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Weakly Connected Neural Networks / by Frank C. Hoppensteadt, Eugene M. Izhikevich
(Applied Mathematical Sciences ; 126)

データ種別 電子ブック
出版者 New York, NY : Springer New York : Imprint: Springer
出版年 1997
本文言語 英語
大きさ XVI, 402 p : online resource

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EB0066198

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内容注記 1 Introduction
2 Bifurcations in Neuron Dynamics
3 Neural Networks
4 Introduction to Canonical Models
5 Local Analysis of WCNNs
6 Local Analysis of Singularly Perturbed WCNNs
7 Local Analysis of Weakly Connected Maps
8 Saddle-Node on a Limit Cycle
9 Weakly Connected Oscillators
10 Multiple Andronov-Hopf Bifurcation
11 Multiple Cusp Bifurcation
12 Quasi-Static Bifurcations
13 Synaptic Organizations of the Brain
References
一般注記 This book is devoted to an analysis of general weakly connected neural networks (WCNNs) that can be written in the form (0.1) m Here, each Xi E IR is a vector that summarizes all physiological attributes of the ith neuron, n is the number of neurons, Ii describes the dynam­ ics of the ith neuron, and gi describes the interactions between neurons. The small parameter € indicates the strength of connections between the neurons. Weakly connected systems have attracted much attention since the sec­ ond half of seventeenth century, when Christian Huygens noticed that a pair of pendulum clocks synchronize when they are attached to a light­ weight beam instead of a wall. The pair of clocks is among the first weakly connected systems to have been studied. Systems of the form (0.1) arise in formal perturbation theories developed by Poincare, Liapunov and Malkin, and in averaging theories developed by Bogoliubov and Mitropolsky
著者標目 *Hoppensteadt, Frank C. author
Izhikevich, Eugene M. author
SpringerLink (Online service)
件 名 LCSH:Mathematics
LCSH:Neurosciences
LCSH:Mathematical analysis
LCSH:Analysis (Mathematics)
LCSH:Biomathematics
FREE:Mathematics
FREE:Analysis
FREE:Mathematical and Computational Biology
FREE:Neurosciences
分 類 DC23:515
巻冊次 ISBN:9781461218289 REFWLINK
ISBN 9781461218289
URL http://dx.doi.org/10.1007/978-1-4612-1828-9
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