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We introduce and study systems of randomly coupled maps (RCM) where the relevant parameter is the degree of connectivity in the system. Global (almost-) synchronized states are found (equivalent to the synchronization observed in globally…

Condensed Matter · Physics 2009-10-31 Susanna C. Manrubia , Alexander S. Mikhailov

We use a generic model for type-I excitability (known as the SNIPER or SNIC model) to describe the local dynamics of nodes within a network in the presence of non-zero coupling delays. Utilising the method of the Master Stability Function,…

Disordered Systems and Neural Networks · Physics 2016-08-10 Andrew Keane , Thomas Dahms , Judith Lehnert , Sachin Aralasurali Suryanarayana , Philipp Hövel , Eckehard Schöll

Two-dimensional mappings obtained by coupling two piecewise increasing expanding maps are considered. Their dynamics is described when the coupling parameter increases in the expanding domain. By introducing a coding and by analysing an…

Chaotic Dynamics · Physics 2007-05-23 Bastien Fernandez , Pierre Guiraud

In this paper we address a series of open questions about the construction of spatially coupled measurement matrices in compressed sensing. For hardware implementations one is forced to depart from the limiting regime of parameters in which…

Information Theory · Computer Science 2014-01-27 Francesco Caltagirone , Lenka Zdeborová

We analyze the properties of order parameters measuring synchronization and phase locking in complex oscillator networks. First, we review network order parameters previously introduced and reveal several shortcomings: none of the…

Adaptation and Self-Organizing Systems · Physics 2017-09-15 Malte Schröder , Marc Timme , Dirk Witthaut

We consider multimodal C^3 interval maps f satisfying a summability condition on the derivatives D_n along the critical orbits which implies the existence of an absolutely continuous f -invariant probability measure mu. If f is…

Dynamical Systems · Mathematics 2007-05-23 Henk Bruin , Stefano Luzzatto , Sebastian van Strien

Using a perturbative expansion for weak synaptic weights and weak sources of randomness, we calculate the correlation structure of neural networks with generic connectivity matrices. In detail, the perturbative parameters are the mean and…

Neurons and Cognition · Quantitative Biology 2013-07-11 D. Fasoli , O. Faugeras

This study investigates the suitability of the annealed approximation in high-dimensional systems characterized by dense networks with quenched link disorder, employing models of coupled oscillators. We demonstrate that dynamic equations…

Statistical Mechanics · Physics 2024-03-25 Jaegon Um , Hyunsuk Hong , Hyunggyu Park

We study a network of coupled logistic maps whose interactions occur with a certain distribution of delay times. The local dynamics is chaotic in the absence of coupling and thus the network is a paradigm of a complex system. There are two…

Chaotic Dynamics · Physics 2009-02-03 Marcelo Ponce , C. Masoller , Arturo C. Marti

The effects of nonlocal and reflecting connectivities have been previously investigated in coupled Leaky Integrate-and-Fire (LIF) elements, which assimilate the exchange of electrical signals between neurons. In this work we investigate the…

Pattern Formation and Solitons · Physics 2018-10-16 N. D. Tsigkri-DeSmedt , I. Koulierakis , G. Karakos , A. Provata

The phase ordering dynamics of coupled chaotic maps on fractal networks are investigated. The statistical properties of the systems are characterized by means of the persistence probability of equivalent spin variables that define the…

Chaotic Dynamics · Physics 2007-05-23 K. Tucci , M. G. Cosenza , O. Alvarez-Llamoza

The parallel dynamics of extremely diluted symmetric Q-Ising neural networks is studied for arbitrary Q using a probabilistic approach. In spite of the extremely diluted architecture the feedback correlations arising from the symmetry…

Disordered Systems and Neural Networks · Physics 2015-06-25 D. Bolle , G. Jongen , G. M. Shim

We consider a pair of collectively oscillating networks of dynamical elements and optimize their internetwork coupling for efficient mutual synchronization based on the phase reduction theory developed in Ref. [H. Nakao, S. Yasui, M. Ota,…

Adaptation and Self-Organizing Systems · Physics 2021-06-11 Hiroya Nakao , Katsunori Yamaguchi , Shingo Katayama , Tatsuo Yanagita

We consider pulse-coupled Leaky Integrate-and-Fire neural networks with randomly distributed synaptic couplings. This random dilution induces fluctuations in the evolution of the macroscopic variables and deterministic chaos at the…

Chaotic Dynamics · Physics 2015-04-14 D. Angulo-Garcia , A. Torcini

The parallel dynamics of the asymmetric extremely diluted Ashkin-Teller neural network is studied using signal-to-noise analysis techniques. Evolution equations for the order parameters are derived, both at zero and finite temperature. The…

Disordered Systems and Neural Networks · Physics 2015-06-25 D. Bolle' , G. Jongen

We investigate collective synchronization in a system of coupled oscillators on small-world networks. The order parameters which measure synchronization of phases and frequencies are introduced and analyzed by means of dynamic simulations…

Disordered Systems and Neural Networks · Physics 2009-11-07 H. Hong , M. Y. Choi , Beom Jun Kim

In a recent work, mean-field analysis and computer simulations were employed to analyze critical self-organization in networks of excitable cellular automata where randomly chosen synapses in the network were depressed after each spike (the…

Adaptation and Self-Organizing Systems · Physics 2017-04-19 João Guilherme Ferreira Campos , Ariadne de Andrade Costa , Mauro Copelli , Osame Kinouchi

We investigate the synaptic noise as a novel mechanism for creating critical avalanches in the activity of neural networks. We model neurons and chemical synapses by dynamical maps with a uniform noise term in the synaptic coupling. An…

Disordered Systems and Neural Networks · Physics 2015-10-07 Mauricio Girardi-Schappo , Osame Kinouchi , Marcelo H. R. Tragtenberg

The thermodynamic and retrieval properties of the Blume-Emery-Griffiths neural network with synchronous updating and variable dilution are studied using replica mean-field theory. Several forms of dilution are allowed by pruning the…

Disordered Systems and Neural Networks · Physics 2007-05-23 D. Bollé , J. Busquets Blanco

We investigate the optimization of synchronizability in multiplex networks and demonstrate that the interlayer coupling strength is the deciding factor for the efficiency of optimization. The optimized networks have homogeneity in the…

Physics and Society · Physics 2016-02-26 Sanjiv K. Dwivedi , Camellia Sarkar , Sarika Jalan
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