Boolean networks are important models of biochemical systems, located at the high end of the abstraction spectrum. A number of Boolean gene networks have been inferred following essentially the same method. Such a method first considers experimental data for a typically underdetermined “regulation” graph. Next, Boolean networks are inferred by using biological constraints to narrow the search space, such as a desired set of (fixed-point or cyclic attractors. We describe Griffin, a computer tool enhancing this method. Griffin incorporates a number of well-established algorithms, such as Dubrova and Teslenko's algorithm for finding attractors in synchronous Boolean networks. In addition, a formal definition of regulation allows Griffin to employ “symbolic” techniques, able to represent both large sets of network states and Boolean constraints. We observe that when the set of attractors is required to be an exact set, prohibiting additional attractors, a naive Boolean coding of this constraint may be unfeasible. Such cases may be intractable even with symbolic methods, as the number of Boolean constraints may be astronomically large. To overcome this problem, we employ an Artificial Intelligence technique known as “clause learning” considerably increasing Griffin's scalability. Without clause learning only toy examples prohibiting additional attractors are solvable: only one out of seven queries reported here is answered. With clause learning, by contrast, all seven queries are answered. We illustrate Griffin with three case studies drawn from the Arabidopsis thaliana literature. Griffin is available at: http://turing.iimas.unam.mx/griffin.
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Danielle Aparecida Nascimento dos Santos
2012-12-01
Full Text Available We describe the analysis of a course in distance mode for the use of Assistive Technology promoted through a Continuing Education Program for Teachers in Special Education from the Ministry of Education. Thus, we performed an analysis of documents (notices, references, manual Course: Assistive Technology, Projects and Accessibility: Promoting Inclusion School (Course TA.The course objective is to support the development of theoretical and practical knowledge to the students in attendance target of special educationin public schools.Thus, we believe that the demonstrations participant teachers are scoring on the need to participate in a process of continuous training on Special Education from the perspective of inclusive education.
Energy Technology Data Exchange (ETDEWEB)
Quinn, N.W.T.; Ortega, R.; Holm, L.
2010-01-05
This paper describes a new approach to environmental decision support for salinity management in the San Joaquin Basin of California that focuses on web-based data sharing using YSI Econet technology and continuous data quality management using a novel software tool, Aquarius.
Kanno, Yoichiro; Vokoun, Jason C.; Letcher, Benjamin H.
2011-01-01
Linear and heterogeneous habitat makes headwater stream networks an ideal ecosystem in which to test the influence of environmental factors on spatial genetic patterns of obligatory aquatic species. We investigated fine-scale population structure and influence of stream habitat on individual-level genetic differentiation in brook trout (Salvelinus fontinalis) by genotyping eight microsatellite loci in 740 individuals in two headwater channel networks (7.7 and 4.4 km) in Connecticut, USA. A weak but statistically significant isolation-by-distance pattern was common in both sites. In the field, many tagged individuals were recaptured in the same 50-m reaches within a single field season (summer to fall). One study site was characterized with a hierarchical population structure, where seasonal barriers (natural falls of 1.5–2.5 m in height during summer base-flow condition) greatly reduced gene flow and perceptible spatial patterns emerged because of the presence of tributaries, each with a group of genetically distinguishable individuals. Genetic differentiation increased when pairs of individuals were separated by high stream gradient (steep channel slope) or warm stream temperature in this site, although the evidence of their influence was equivocal. In a second site, evidence for genetic clusters was weak at best, but genetic differentiation between individuals was positively correlated with number of tributary confluences. We concluded that the population-level movement of brook trout was limited in the study headwater stream networks, resulting in the fine-scale population structure (genetic clusters and clines) even at distances of a few kilometres, and gene flow was mitigated by ‘riverscape’ variables, particularly by physical barriers, waterway distance (i.e. isolation-by-distance) and the presence of tributaries.
Dierck, Carina
2018-01-01
CSWS is an age-related epileptic encephalopathy consisting of the triad of seizures, neuropsychological impairment and a specific EEG-pattern. This EEG-pattern is characterized by spike-and-wave-discharges emphasized during non-REM sleep. Until now, little has been known about the pathophysiologic processes. So far research approaches on the underlying neuronal network have been based on techniques with a good spatial but poor temporal resolution like fMRI and FDG-PET. In this study the se...
Self-organizing maps based on limit cycle attractors.
Huang, Di-Wei; Gentili, Rodolphe J; Reggia, James A
2015-03-01
Recent efforts to develop large-scale brain and neurocognitive architectures have paid relatively little attention to the use of self-organizing maps (SOMs). Part of the reason for this is that most conventional SOMs use a static encoding representation: each input pattern or sequence is effectively represented as a fixed point activation pattern in the map layer, something that is inconsistent with the rhythmic oscillatory activity observed in the brain. Here we develop and study an alternative encoding scheme that instead uses sparsely-coded limit cycles to represent external input patterns/sequences. We establish conditions under which learned limit cycle representations arise reliably and dominate the dynamics in a SOM. These limit cycles tend to be relatively unique for different inputs, robust to perturbations, and fairly insensitive to timing. In spite of the continually changing activity in the map layer when a limit cycle representation is used, map formation continues to occur reliably. In a two-SOM architecture where each SOM represents a different sensory modality, we also show that after learning, limit cycles in one SOM can correctly evoke corresponding limit cycles in the other, and thus there is the potential for multi-SOM systems using limit cycles to work effectively as hetero-associative memories. While the results presented here are only first steps, they establish the viability of SOM models based on limit cycle activity patterns, and suggest that such models merit further study. Copyright © 2014 Elsevier Ltd. All rights reserved.
Noise in attractor networks in the brain produced by graded firing rate representations
Webb, Tristan J.; Rolls, Edmund T; Deco, Gustavo; Feng, Jianfeng
2011-01-01
Representations in the cortex are often distributed with graded firing rates in the neuronal populations. The firing rate\\ud probability distribution of each neuron to a set of stimuli is often exponential or gamma. In processes in the brain, such as\\ud decision-making, that are influenced by the noise produced by the close to random spike timings of each neuron for a given\\ud mean rate, the noise with this graded type of representation may be larger than with the binary firing rate distribut...
Denis-le Coarer, Florian; Quirce, Ana; Valle, Angel; Pesquera, Luis; Rodríguez, Miguel A.; Panajotov, Krassimir; Sciamanna, Marc
2018-03-01
We present experimental and theoretical results of noise-induced attractor hopping between dynamical states found in a single transverse mode vertical-cavity surface-emitting laser (VCSEL) subject to parallel optical injection. These transitions involve dynamical states with different polarizations of the light emitted by the VCSEL. We report an experimental map identifying, in the injected power-frequency detuning plane, regions where attractor hopping between two, or even three, different states occur. The transition between these behaviors is characterized by using residence time distributions. We find multistability regions that are characterized by heavy-tailed residence time distributions. These distributions are characterized by a -1.83 ±0.17 power law. Between these regions we find coherence enhancement of noise-induced attractor hopping in which transitions between states occur regularly. Simulation results show that frequency detuning variations and spontaneous emission noise play a role in causing switching between attractors. We also find attractor hopping between chaotic states with different polarization properties. In this case, simulation results show that spontaneous emission noise inherent to the VCSEL is enough to induce this hopping.
Applications of (a,b)-continued fraction transformations
Katok, Svetlana; Ugarcovici, Ilie
2011-01-01
We describe a general method of arithmetic coding of geodesics on the modular surface based on a two parameter family of continued fraction transformations studied previously by the authors. The finite rectangular structure of the attractors of the natural extension maps and the corresponding "reduction theory" play an essential role. In special cases, when an (a,b)-expansion admits a so-called "dual", the coding sequences are obtained by juxtaposition of the boundary expansions of the fixed ...
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Mohtasham Ghaffari
2017-07-01
Full Text Available Background: Distanceeducation for mothers with suckling babies can have a high effect and more proponents due to short time of such mothers as well as other problems like bringing infant with themselves. Authors of this research have shared an experience on application of social network of Telegram for educational intervention in field of continued breast feeding and complementary feeding of children among Iranian women. Materials and Methods: In this research, social network of Telegram was employed to provide teachings associated with continued breastfeeding and complementary feeding of children to mothers based on the model of Center for Diseases Control of USA (CDC. 90 members, out of 125 mothers who were informed, became member of Telegram group voluntary with informed consent,namely that the participation rate was 72%. The Telegram group called "Mother’s love - Mother’s milk" was designed on August 2016 and has been active for 6 months until this date. The group has been active under the management of an experienced physician and consultation with a pharmacist. Results: Participants of this research reported cell phone, internet, physician, books, and journals as the most-used sources, respectively, to access to information about breast feeding and health of their children. Only five mother of group-member mothers were uneducated or had elementary education level. Also, it was determined that the higher percentage of women who joined Telegram group were housewives compared with the group who had no tendency to join group. 100% of members evaluated membership in Telegram group and subjects related to complementary feeding beneficial and 39 of 41 (95% participants in an E-survey, were satisfied with learning, and 35 members (85.4% were satisfied with teaching. Conclusion: This study highlights the importance of social networks as potential educational field. Usage of this media, particularly among women groups under specific circumstance
Directory of Open Access Journals (Sweden)
Lorenzo Peppoloni
Full Text Available The Strength-Dexterity (SD test measures the ability of the pulps of the thumb and index finger to compress a compliant and slender spring prone to buckling at low forces (<3N. We know that factors such as aging and neurodegenerative conditions bring deteriorating physiological changes (e.g., at the level of motor cortex, cerebellum, and basal ganglia, which lead to an overall loss of dexterous ability. However, little is known about how these changes reflect upon the dynamics of the underlying biological system. The spring-hand system exhibits nonlinear dynamical behavior and here we characterize the dynamical behavior of the phase portraits using attractor reconstruction. Thirty participants performed the SD test: 10 young adults, 10 older adults, and 10 older adults with Parkinson's disease (PD. We used delayed embedding of the applied force to reconstruct its attractor. We characterized the distribution of points of the phase portraits by their density (number of distant points and interquartile range and geometric features (trajectory length and size. We find phase portraits from older adults exhibit more distant points (p = 0.028 than young adults and participants with PD have larger interquartile ranges (p = 0.001, trajectory lengths (p = 0.005, and size (p = 0.003 than their healthy counterparts. The increased size of the phase portraits with healthy aging suggests a change in the dynamical properties of the system, which may represent a weakening of the neural control strategy. In contrast, the distortion of the attractor in PD suggests a fundamental change in the underlying biological system, and disruption of the neural control strategy. This ability to detect differences in the biological mechanisms of dexterity in healthy and pathological aging provides a simple means to assess their disruption in neurodegenerative conditions and justifies further studies to understand the link with the physiological changes.
AHaH Computing–From Metastable Switches to Attractors to Machine Learning
Nugent, Michael Alexander; Molter, Timothy Wesley
2014-01-01
Modern computing architecture based on the separation of memory and processing leads to a well known problem called the von Neumann bottleneck, a restrictive limit on the data bandwidth between CPU and RAM. This paper introduces a new approach to computing we call AHaH computing where memory and processing are combined. The idea is based on the attractor dynamics of volatile dissipative electronics inspired by biological systems, presenting an attractive alternative architecture that is able to adapt, self-repair, and learn from interactions with the environment. We envision that both von Neumann and AHaH computing architectures will operate together on the same machine, but that the AHaH computing processor may reduce the power consumption and processing time for certain adaptive learning tasks by orders of magnitude. The paper begins by drawing a connection between the properties of volatility, thermodynamics, and Anti-Hebbian and Hebbian (AHaH) plasticity. We show how AHaH synaptic plasticity leads to attractor states that extract the independent components of applied data streams and how they form a computationally complete set of logic functions. After introducing a general memristive device model based on collections of metastable switches, we show how adaptive synaptic weights can be formed from differential pairs of incremental memristors. We also disclose how arrays of synaptic weights can be used to build a neural node circuit operating AHaH plasticity. By configuring the attractor states of the AHaH node in different ways, high level machine learning functions are demonstrated. This includes unsupervised clustering, supervised and unsupervised classification, complex signal prediction, unsupervised robotic actuation and combinatorial optimization of procedures–all key capabilities of biological nervous systems and modern machine learning algorithms with real world application. PMID:24520315
AHaH computing-from metastable switches to attractors to machine learning.
Directory of Open Access Journals (Sweden)
Michael Alexander Nugent
Full Text Available Modern computing architecture based on the separation of memory and processing leads to a well known problem called the von Neumann bottleneck, a restrictive limit on the data bandwidth between CPU and RAM. This paper introduces a new approach to computing we call AHaH computing where memory and processing are combined. The idea is based on the attractor dynamics of volatile dissipative electronics inspired by biological systems, presenting an attractive alternative architecture that is able to adapt, self-repair, and learn from interactions with the environment. We envision that both von Neumann and AHaH computing architectures will operate together on the same machine, but that the AHaH computing processor may reduce the power consumption and processing time for certain adaptive learning tasks by orders of magnitude. The paper begins by drawing a connection between the properties of volatility, thermodynamics, and Anti-Hebbian and Hebbian (AHaH plasticity. We show how AHaH synaptic plasticity leads to attractor states that extract the independent components of applied data streams and how they form a computationally complete set of logic functions. After introducing a general memristive device model based on collections of metastable switches, we show how adaptive synaptic weights can be formed from differential pairs of incremental memristors. We also disclose how arrays of synaptic weights can be used to build a neural node circuit operating AHaH plasticity. By configuring the attractor states of the AHaH node in different ways, high level machine learning functions are demonstrated. This includes unsupervised clustering, supervised and unsupervised classification, complex signal prediction, unsupervised robotic actuation and combinatorial optimization of procedures-all key capabilities of biological nervous systems and modern machine learning algorithms with real world application.
Janz, M.
2017-12-01
Data Refuge began as concerns grew about the vulnerability of federal climate and environmental data. The project began by hosting a Data Rescue event that intended to educate attendees about the risks that exist for digital information, advocate for the many local uses of climate and environmental data, and create research copies of federal climate and environmental data that would be held off federal servers. This workflow was used by many other Data Rescue events over the next few months and caught the attention of many interested groups. Those groups included federal agencies, data managers and curators, open data and open government proponents, and librarians and archivists. The Data Refuge project team brought these stakeholders together at the Libraries+ Network meeting to talk about this complicated problem space and to encourage new partnerships to experiment with solutions. The team at University of Pennsylvania is working on federal, regional, and local projects that address some aspects of the problem while many other organizations and universities are working on others. This talk will serve as an update on those projects, the lessons learned from them, and the challenges that remain.
International Nuclear Information System (INIS)
Astone, P; Colla, A; Frasca, S; Palomba, C; D'Antonio, S
2012-01-01
We describe the extension to multiple datasets of a coherent method for the search of continuous gravitational wave signals, based on the computation of 5-vectors. In particular, we show how to coherently combine different datasets belonging to the same detector or to different detectors. In the latter case the coherent combination is the way to have the maximum increase in signal-to-noise ratio. If the datasets belong to the same detector the advantage comes mainly from the properties of a quantity called coherence which is helpful (in both cases, in fact) in rejecting false candidates. The method has been tested searching for simulated signals injected in Gaussian noise and the results of the simulations are discussed.
Szejka, Agnes; Drossel, Barbara
2010-02-01
We study the evolution of Boolean networks as model systems for gene regulation. Inspired by biological networks, we select simultaneously for robust attractors and for the ability to respond to external inputs by changing the attractor. Mutations change the connections between the nodes and the update functions. In order to investigate the influence of the type of update functions, we perform our simulations with canalizing as well as with threshold functions. We compare the properties of the fitness landscapes that result for different versions of the selection criterion and the update functions. We find that for all studied cases the fitness landscape has a plateau with maximum fitness resulting in the fact that structurally very different networks are able to fulfill the same task and are connected by neutral paths in network (“genotype”) space. We find furthermore a connection between the attractor length and the mutational robustness, and an extremely long memory of the initial evolutionary stage.
Attractors, statefinders and observational measurement for chameleonic Brans-Dicke cosmology
International Nuclear Information System (INIS)
Farajollahi, Hossein; Salehi, Amin
2010-01-01
We investigate chameleonic Brans-Dicke model applied to the FRW universes. A framework to study stability and attractor solutions in the phase space is developed for the model. We show that depending on the matter field and stability conditions, it is possible to realize phantom-like behavior without introducing phantom filed in the model while the stability is fulfilled and phantom crossing occurs. The statefinder parameters to the model for different kinds of matter interacting with the chameleon scalar field are studied. We also compare our model with present day observations
Attractors, statefinders and observational measurement for chameleonic Brans-Dicke cosmology
Energy Technology Data Exchange (ETDEWEB)
Farajollahi, Hossein; Salehi, Amin, E-mail: hosseinf@guilan.ac.ir, E-mail: a.salehi@guilan.ac.ir [Department of Physics, University of Guilan, Rasht (Iran, Islamic Republic of)
2010-11-01
We investigate chameleonic Brans-Dicke model applied to the FRW universes. A framework to study stability and attractor solutions in the phase space is developed for the model. We show that depending on the matter field and stability conditions, it is possible to realize phantom-like behavior without introducing phantom filed in the model while the stability is fulfilled and phantom crossing occurs. The statefinder parameters to the model for different kinds of matter interacting with the chameleon scalar field are studied. We also compare our model with present day observations.
A novel double-convection chaotic attractor, its adaptive control and circuit simulation
Mamat, M.; Vaidyanathan, S.; Sambas, A.; Mujiarto; Sanjaya, W. S. M.; Subiyanto
2018-03-01
A 3-D novel double-convection chaotic system with three nonlinearities is proposed in this research work. The dynamical properties of the new chaotic system are described in terms of phase portraits, Lyapunov exponents, Kaplan-Yorke dimension, dissipativity, stability analysis of equilibria, etc. Adaptive control and synchronization of the new chaotic system with unknown parameters are achieved via nonlinear controllers and the results are established using Lyapunov stability theory. Furthermore, an electronic circuit realization of the new 3-D novel chaotic system is presented in detail. Finally, the circuit experimental results of the 3-D novel chaotic attractor show agreement with the numerical simulations.
Directory of Open Access Journals (Sweden)
A. Weissblut
2012-03-01
Full Text Available This article – introduction to the structural theory of general view dynamical systems, based on construction of dynamic quantum models (DQM, offered by the author. This model is simply connected with traditional model of quantum mechanics (i.e. with the Schrodinger equation. At the same time obtained thus non – Hamiltonian quantum dynamics is easier than classical one: it allow building the clear structural theory and effective algorithms of research for concrete systems. This article is devoted mainly to such task. The algorithm of search for DQM attractors, based on this approach, is offered here.
CMB constraints on the inflaton couplings and reheating temperature in α-attractor inflation
Drewes, Marco; Kang, Jin U.; Mun, Ui Ri
2017-11-01
We study reheating in α-attractor models of inflation in which the inflaton couples to other scalars or fermions. We show that the parameter space contains viable regions in which the inflaton couplings to radiation can be determined from the properties of CMB temperature fluctuations, in particular the spectral index. This may be the only way to measure these fundamental microphysical parameters, which shaped the universe by setting the initial temperature of the hot big bang and contain important information about the embedding of a given model of inflation into a more fundamental theory of physics. The method can be applied to other models of single field inflation.
Birth of new folds and competing attractors in Elmo Bumpy Torus
Energy Technology Data Exchange (ETDEWEB)
Punjabi, A; Vahala, G
1984-04-09
The topology of equilibrium surfaces for the point model equations with neoclassical nonresonant ions in EBT is a complicated nongradient-dynamic version of the canonical cusp catastrophe. New folds emerge from degenerate equilibrium surfaces as the control vector (filling pressure, microwave power, ambipolar potential) is changed. Strong sensitivity to small changes in initial conditions of the state variables (electron/ion temperatures, plasma density) is found that can drastically alter the final equilibrium state when competing point attractors are present. 5 references, 3 figures.
Induced gravity and the attractor dynamics of dark energy/dark matter
International Nuclear Information System (INIS)
Cervantes-Cota, Jorge L.; Putter, Roland de; Linder, Eric V.
2010-01-01
Attractor solutions that give dynamical reasons for dark energy to act like the cosmological constant, or behavior close to it, are interesting possibilities to explain cosmic acceleration. Coupling the scalar field to matter or to gravity enlarges the dynamical behavior; we consider both couplings together, which can ameliorate some problems for each individually. Such theories have also been proposed in a Higgs-like fashion to induce gravity and unify dark energy and dark matter origins. We explore restrictions on such theories due to their dynamical behavior compared to observations of the cosmic expansion. Quartic potentials in particular have viable stability properties and asymptotically approach general relativity
On the global attractor of 2D incompressible turbulence with random forcing
Emami, Pedram; Bowman, John C.
2018-03-01
This study revisits bounds on the projection of the global attractor in the energy-enstrophy plane for 2D incompressible turbulence [Dascaliuc, Foias, and Jolly, 2005, 2010]. In addition to providing more elegant proofs of some of the required nonlinear identities, the treatment is extended from the case of constant forcing to the more realistic case of random forcing. Numerical simulations in particular often use a stochastic white-noise forcing to achieve a prescribed mean energy injection rate. The analytical bounds are demonstrated numerically for the case of white-noise forcing.
Energy landscapes of resting-state brain networks
Directory of Open Access Journals (Sweden)
Takamitsu eWatanabe
2014-02-01
Full Text Available During rest, the human brain performs essential functions such as memory maintenance, which are associated with resting-state brain networks (RSNs including the default-mode network (DMN and frontoparietal network (FPN. Previous studies based on spiking-neuron network models and their reduced models, as well as those based on imaging data, suggest that resting-state network activity can be captured as attractor dynamics, i.e., dynamics of the brain state toward an attractive state and transitions between different attractors. Here, we analyze the energy landscapes of the RSNs by applying the maximum entropy model, or equivalently the Ising spin model, to human RSN data. We use the previously estimated parameter values to define the energy landscape, and the disconnectivity graph method to estimate the number of local energy minima (equivalent to attractors in attractor dynamics, the basin size, and hierarchical relationships among the different local minima. In both of the DMN and FPN, low-energy local minima tended to have large basins. A majority of the network states belonged to a basin of one of a few local minima. Therefore, a small number of local minima constituted the backbone of each RSN. In the DMN, the energy landscape consisted of two groups of low-energy local minima that are separated by a relatively high energy barrier. Within each group, the activity patterns of the local minima were similar, and different minima were connected by relatively low energy barriers. In the FPN, all dominant energy were separated by relatively low energy barriers such that they formed a single coarse-grained global minimum. Our results indicate that multistable attractor dynamics may underlie the DMN, but not the FPN, and assist memory maintenance with different memory states.
Lien, C.-H.; Vaidyanathan, S.; Sambas, A.; Sukono; Mamat, M.; Sanjaya, W. S. M.; Subiyanto
2018-03-01
A 3-D new two-scroll chaotic attractor with three quadratic nonlinearities is investigated in this paper. First, the qualitative and dynamical properties of the new two-scroll chaotic system are described in terms of phase portraits, equilibrium points, Lyapunov exponents, Kaplan-Yorke dimension, dissipativity, etc. We show that the new two-scroll dissipative chaotic system has three unstable equilibrium points. As an engineering application, global chaos control of the new two-scroll chaotic system with unknown system parameters is designed via adaptive feedback control and Lyapunov stability theory. Furthermore, an electronic circuit realization of the new chaotic attractor is presented in detail to confirm the feasibility of the theoretical chaotic two-scroll attractor model.
Rauno Lindholm, Daniel; Boisen Devantier, Lykke; Nyborg, Karoline Lykke; Høgsbro, Andreas; Fries, de; Skovlund, Louise
2016-01-01
The purpose of this project was to examine what influencing factor that has had an impact on the presumed increasement of the use of networking among academics on the labour market and how it is expressed. On the basis of the influence from globalization on the labour market it can be concluded that the globalization has transformed the labour market into a market based on the organization of networks. In this new organization there is a greater emphasis on employees having social qualificati...
Nagano, Y; Teraguchi, T; Lieu, P K; Furumai, H
2014-01-01
In the Citadel area of Hue City, drainage systems that include canals and ponds are considerable sources of fecal contaminants to inundated water during the rainy season because canals and ponds receive untreated wastewater. It is important to investigate the characteristics of hydraulics and water pollution in canals and ponds. At the canals and ponds, water sampling was conducted during dry and wet weather periods in order to evaluate fecal contamination and to investigate changes in water pollution caused by runoff inflow. Inundated water was also collected from streets during heavy rainfall. At the canals and ponds, concentrations of Escherichia coli and total coliform exceeded the Vietnamese regulation values for surface water in 23 and 24 out of 27 samples (85 and 89%), respectively. The water samples were categorized based on the characteristics of water pollution using cluster analysis. In the rainy season, continuous monitoring was conducted at the canals and ponds using water depth and electrical conductivity (EC) sensors to investigate the dynamic relationship between water level and water pollution. It is suggested that in the canals, high EC meant water stagnation and low EC signified river water inflow. Therefore, EC might be a good indicator of water flow change in canals.
Directory of Open Access Journals (Sweden)
Federico Conrado
2017-01-01
Full Text Available In order to overcome thermal resistance issues in polymeric matrix composites, self-standing graphene aerogels were synthetized and infiltrated with an epoxy resin, in order to create conductive preferential pathways through which heat can be easily transported. These continuous highly thermally conductive 3D-structures show, due to the high interconnection degree of graphene flakes, enhanced transport properties. Two kinds of aerogels were investigated, obtained by hydrothermal synthesis (HS and ice-templated direct freeze synthesis (DFS. Following HS method an isotropic structure is obtained, and following DFS method instead an anisotropic arrangement of graphene flakes results. The density of the structure can be tuned leading to a different amount of graphene inside the final composite. The residual oxygen, known to be detrimental to thermal properties, was removed by thermal treatment before the infiltration process. With 1,25 wt.% of graphene, using HS method, the thermal conductivity of the polymeric resin was increased by 80%, suggesting that this technique is a valid route to improve the thermal performance of graphene-based composites. When preferential orientation of the filler was present (DFS case, thermal conductivity was increased more than 25% with a graphene content of only 0,27 wt.%, demonstrating that oriented structures can further improve the thermal transport efficiency.
Identification of core pathways based on attractor and crosstalk in ischemic stroke.
Diao, Xiufang; Liu, Aijuan
2018-02-01
Ischemic stroke is a leading cause of mortality and disability around the world. It is an important task to identify dysregulated pathways which infer molecular and functional insights existing in high-throughput experimental data. Gene expression profile of E-GEOD-16561 was collected. Pathways were obtained from the database of Kyoto Encyclopedia of Genes and Genomes and Retrieval of Interacting Genes was used to download protein-protein interaction sets. Attractor and crosstalk approaches were applied to screen dysregulated pathways. A total of 20 differentially expressed genes were identified in ischemic stroke. Thirty-nine significant differential pathways were identified according to Ppathways were identified with RPpathways were identified with impact factor >250. On the basis of the three criteria, 11 significant dysfunctional pathways were identified. Among them, Epstein-Barr virus infection was the most significant differential pathway. In conclusion, with the method based on attractor and crosstalk, significantly dysfunctional pathways were identified. These pathways are expected to provide molecular mechanism of ischemic stroke and represents a novel potential therapeutic target for ischemic stroke treatment.
Distortions in recall from visual memory: two classes of attractors at work.
Huang, Jie; Sekuler, Robert
2010-02-24
In a trio of experiments, a matching procedure generated direct, analogue measures of short-term memory for the spatial frequency of Gabor stimuli. Experiment 1 showed that when just a single Gabor was presented for study, a retention interval of just a few seconds was enough to increase the variability of matches, suggesting that noise in memory substantially exceeds that in vision. Experiment 2 revealed that when a pair of Gabors was presented on each trial, the remembered appearance of one of the Gabors was influenced by: (1) the relationship between its spatial frequency and the spatial frequency of the accompanying, task-irrelevant non-target stimulus; and (2) the average spatial frequency of Gabors seen on previous trials. These two influences, which work on very different time scales, were approximately additive in their effects, each operating as an attractor for remembered appearance. Experiment 3 showed that a timely pre-stimulus cue allowed selective attention to curtail the influence of a task-irrelevant non-target, without diminishing the impact of the stimuli seen on previous trials. It appears that these two separable attractors influence distinct processes, with perception being influenced by the non-target stimulus and memory being influenced by stimuli seen on previous trials.
Higher derivative corrections to BPS black hole attractors in 4d gauged supergravity
Energy Technology Data Exchange (ETDEWEB)
Hristov, Kiril [Institute for Nuclear Research and Nuclear Energy, Bulgarian Academy of Sciences, Tsarigradsko Chaussee 72, 1784 Sofia (Bulgaria); Katmadas, Stefanos [Dipartimento di Fisica, Università di Milano-Bicocca,I-20126 Milano (Italy); INFN, Sezione di Milano-Bicocca,I-20126 Milano (Italy); Lodato, Ivano [Department of Physics, IISER Pune,Homi Bhaba Road, Pashan, Pune (India)
2016-05-30
We analyze BPS black hole attractors in 4d gauged supergravity in the presence of higher derivative supersymmetric terms, including a Weyl-squared-type action, and determine the resulting corrections to the Bekenstein-Hawking entropy. The near-horizon geometry AdS{sub 2}×S{sup 2} (or other Riemann surface) preserves half of the supercharges in N=2 supergravity with Fayet-Iliopoulos gauging. We derive a relation between the entropy and the black hole charges that suggests via AdS/CFT how subleading corrections contribute to the supersymmetric index in the dual microscopic picture. Depending on the model, the attractors are part of full black hole solutions with different asymptotics, such as Minkowski, AdS{sub 4}, and hvLif{sub 4}. We give explicit examples for each of the asymptotic cases and comment on the implications. Among other results, we find that the Weyl-squared terms spoil the exact two-derivative relation to non-BPS asymptotically flat black holes in ungauged supergravity.
Senthilkumar, D V; Srinivasan, K; Thamilmaran, K; Lakshmanan, M
2008-12-01
We identify an unconventional route to the creation of a strange nonchaotic attractor (SNA) in a quasiperiodically forced electronic circuit with a nonsinusoidal (square wave) force as one of the quasiperiodic forces through numerical and experimental studies. We find that bubbles appear in the strands of the quasiperiodic attractor due to the instability induced by the additional square-wave-type force. The bubbles then enlarge and get increasingly wrinkled as a function of the control parameter. Finally, the bubbles get extremely wrinkled (while the remaining parts of the strands of the torus remain largely unaffected) resulting in the creation of the SNA; we term this the bubbling route to the SNA. We characterize and confirm this creation from both experimental and numerical data using maximal Lyapunov exponents and their variance, Poincaré maps, Fourier amplitude spectra, and spectral distribution functions. We also strongly confirm the creation of a SNA via the bubbling route by the distribution of the finite-time Lyapunov exponents.
The Kuramoto–Sivashinsky equation. A Local Attractor Filled with Unstable Periodic Solutions
Directory of Open Access Journals (Sweden)
Anatoli N. Kulikov
2018-01-01
Full Text Available A periodic boundary value problem is considered for one version of the KuramotoSivashinsky equation, which is widely known in mathematical physics. Local bifurcations in a neighborhood of the spatially homogeneous equilibrium points in the case when they change stability are studied. It is shown that the loss of stability of homogeneous equilibrium points leads to the appearance of a two-dimensional attractor on which all solutions are periodic functions of time, except one spatially inhomogeneous state. A spectrum of frequencies of the given family of periodic solutions fills the entire number line, and they are all unstable in a sense of Lyapunov definition in the metric of the phase space (space of initial conditions of the corresponding initial boundary value problem. It is chosen the Sobolev space as the phase space. For the periodic solutions which fill the two-dimensional attractor, the asymptotic formulas are given. In order to analyze the bifurcation problem it was used analysis methods for infinite-dimensional dynamical systems: the integral (invariant manifold method, the Poincare normal form theory, and asymptotic methods. The analysis of bifurcations for periodic boundary value problem was reduced to analysing the structure of the neighborhood of the zero solution of the homogeneous Dirichlet boundary value problem for the considered equation.
Enhancing neural-network performance via assortativity
International Nuclear Information System (INIS)
Franciscis, Sebastiano de; Johnson, Samuel; Torres, Joaquin J.
2011-01-01
The performance of attractor neural networks has been shown to depend crucially on the heterogeneity of the underlying topology. We take this analysis a step further by examining the effect of degree-degree correlations - assortativity - on neural-network behavior. We make use of a method recently put forward for studying correlated networks and dynamics thereon, both analytically and computationally, which is independent of how the topology may have evolved. We show how the robustness to noise is greatly enhanced in assortative (positively correlated) neural networks, especially if it is the hub neurons that store the information.
Neural network recognition of mammographic lesions
International Nuclear Information System (INIS)
Oldham, W.J.B.; Downes, P.T.; Hunter, V.
1987-01-01
A method for recognition of mammographic lesions through the use of neural networks is presented. Neural networks have exhibited the ability to learn the shape andinternal structure of patterns. Digitized mammograms containing circumscribed and stelate lesions were used to train a feedfoward synchronous neural network that self-organizes to stable attractor states. Encoding of data for submission to the network was accomplished by performing a fractal analysis of the digitized image. This results in scale invariant representation of the lesions. Results are discussed
Directory of Open Access Journals (Sweden)
H. Baars
2016-04-01
Full Text Available A global vertically resolved aerosol data set covering more than 10 years of observations at more than 20 measurement sites distributed from 63° N to 52° S and 72° W to 124° E has been achieved within the Raman and polarization lidar network PollyNET. This network consists of portable, remote-controlled multiwavelength-polarization-Raman lidars (Polly for automated and continuous 24/7 observations of clouds and aerosols. PollyNET is an independent, voluntary, and scientific network. All Polly lidars feature a standardized instrument design with different capabilities ranging from single wavelength to multiwavelength systems, and now apply unified calibration, quality control, and data analysis. The observations are processed in near-real time without manual intervention, and are presented online at http://polly.tropos.de/. The paper gives an overview of the observations on four continents and two research vessels obtained with eight Polly systems. The specific aerosol types at these locations (mineral dust, smoke, dust-smoke and other dusty mixtures, urban haze, and volcanic ash are identified by their Ångström exponent, lidar ratio, and depolarization ratio. The vertical aerosol distribution at the PollyNET locations is discussed on the basis of more than 55 000 automatically retrieved 30 min particle backscatter coefficient profiles at 532 nm as this operating wavelength is available for all Polly lidar systems. A seasonal analysis of measurements at selected sites revealed typical and extraordinary aerosol conditions as well as seasonal differences. These studies show the potential of PollyNET to support the establishment of a global aerosol climatology that covers the entire troposphere.
Didier, Caroline; Forno, Guillermina; Etcheverrigaray, Marina; Kratje, Ricardo; Goicoechea, Héctor
2009-09-21
The optimal blends of six compounds that should be present in culture media used in recombinant protein production were determined by means of artificial neural networks (ANN) coupled with crossed mixture experimental design. This combination constitutes a novel approach to develop a medium for cultivating genetically engineered mammalian cells. The compounds were collected in two mixtures of three elements each, and the experimental space was determined by a crossed mixture design. Empirical data from 51 experimental units were used in a multiresponse analysis to train artificial neural networks which satisfy different requirements, in order to define two new culture media (Medium 1 and Medium 2) to be used in a continuous biopharmaceutical production process. These media were tested in a bioreactor to produce a recombinant protein in CHO cells. Remarkably, for both predicted media all responses satisfied the predefined goals pursued during the analysis, except in the case of the specific growth rate (mu) observed for Medium 1. ANN analysis proved to be a suitable methodology to be used when dealing with complex experimental designs, as frequently occurs in the optimization of production processes in the biotechnology area. The present work is a new example of the use of ANN for the resolution of a complex, real life system, successfully employed in the context of a biopharmaceutical production process.
Bifurcation and category learning in network models of oscillating cortex
Baird, Bill
1990-06-01
A genetic model of oscillating cortex, which assumes “minimal” coupling justified by known anatomy, is shown to function as an associative memory, using previously developed theory. The network has explicit excitatory neurons with local inhibitory interneuron feedback that forms a set of nonlinear oscillators coupled only by long-range excitatory connections. Using a local Hebb-like learning rule for primary and higher-order synapses at the ends of the long-range connections, the system learns to store the kinds of oscillation amplitude patterns observed in olfactory and visual cortex. In olfaction, these patterns “emerge” during respiration by a pattern forming phase transition which we characterize in the model as a multiple Hopf bifurcation. We argue that these bifurcations play an important role in the operation of real digital computers and neural networks, and we use bifurcation theory to derive learning rules which analytically guarantee CAM storage of continuous periodic sequences-capacity: N/2 Fourier components for an N-node network-no “spurious” attractors.
Fine-tuning and the stability of recurrent neural networks.
Directory of Open Access Journals (Sweden)
David MacNeil
Full Text Available A central criticism of standard theoretical approaches to constructing stable, recurrent model networks is that the synaptic connection weights need to be finely-tuned. This criticism is severe because proposed rules for learning these weights have been shown to have various limitations to their biological plausibility. Hence it is unlikely that such rules are used to continuously fine-tune the network in vivo. We describe a learning rule that is able to tune synaptic weights in a biologically plausible manner. We demonstrate and test this rule in the context of the oculomotor integrator, showing that only known neural signals are needed to tune the weights. We demonstrate that the rule appropriately accounts for a wide variety of experimental results, and is robust under several kinds of perturbation. Furthermore, we show that the rule is able to achieve stability as good as or better than that provided by the linearly optimal weights often used in recurrent models of the integrator. Finally, we discuss how this rule can be generalized to tune a wide variety of recurrent attractor networks, such as those found in head direction and path integration systems, suggesting that it may be used to tune a wide variety of stable neural systems.
Attractive target wave patterns in complex networks consisting of excitable nodes
International Nuclear Information System (INIS)
Zhang Li-Sheng; Mi Yuan-Yuan; Liao Xu-Hong; Qian Yu; Hu Gang
2014-01-01
This review describes the investigations of oscillatory complex networks consisting of excitable nodes, focusing on the target wave patterns or say the target wave attractors. A method of dominant phase advanced driving (DPAD) is introduced to reveal the dynamic structures in the networks supporting oscillations, such as the oscillation sources and the main excitation propagation paths from the sources to the whole networks. The target center nodes and their drivers are regarded as the key nodes which can completely determine the corresponding target wave patterns. Therefore, the center (say node A) and its driver (say node B) of a target wave can be used as a label, (A,B), of the given target pattern. The label can give a clue to conveniently retrieve, suppress, and control the target waves. Statistical investigations, both theoretically from the label analysis and numerically from direct simulations of network dynamics, show that there exist huge numbers of target wave attractors in excitable complex networks if the system size is large, and all these attractors can be labeled and easily controlled based on the information given by the labels. The possible applications of the physical ideas and the mathematical methods about multiplicity and labelability of attractors to memory problems of neural networks are briefly discussed. (topical review - statistical physics and complex systems)