Weakly Connected Neural Networks

Author: Hagendorf, Col
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BISAC Categories:
Data Science | Neural Networks |
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.

Publisher Name Springer
Author Name Hagendorf, Col
Format Audio
Bisac Subject Major COM
Language NG
Isbn 10 0387949488
Isbn 13 9780387949482
Target Age Group min:NA, max:NA
Series 000478382126
Dimensions 00.95" H x 00.06" L x 34.00" W
Page Count 402

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