Neural Networks for Identification, Prediction, and Control

Rating:
Summary: very clear and useful for studies about neural network
Review: I am studying civil engineering and I found this book very useful for my studies:I have investigated the application of neural networks in the identification of Tensegrities, that is civil sistems made up of rigid beams and cables. The identifications I made, using Matlab, were essentially statics, but I had to write something dealing with dynamic identification. I found this book very clear, and it helped me much more than other various articles and books I read on the subject.

Rating:
Summary: State-of-the-art neural networks for complex control
Review: The book is both clear and interesting to read. It is invaluable for people wishing to implement neural network systems for modelling, prediction or control. Many state-of-the-art neural network techniques are explained, including MLP, LVQ, Elman, Jordan, Kohonen and ART. In addition, a large number of examples are given of how neural networks can be employed for controlling complex non-linear systems.

Rating:
Summary: Not Good
Review: This book was quite disappointing. The majority of examples were linear (which is not the strengh of the use of Neural Networks) especially in the presentation of system identification. The material itself needs to be updated to the current methods. It seems that the authors tried to cover too much material (i.e. Genetic Algs., Fuzzy logic) which resulted in not enough detail especially mathematically.