
Statistical Physics, Automata Networks and Dynamical Systems
Springer (Publisher)
Published on 23. October 2012
Book
Paperback/Softback
X, 207 pages
978-94-010-5137-8 (ISBN)
Description
One service mathematics has rendered the ~Et moi, ...si j'avait su comment en revenir, je human race. It has put common sense back n'y serais point aile.' where it belongs, on the topmost shelf next to Jules Verne the dusty canister labelled 'discarded nonsense'. Eric T. Bell The series is divergent; therefore we may be able to do something with it. O. Heaviside Mathematics is a tool for thought. A highly necessary tool in a world where both feedback and nonlineari- ties abound. Similarly, all kinds of parts of mathematics serve as tools for other parts and for other sci- ences. Applying a simple rewriting rule to the quote on the right above one finds such statements as: 'One ser- vice topology has rendered mathematical physics ...'; 'One service logic has rendered computer science ...'; 'One service category theory has rendered mathematics ...'. All arguably true. And all statements obtainable this way form part of the raison d'etre of this series.
More details
Series
Edition
Softcover reprint of the original 1st ed. 1992
Language
English
Place of publication
Dordrecht
Netherlands
Target group
Professional and scholarly
Research
Illustrations
X, 207 p.
Dimensions
Height: 240 mm
Width: 160 mm
Thickness: 13 mm
Weight
360 gr
ISBN-13
978-94-010-5137-8 (9789401051378)
DOI
10.1007/978-94-011-2578-9
Schweitzer Classification
Other editions
Additional editions

E. Goles | Servet Martínez
Statistical Physics, Automata Networks and Dynamical Systems
Book
03/1992
Kluwer Academic Publishers
€53.49
Shipment within 15-20 days
Content
Regular and Chaotic Behaviour of Dynamical Systems.- Shocks in the Burgers Equation and the Asymmetric Simple Exclusion Process.- Automata Networks Strategies for Optimization Problems.- Two Chosen Examples for Fractals: one Deterministic, the Other Random.- A Brief Account of Statistical Theories of Learning and Generalization in Neural Networks.- On the R.E.M. and the G.R.E.M..