| 书目名称 | Weakly Connected Neural Networks |
| 编辑 | Frank C. Hoppensteadt,Eugene M. Izhikevich |
| 视频video | |
| 概述 | Recent studies of bifurcations have inspired a new approach to brain modelling * Shows how some synaptic organisations have especially rich dynamic behaviour *.Hoppensteadt is a well-known author |
| 丛书名称 | Applied Mathematical Sciences |
| 图书封面 |  |
| 描述 | 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. |
| 出版日期 | Book 1997 |
| 关键词 | biology; calculus; differential equation; neural network; neurons; neuroscience |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-1-4612-1828-9 |
| isbn_softcover | 978-1-4612-7302-8 |
| isbn_ebook | 978-1-4612-1828-9Series ISSN 0066-5452 Series E-ISSN 2196-968X |
| issn_series | 0066-5452 |
| copyright | Springer Science+Business Media New York 1997 |
发表于 2025-3-21 17:20:18
