Neural Fuzzy Systems
by Robert Fuller
Publisher: Abo Akademi University 1995
Number of pages: 348
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 the basic principles of fuzzy neural hybrid systems.
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by David Kriesel - dkriesel.com
Text and illustrations should be memorable and easy to understand to offer as many people as possible access to the field of neural networks. The chapters are individually accessible to readers with little previous knowledge.
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.
by Martin T. Hagan, et al.
This book 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.
Neural networks excel in a number of problem areas where conventional von Neumann computer systems have traditionally been slow and inefficient. This book is going to discuss the creation and use of artificial neural networks.