Weakly Connected Neural Networks (Paperback, Softcover reprint of the original 1st ed. 1997)

Devoted to local and global analysis of weakly connected systems with applications to neurosciences, this book uses bifurcation theory and canonical models as the major tools of analysis. It presents a systematic and well motivated development of both weakly connected system theory and mathematical neuroscience, addressing bifurcations in neuron and brain dynamics, synaptic organisations of the brain, and the nature of neural codes. The authors present classical results together with the most recent developments in the field, making this a useful reference for researchers and graduate students in various branches of mathematical neuroscience.

General

Imprint:	Springer-Verlag New York
Country of origin:	United States
Series:	Applied Mathematical Sciences, 126
Release date:	December 2012
First published:	1997
Authors:	Frank C. Hoppensteadt • Eugene M. Izhikevich
Dimensions:	235 x 155 x 21mm (L x W x T)
Format:	Paperback
Pages:	402
Edition:	Softcover reprint of the original 1st ed. 1997
ISBN-13:	978-1-4612-7302-8
Categories:	Books > Science & Mathematics > Mathematics > Calculus & mathematical analysis > Vector & tensor analysis Books > Science & Mathematics > Mathematics > Applied mathematics > Mathematics for scientists & engineers Books > Science & Mathematics > Biology, life sciences > Life sciences: general issues > Neurosciences
LSN:	1-4612-7302-1
Barcode:	9781461273028

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