Weakly Connected Neural Networks (Hardcover, 1997 ed.)

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:	July 1997
First published:	1997
Authors:	Frank C. Hoppensteadt • Eugene M. Izhikevich
Dimensions:	235 x 155 x 31mm (L x W x T)
Format:	Hardcover
Pages:	402
Edition:	1997 ed.
ISBN-13:	978-0-387-94948-2
Categories:	Books > Science & Mathematics > Mathematics > Applied mathematics > Mathematics for scientists & engineers Books > Science & Mathematics > Biology, life sciences > Life sciences: general issues > Neurosciences
LSN:	0-387-94948-8
Barcode:	9780387949482

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