Overview
Suitable for researchers engaged with neural networks and dynamical systems theory
Introduces advanced models of neural networks
Includes several chapters suitable for related postgraduate courses in engineering, computer science, mathematics, physics and biology
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Table of contents (13 chapters)
Keywords
About this book
This book provides a complete study on neural structures exhibiting nonlinear and stochastic dynamics, elaborating on neural dynamics by introducing advanced models of neural networks. It overviews the main findings in the modelling of neural dynamics in terms of electrical circuits and examines their stability properties with the use of dynamical systems theory.
It is suitable for researchers and postgraduate students engaged with neural networks and dynamical systems theory.
Authors and Affiliations
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Bibliographic Information
Book Title: Advanced Models of Neural Networks
Book Subtitle: Nonlinear Dynamics and Stochasticity in Biological Neurons
Authors: Gerasimos G. Rigatos
DOI: https://doi.org/10.1007/978-3-662-43764-3
Publisher: Springer Berlin, Heidelberg
eBook Packages: Engineering, Engineering (R0)
Copyright Information: Springer-Verlag Berlin Heidelberg 2015
Hardcover ISBN: 978-3-662-43763-6Published: 09 September 2014
Softcover ISBN: 978-3-662-51557-0Published: 23 August 2016
eBook ISBN: 978-3-662-43764-3Published: 27 August 2014
Edition Number: 1
Number of Pages: XXIII, 275
Number of Illustrations: 44 b/w illustrations, 91 illustrations in colour