This book bridges the gap between the highly theoretical level of research in neural networks and the practical, analytical level encountered by those who are not specialised in the neural field. It covers the taxonomy of network paradigms and interrelates the paradigms in a systematic fashion, explores practical implementation in terms of applications and discusses neural products that are in development or on the market: chips, printed circuit boards, systems and software.
Sprache
Verlagsort
Verlagsgruppe
Zielgruppe
Für höhere Schule und Studium
Maße
Höhe: 235 mm
Breite: 155 mm
Dicke: 15 mm
Gewicht
ISBN-13
978-0-13-368903-7 (9780133689037)
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Schweitzer Klassifikation
1. A Structure of an Artificial Neural Network. 2. Applications of Neural Networks. 3. The Early Years. 4. The Hopfield Net. 5. Self Organizing Maps. 6. Backpropagation. 7. Learning Laws and Continued Taxonomy. 8. Adaptive Resonance Theory. 9. Bidirectional Associative Memory. 10. Variations on Neural Themes. 11. Fuzzy Theory. 12. Integrated Circuits. 13. Optical Neural Nets. 14. The Evolution of Intelligence. Appendix: Mathematical Notation. Bibliography. Index.
