An introduction to neural networks /
Gurney, Kevin,
An introduction to neural networks / Kevin Gurney. - Primera edición. - xi, 234 páginas : ilustraciones, gráficas ; 24 cm .
Incluye referencias (215-227) Incluye índice (229-234)
1. Neural networks - an overview ; 2. Real and artificial neurons ; 3. TLUs, linear separability and vectors ; 4. Training TLUs: the perceptron rule ; 5. The delta rule ; 6. Multilayer nets and backpropagation ; 7. Associative memories: the Hopfield net ; 8. Self-organization ; 9. Adaptive resonance theory: ART ; 10. Nodes, nets and algorithms: further alternatives ; 11. Taxonomies, contexts and hierarchies.
The book provides comprehensive coverage of the following key areas: artificial neurons as models of their real counterparts; the geometry of network action in pattern space; gradient descent methods, including back- propagation; associative memory and Hopfield nets; and selforganisation and feature maps. The traditionally difficult topic of adaptive resonance theory is clarified within a hierarchical description of its operation, which disentangles features specific to separate levels of discussion. Finally, a chapter is devoted to organizing the study of neural networks in various ways, and it attempts to overcome the general impression that it is a loose-knit collection of structures and recipes. The primary aim of the book is to provide an understanding of basic principles, but it also includes several real-world examples to provide a concrete focus. This will undoubtedly enhance its appeal to those involved in the design, construction and management of networks in commercial environments and who wish to improve their understanding of network simulator packages. As a comprehensive and highly accessible introduction to neural networks, this book will satisfy a wide range of readers, both students and professionals, in cognitive science, psychology, computer science and electrical engineering.
9781857285031
Redes neuronales (Computadores)--Estrategia y técnica.
Inteligencia artificial--Enseñanza.
Aprendizaje automático (Inteligencia Artificial)--Enseñanza.
Algoritmos--Redes de computadores.
006.32 / G981
An introduction to neural networks / Kevin Gurney. - Primera edición. - xi, 234 páginas : ilustraciones, gráficas ; 24 cm .
Incluye referencias (215-227) Incluye índice (229-234)
1. Neural networks - an overview ; 2. Real and artificial neurons ; 3. TLUs, linear separability and vectors ; 4. Training TLUs: the perceptron rule ; 5. The delta rule ; 6. Multilayer nets and backpropagation ; 7. Associative memories: the Hopfield net ; 8. Self-organization ; 9. Adaptive resonance theory: ART ; 10. Nodes, nets and algorithms: further alternatives ; 11. Taxonomies, contexts and hierarchies.
The book provides comprehensive coverage of the following key areas: artificial neurons as models of their real counterparts; the geometry of network action in pattern space; gradient descent methods, including back- propagation; associative memory and Hopfield nets; and selforganisation and feature maps. The traditionally difficult topic of adaptive resonance theory is clarified within a hierarchical description of its operation, which disentangles features specific to separate levels of discussion. Finally, a chapter is devoted to organizing the study of neural networks in various ways, and it attempts to overcome the general impression that it is a loose-knit collection of structures and recipes. The primary aim of the book is to provide an understanding of basic principles, but it also includes several real-world examples to provide a concrete focus. This will undoubtedly enhance its appeal to those involved in the design, construction and management of networks in commercial environments and who wish to improve their understanding of network simulator packages. As a comprehensive and highly accessible introduction to neural networks, this book will satisfy a wide range of readers, both students and professionals, in cognitive science, psychology, computer science and electrical engineering.
9781857285031
Redes neuronales (Computadores)--Estrategia y técnica.
Inteligencia artificial--Enseñanza.
Aprendizaje automático (Inteligencia Artificial)--Enseñanza.
Algoritmos--Redes de computadores.
006.32 / G981
