Neural Network Design
by Martin T. Hagan, et al.
Number of pages: 1012
This book, by the authors of the Neural Network Toolbox for MATLAB, provides a clear and detailed coverage of fundamental neural network architectures and learning rules. In it, the authors emphasize a coherent presentation of the principal neural networks, methods for training them and their applications to practical problems.
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by Ivan F Wilde - King's College London
These notes are based on lectures given in the Mathematics Department at King's College London. An attempt has been made to present a logical (mathematical) account of some of the basic ideas of the 'artificial intelligence' aspects of the subject.
by Robert Fuller - Abo Akademi University
This text covers inference mechanisms in fuzzy expert systems, learning rules of feedforward multi-layer supervised neural networks, Kohonen's unsupervised learning algorithm for classification of input patterns, and fuzzy neural hybrid systems.
by Allessandro Treves, Yasser Roudi - SISSA
We review the common themes, the network models and the mathematical formalism underlying our studies about different stages in the evolution of the human brain. These studies discuss the evolution of cortical networks in terms of their computations.
by William Bialek - arXiv
We all are fascinated by the phenomena of intelligent behavior, as generated by our own brains. As physicists we want to understand if there are some general principles that govern the dynamics of the neural circuits that underlie these phenomena.