Ebook: Cellular Automata, Dynamical Systems and Neural Networks
- Tags: Statistical Physics Dynamical Systems and Complexity, Theory of Computation, Discrete Mathematics in Computer Science
- Series: Mathematics and Its Applications 282
- Year: 1994
- Publisher: Springer Netherlands
- Edition: 1
- Language: English
- pdf
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
This volume contains the lectures given at the Third School on Statistical Physics and Cooperative Systems, Santiago, Chile, in December 1992.
All lectures are related to recent interdisciplinary trends in statistical physics: nonlinear phenomena, dynamical systems, ergodic theory, cellular automata, symbolic dynamics, large deviations theory and numeral networks. Each contribution is devoted to one or more of the previous subjects. In most cases they are structured as surveys presenting an original point of view and new results at the same time.
For researchers and graduate students interested in statistical physics and theoretical computer science.
This volume contains the lectures given at the Third School on Statistical Physics and Cooperative Systems, Santiago, Chile, in December 1992.
All lectures are related to recent interdisciplinary trends in statistical physics: nonlinear phenomena, dynamical systems, ergodic theory, cellular automata, symbolic dynamics, large deviations theory and numeral networks. Each contribution is devoted to one or more of the previous subjects. In most cases they are structured as surveys presenting an original point of view and new results at the same time.
For researchers and graduate students interested in statistical physics and theoretical computer science.
Content:
Front Matter....Pages i-viii
Cellular Automata and Transducers. A Topological View....Pages 1-22
Automata Network Models of Interacting Populations....Pages 23-77
Entropy, Pressure and Large Deviation....Pages 79-146
Formal Neural Networks: From Supervised to Unsupervised Learning....Pages 147-166
Storage of Correlated Patterns in Neural Networks....Pages 167-189
Back Matter....Pages 191-192
This volume contains the lectures given at the Third School on Statistical Physics and Cooperative Systems, Santiago, Chile, in December 1992.
All lectures are related to recent interdisciplinary trends in statistical physics: nonlinear phenomena, dynamical systems, ergodic theory, cellular automata, symbolic dynamics, large deviations theory and numeral networks. Each contribution is devoted to one or more of the previous subjects. In most cases they are structured as surveys presenting an original point of view and new results at the same time.
For researchers and graduate students interested in statistical physics and theoretical computer science.
Content:
Front Matter....Pages i-viii
Cellular Automata and Transducers. A Topological View....Pages 1-22
Automata Network Models of Interacting Populations....Pages 23-77
Entropy, Pressure and Large Deviation....Pages 79-146
Formal Neural Networks: From Supervised to Unsupervised Learning....Pages 147-166
Storage of Correlated Patterns in Neural Networks....Pages 167-189
Back Matter....Pages 191-192
....