This text is a beginning graduate-level introduction to neural networks, focussing on current theoretical models, examining what these models can reveal about how the brain functions, and discussing the ramifications for psychology, artificial intelligence and the construction of a new generation of intelligent computers.
This text is a beginning graduate-level introduction to neural networks, focussing on current theoretical models, examining what these models can reveal about how the brain functions, and discussing the ramifications for psychology, artificial intelligence and the construction of a new generation of intelligent computers.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Produktdetails
Produktdetails
Collection Alea-Saclay: Monographs and Texts in Statistical Physics
Preface Acknowledgments 1. Introduction 2. The biology of neural networks: a few features for the sake of non-biologists 3. The dynamics of neural networks: a stochastic approach 4. Hebbian models of associative memory 5. Temporal sequences of patterns 6. The problem of learning in neural networks 7. Learning dynamics in 'visible' neural networks 8. Solving the problem of credit assignment 9. Self-organization 10. Neurocomputation 11. Neurocomputers 12. A critical view of the modeling of neural networks References Index.
Preface Acknowledgments 1. Introduction 2. The biology of neural networks: a few features for the sake of non-biologists 3. The dynamics of neural networks: a stochastic approach 4. Hebbian models of associative memory 5. Temporal sequences of patterns 6. The problem of learning in neural networks 7. Learning dynamics in 'visible' neural networks 8. Solving the problem of credit assignment 9. Self-organization 10. Neurocomputation 11. Neurocomputers 12. A critical view of the modeling of neural networks References Index.
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