Neural Networks and Analog Computation - Beyond the Turing Limit (Paperback, Softcover reprint of the original 1st ed. 1999)

The theoretical foundations of Neural Networks and Analog Computation conceptualize neural networks as a particular type of computer consisting of multiple assemblies of basic processors interconnected in an intricate structure. Examining these networks under various resource constraints reveals a continuum of computational devices, several of which coincide with well-known classical models. On a mathematical level, the treatment of neural computations enriches the theory of computation but also explicated the computational complexity associated with biological networks, adaptive engineering tools, and related models from the fields of control theory and nonlinear dynamics. The material in this book will be of interest to researchers in a variety of engineering and applied sciences disciplines. In addition, the work may provide the base of a graduate-level seminar in neural networks for computer science students.

General

Imprint:	Springer-Verlag New York
Country of origin:	United States
Series:	Progress in Theoretical Computer Science
Release date:	October 2012
First published:	1999
Authors:	Hava T. Siegelmann
Dimensions:	235 x 155 x 11mm (L x W x T)
Format:	Paperback
Pages:	181
Edition:	Softcover reprint of the original 1st ed. 1999
ISBN-13:	978-1-4612-6875-8
Categories:	Books > Computing & IT > General theory of computing > Mathematical theory of computation Books > Science & Mathematics > Mathematics > Applied mathematics > Mathematics for scientists & engineers Books > Science & Mathematics > Physics > Thermodynamics & statistical physics > Statistical physics Books > Computing & IT > Applications of computing > Artificial intelligence > General Promotions
LSN:	1-4612-6875-3
Barcode:	9781461268758

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