14 research outputs found

    Synchronization of unidirectional time delay chaotic networks and the greatest common divisor

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    We present the interplay between synchronization of unidirectional coupled chaotic nodes with heterogeneous delays and the greatest common divisor (GCD) of loops composing the oriented graph. In the weak chaos region and for GCD=1 the network is in chaotic zero-lag synchronization, whereas for GCD=m>1 synchronization of m-sublattices emerges. Complete synchronization can be achieved when all chaotic nodes are influenced by an identical set of delays and in particular for the limiting case of homogeneous delays. Results are supported by simulations of chaotic systems, self-consistent and mixing arguments, as well as analytical solutions of Bernoulli maps.Comment: 7 pages, 5 figure

    Nonlocal mechanism for cluster synchronization in neural circuits

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    The interplay between the topology of cortical circuits and synchronized activity modes in distinct cortical areas is a key enigma in neuroscience. We present a new nonlocal mechanism governing the periodic activity mode: the greatest common divisor (GCD) of network loops. For a stimulus to one node, the network splits into GCD-clusters in which cluster neurons are in zero-lag synchronization. For complex external stimuli, the number of clusters can be any common divisor. The synchronized mode and the transients to synchronization pinpoint the type of external stimuli. The findings, supported by an information mixing argument and simulations of Hodgkin Huxley population dynamic networks with unidirectional connectivity and synaptic noise, call for reexamining sources of correlated activity in cortex and shorter information processing time scales.Comment: 8 pges, 6 figure

    Coexistence of exponentially many chaotic spin-glass attractors

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    A chaotic network of size NN with delayed interactions which resembles a pseudo-inverse associative memory neural network is investigated. For a load α=P/N<1\alpha=P/N<1, where PP stands for the number of stored patterns, the chaotic network functions as an associative memory of 2P attractors with macroscopic basin of attractions which decrease with α\alpha. At finite α\alpha, a chaotic spin glass phase exists, where the number of distinct chaotic attractors scales exponentially with NN. Each attractor is characterized by a coexistence of chaotic behavior and freezing of each one of the NN chaotic units or freezing with respect to the PP patterns. Results are supported by large scale simulations of networks composed of Bernoulli map units and Mackey-Glass time delay differential equations.Comment: 6 pages and 5 figure

    Heterogeneous Delays in Neural Networks

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    We investigate heterogeneous coupling delays in complex networks of excitable elements described by the FitzHugh-Nagumo model. The effects of discrete as well as of uni- and bimodal continuous distributions are studied with a focus on different topologies, i.e., regular, small-world, and random networks. In the case of two discrete delay times resonance effects play a major role: Depending on the ratio of the delay times, various characteristic spiking scenarios, such as coherent or asynchronous spiking, arise. For continuous delay distributions different dynamical patterns emerge depending on the width of the distribution. For small distribution widths, we find highly synchronized spiking, while for intermediate widths only spiking with low degree of synchrony persists, which is associated with traveling disruptions, partial amplitude death, or subnetwork synchronization, depending sensitively on the network topology. If the inhomogeneity of the coupling delays becomes too large, global amplitude death is induced

    Zero-lag synchronization of chaotic units with time-delayed couplings

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    Zero-lag synchronization (ZLS) is achieved in a very restricted mutually coupled chaotic systems, where the delays of the self-coupling and the mutual coupling are identical or fulfil some restricted ratios. Using a set of multiple self-feedbacks and mutual couplings we demonstrate both analytically and numerically that ZLS is achieved for a wide range of mutual delays. It indicates that ZLS can be achieved without the knowledge of the mutual distance between the communicating partners and has an important implication in the possible use of ZLS in communications networks as well as in the understanding of the emergence of such synchronization in the neuronal activities

    Synchronization of Time-Delay Chaotic System in Presence of Noise

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    Chaotic synchronization, as a key technique of chaotic secure communication, has received much attention in recent years. This paper proposes a nonlinear synchronization scheme for the time-delay chaotic system in the presence of noise. In this scheme, an integrator is introduced to suppress the influence of channel noise in the synchronization process. The experimental results demonstrate the effectiveness and feasibility of the proposed scheme which is strongly robust against noises, especially the high-frequency noises
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