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    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Weakly Connected Neural Networks

Weakly Connected Neural Networks

Hoppensteadt, Frank C.
Izhikevich, Eugene M.

Paperback

Series: Applied Mathematical Sciences, Book 126

General ComputersGeneral EducationNetworking

ISBN10: 1461273021
ISBN13: 9781461273028
Publisher: Springer Nature
Published: Sep 30 2012
Pages: 402
Weight: 1.30
Height: 0.86 Width: 6.14 Depth: 9.21
Language: English
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.

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