Titlebook: Complex Systems; Eric Goles,Servet Martínez Book 2001 Springer Science+Business Media Dordrecht 2001 Chaos.Markov.algorithm.algorithms.aut

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书目名称Complex Systems影响因子(影响力)




书目名称Complex Systems影响因子(影响力)学科排名




书目名称Complex Systems网络公开度




书目名称Complex Systems网络公开度学科排名




书目名称Complex Systems被引频次




书目名称Complex Systems被引频次学科排名




书目名称Complex Systems年度引用




书目名称Complex Systems年度引用学科排名




书目名称Complex Systems读者反馈




书目名称Complex Systems读者反馈学科排名

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Lyapunov Exponents and Synchronization of Cellular Automata,th an introduction to CA, introduce the concept of Boolean derivative and show that any CA has a finite expansion in terms of the Boolean derivatives. The Lyapunov exponents are defined as the rate of exponential growth of the linear part of this expansion using a suitable norm. We then present a si

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Why Kolmogorov Complexity?,ility? Is it possible to partition the set of infinite binary strings into two subsets, namely, the subset of random strings and the other of non-random ones? The goal of this paper is to present the answers to the above questions which are provided by the Kolmogorov theory. The basic preliminaries

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Cutoff for Markov Chains: Some Examples and Applications,quilibrium measure is close to 1 until some deterministic ‘cutoff time’, and close to 0 shortly after. Many examples have been studied by Diaconis and his followers. Our goal is to introduce two families of examples of this phenomenon, focusing mainly on their possible applications. We present first

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Book 2001anco Bagnoli and Raul Rechtman establishes relations be­ tween Lyapunov exponents and synchronization processes in cellular automata. The principal goal is to associate tools, usually used in physical problems, to an important problem in cellularautomata and computer science, the synchronization pro

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1386-288X incipal goal is to associate tools, usually used in physical problems, to an important problem in cellularautomata and computer science, the synchronization pro978-94-010-3817-1978-94-010-0920-1Series ISSN 1386-288X

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Dynamical Systems and Biological Regulations,tion in neuromodelling. We consider after the case of a universal minimal regulatory system (called a regulon), having a positive and a negative circuit in its interaction matrix, and we recall the main results related to the presence of such circuits. Finally, we give two examples of application of