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The paper examines the discrete-time dynamics of neuron models (of excitatory and inhibitory types) with piecewise linear activation functions, which are connected in a network. The properties of a pair of neurons (one excitatory and the…

chao-dyn · 物理学 2007-05-23 Sitabhra Sinha

We study emergent oscillatory behavior in networks of diffusively coupled nonlinear ordinary differential equations. Starting from a situation where each isolated node possesses a globally attracting equilibrium point, we give, for an…

动力系统 · 数学 2023-08-22 Eddie Nijholt , Tiago Pereira , Fernando C. Queiroz , Dmitry Turaev

The dynamics of an extremely diluted neural network with high order synapses acting as corrections to the Hopfield model is investigated. As in the fully connected case, the high order terms may strongly improve the storage capacity of the…

凝聚态物理 · 物理学 2009-10-22 N. Lemke , J. J. Arenzon , F. A. Tamarit

Chaotic functions are characterized by sensitivity to initial conditions, transitivity, and regularity. Providing new functions with such properties is a real challenge. This work shows that one can associate with any Boolean network a…

离散数学 · 计算机科学 2011-12-08 J. M. Bahi , J. -F. Couchot , C. Guyeux , A. Richard

Key features of biological activity can often be captured by transitions between a finite number of semi-stable states that correspond to behaviors or decisions. We present here a broad class of dynamical systems that are ideal for modeling…

动力系统 · 数学 2022-12-14 Megan Morrison , Lai-Sang Young

We adapt the bialgebra and Hopf relations to expose internal structure in the ground state of a Hamiltonian with $Z_2$ topological order. Its tensor network description allows for exact contraction through simple diagrammatic rewrite rules.…

量子物理 · 物理学 2011-12-08 S. J. Denny , J. D. Biamonte , D. Jaksch , S. R. Clark

We propose a discrete time dynamical system (a map) as phenomenological model of excitable and spiking-bursting neurons. The model is a discontinuous two-dimensional map. We find condition under which this map has an invariant region on the…

神经元与认知 · 定量生物学 2009-11-13 Maurice Courbage , V. I. Nekorkin , L. V. Vdovin

The influence of networks topology on collective properties of dynamical systems defined upon it is studied in the thermodynamic limit. A network model construction scheme is proposed where the number of links, the average eccentricity and…

物理与社会 · 物理学 2015-05-25 Sarah De Nigris , Xavier Leoncini

In this paper, a novel formulation of discrete chaotic iterations in the field of dynamical systems is given. Their topological properties are studied: it is mathematically proved that, under some conditions, these iterations have a chaotic…

密码学与安全 · 计算机科学 2017-02-09 Jacques M. Bahi , Christophe Guyeux

In neural circuits, statistical connectivity rules strongly depend on neuronal type. Here we study dynamics of neural networks with cell-type specific connectivity by extending the dynamic mean field method, and find that these networks…

神经元与认知 · 定量生物学 2015-02-24 Johnatan Aljadeff , Merav Stern , Tatyana O. Sharpee

We study collective dynamics of complex networks of stochastic excitable elements, active rotators. In the thermodynamic limit of infinite number of elements, we apply a mean-field theory for the network and then use a Gaussian…

混沌动力学 · 物理学 2013-11-19 Bernard Sonnenschein , Michael A. Zaks , Alexander B. Neiman , Lutz Schimansky-Geier

We set up a signal-driven scheme of the chaotic neural network with the coupling constants corresponding to certain information, and investigate the stochastic resonance-like effects under its deterministic dynamics, comparing with the…

混沌动力学 · 物理学 2007-05-23 Haruhiko Nishimura , Naofumi Katada , Kazuyuki Aihara

Chaotic dynamics have emerged as a versatile resource for neuromorphic and probabilistic computing, enabling high-dimensional nonlinear processing and classical analogues of quantum randomness. Exploiting chaos for computation requires…

混沌动力学 · 物理学 2026-05-20 Jungyoon Kim , Kyuho Kim , Kunwoo Park , Namkyoo Park , Sunkyu Yu

An abstract network approach is proposed for the description of the dynamics in reactive processes. The phase space of the variables (concentrations in reactive systems) is partitioned into a finite number of segments, which constitute the…

统计力学 · 物理学 2015-06-17 A. Provata , E. Panagakou

We study a deterministic dynamics with two time scales in a continuous state attractor network. To the usual (fast) relaxation dynamics towards point attractors (``patterns'') we add a slow coupling dynamics that makes the visited patterns…

神经元与认知 · 定量生物学 2010-06-10 Juliana R. Dias , Rodrigo F. Oliveira , Osame Kinouchi

We study the effect of varying wiring in excitable random networks in which connection weights change with activity to mold local resistance or facilitation due to fatigue. Dynamic attractors, corresponding to patterns of activity, are then…

无序系统与神经网络 · 物理学 2009-05-22 Samuel Johnson , J. Marro , Joaquin J. Torres

The modern Hopfield network, proposed by Krotov and Hopfield, is a mathematical generalization of the Hopfield network, which is a basic model of associative memory that employs higher-order interactions. This study introduces an open…

量子物理 · 物理学 2025-08-21 Takeshi Kimura , Kohtaro Kato

We prove that a topologically generic network (an open and dense set of networks) of three or more inhibitory neurons have periodic behavior with a finite number of limit cycles that persist under small perturbations of the structure of the…

动力系统 · 数学 2011-01-12 E. Catsigeras , A. Rovella , R. Budelli

As a generalization of integer-order calculus, fractional calculus has seen tremendous applications in the past few years especially in the description of anomalous viscoelastic properties, transport processes in complex media as well as in…

应用物理 · 物理学 2025-02-06 Anis Allagui , Ahmed S. Elwakil

When implemented in the digital domain with time, space and value discretized in the binary form, many good dynamical properties of chaotic systems in continuous domain may be degraded or even diminish. To measure the dynamic complexity of…

混沌动力学 · 物理学 2019-05-08 Chengqing Li , Jinhu Lu , Guanrong Chen
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