TY  - BOOK
AU  - Haykin,Simon
TI  - Neural networks and learning machines
SN  - 9780131471399
U1  - 006.32019 23
PY  - 2009///
CY  - New York
PB  - Prentice Hall
KW  - Neural Networks (Computer Science)
KW  - Adaptive Filters
N1  - This book is completed in two parts. The 1st part contains up to chapter 7; Includes bibliography and index; Principal-components analysis -- Self-organizing maps -- Information-theoretic learning models -- Stochastic methods rooted in statistical mechanics -- Dynamic programming -- Neurodynamics -- Bayseian filtering for state estimation of dynamic systems -- Dynamically driven recurrent networks
N2  - For graduate-level neural network courses offered in the departments of Computer Engineering, Electrical Engineering, and Computer Science. Renowned for its thoroughness and readability, this well-organized and completely up-to-date text remains the most comprehensive treatment of neural networks from an engineering perspective. Refocused, revised and renamed to reflect the duality of neural networks and learning machines, this edition recognizes that the subject matter is richer when these topics are studied together. Ideas drawn from neural networks and machine learning are hybridized to perform improved learning tasks beyond the capability of either independently
ER  -