Customer Reviews

Neural Network Models: Theory and Projects, 2nd Edition

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This book is an excellent introduction to neural networks for the reader with a good mathematics background. The first few chapters describe popular and useful algorithms for implementing neural networks (Hopfield, backpropagation). Much of the book is devoted to the theory behind these networks (capacity, convergence and the dynamical systems approach, Markov chains). [This gave me, a total novice before reading the book, a much better idea of how these networks function, so much so that I can implement them in software.] Complementing the theory are numerous stimulating projects that illustrate many applications and open questions in the field.

De Wilde's book is very clearly written. Its compact size is a joy in this age of mammoth, but often poorly-written and substanceless, textbooks.

Neural Network Models: Theory and Projects concentrates on the essential parameters and results that will enable the reader to design hardware or software implementations of neural networks and to assess critically existing commercial products.