This book is a beginning graduate-level introduction to neural networks which is divided into four parts.
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"...a beginning graduate-level text that discusses a wide range of neural network models and algorithms: simulated annealing, Aleksander's model, Boltzmann machine, perceptron, backpropagation, Hopfield's models, self-organization, and others. It may be especially useful for those with no or limited knowledge of the biology of neural networks and their relation to artificial neural networks." George Georgiou, Mathematical Reviews
"...excellent introductions to this exciting new enterprise...this comprehensive summary of research results in neural networks with both practical and biological applications provides an invaluable resource for the graduate student or researcher working in this field...summarizes some of the important questions that remain in our understanding of biological neural networks that may be addressed with greater integration of neural network modeling and biological experimentation." Roderick V. Jensen, American Journal of Physics
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.
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Condition: New. This book is a beginning graduate-level introduction to neural networks which is divided into four parts. Series Editor(s): Godrche, C. Series: Collection Alea-Saclay: Monographs and Texts in Statistical Physics. Num Pages: 492 pages, diagrams. BIC Classification: PHS; PSVD. Category: (P) Professional & Vocational. Dimension: 228 x 152 x 32. Weight in Grams: 890. . 1992. 1st Edition. Hardcover. . . . . Seller Inventory # V9780521414517
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