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  3. An Introduction to the Modeling of Neural Networks
  • Cited by 71
Publisher:
Cambridge University Press
Online publication date:
November 2009
Print publication year:
1992
Online ISBN:
9780511622793
DOI:
https://doi.org/10.1017/CBO9780511622793
Subjects:
Physics and Astronomy, Condensed Matter Physics, Nanoscience and Mesoscopic Physics, Mathematical Methods
Series:
Collection Alea-Saclay: Monographs and Texts in Statistical Physics
Information

Book description

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. The book is divided into four parts. The first part gives an account of the anatomy of the central nervous system, followed by a brief introduction to neurophysiology. The second part is devoted to the dynamics of neuronal states, and demonstrates how very simple models may stimulate associative memory. The third part of the book discusses models of learning, including detailed discussions on the limits of memory storage, methods of learning and their associated models, associativity, and error correction. The final part reviews possible applications of neural networks in artificial intelligence, expert systems, optimization problems, and the construction of actual neuronal supercomputers, with the potential for one-hundred-fold increase in speed over contemporary serial machines.

Reviews

"...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

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