Introduction To The Theory Of Neural Computation

John A. Hertz, Anders S. Krogh, Richard G. Palmer

$284

Hardback

Not in-store but you can order this
How long will it take?

Availability Information

We source books from suppliers in Australia and overseas. For books we don't currently have in stock, the time it takes to get them from our suppliers can vary widely - from a few days to a few months - so we check each book with each supplier to determine the expected time it will take to be supplied to us.

We then advise you accordingly. If the time taken to get any book is too long for you, you can let us know and we will cancel or adjust your order, and refund as required.

To find out the anticipated arrival time for specific items prior to ordering, please contact us by phone or email:

Phone +61 2 9264 3111, or 1800 4 BOOKS (1800 4 26657) if outside Sydney:
option 1 Abbey's Bookshop (Crime, History, Science, Kids & more) • info@abbeys.com.au
option 2 Language Book Centre (ESL & Foreign Languages) • language@abbeys.com.au
option 3 Galaxy Bookshop (Sci-fi, Fantasy, Romance, Graphic Novels) • sf@galaxybooks.com.au

QTY:

English

CRC Press
13 June 2019

Physics; Life sciences: general issues

Comprehensive introduction to the neural network models currently under intensive study for computational applications. It also provides coverage of neural network applications in a variety of problems of both theoretical and practical interest.

By: John A. Hertz, Anders S. Krogh, Richard G. Palmer
Imprint: CRC Press
Country of Publication: United Kingdom
Dimensions: Height: 229mm, Width: 152mm,
Weight: 453g
ISBN: 9780367091361
ISBN 10: 0367091364
Pages: 352
Publication Date: 13 June 2019
Audience: College/higher education , General/trade , Primary , ELT Advanced
Format: Hardback
Publisher's Status: Active

About the Santa Fe Institute , Santa Fe Institute Editorial Board September 1990 , Santa Fe Institute Studies in the Sciences of Complexity , Series Foreword , Foreword , Foreword , Preface , Introduction , The Hopfield Model , Extensions of the Hopfield Model , Optimization Problems , Simple Perceptrons , Multi-Layer Networks , Recurrent Networks , Unsupervised Hebbian Learning , Unsupervised Competitive Learning , Formal Statistical Mechanics of Neural Networks , Statistical Mechanics

John A Hertz