
Cellular Automata, Dynamical Systems and Neural Networks
Kluwer Academic Publishers
Published on 31. March 1994
Book
Hardback
VIII, 192 pages
978-0-7923-2772-1 (ISBN)
Description
This book contains the courses given at the Third School on Statistical Physics and Cooperative Systems held at Santiago, Chile, from 14th to 18th December 1992. The main idea of this periodic school was to bring together scientists work with recent trends in Statistical Physics. More precisely ing on subjects related related with non linear phenomena, dynamical systems, ergodic theory, cellular au tomata, symbolic dynamics, large deviation theory and neural networks. Scientists working in these subjects come from several areas: mathematics, biology, physics, computer science, electrical engineering and artificial intelligence. Recently, a very important cross-fertilization has taken place with regard to the aforesaid scientific and technological disciplines, so as to give a new approach to the research whose common core remains in statistical physics. Each contribution is devoted to one or more of the previous subjects. In most cases they are structured as surveys, presenting at the same time an original point of view about the topic and showing mostly new results. The expository text of Fran
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Series
Edition
1994 ed.
Language
English
Place of publication
Dordrecht
Netherlands
Target group
Professional and scholarly
Research
Illustrations
VIII, 192 p.
Dimensions
Height: 241 mm
Width: 160 mm
Thickness: 17 mm
Weight
477 gr
ISBN-13
978-0-7923-2772-1 (9780792327721)
DOI
10.1007/978-94-017-1005-3
Schweitzer Classification
Other editions
Additional editions

E. Goles | Servet Martínez
Cellular Automata, Dynamical Systems and Neural Networks
Book
12/2010
Springer
€106.99
Shipment within 15-20 days
Content
Cellular Automata and Transducers. A Topological View.- Automata Network Models of Interacting Populations.- Entropy, Pressure and Large Deviation.- Formal Neural Networks: from Supervised to Unsupervised Learning.- Storage of Correlated Patterns in Neural Networks.