Neural Networks for Intelligent Signal Processing (Series on...

Features

• Cover Type: Hard Cover with 508 pages
• Published by: World Scientific Pub Co Inc. January 2003
• Written in: English
• ISBN 10 Number: 9812383050
• ISBN 13 Number: 978-9812383051
• Book Dimensions: 9.1 x 6.1 x 1.2 inches
• Weighs: 2 pounds

Product Description
This book provides a thorough theoretical and practical introduction to the application of neural networks to pattern recognition and intelligent signal processing. It has been tested on students, unfamiliar with neural networks, who were able to pick up enough details to successfully complete their masters or final year undergraduate projects. The text also presents a comprehensive treatment of a class of neural networks called common bandwidth spherical basis function NNs, including the probabilistic NN, the modified probabilistic NN and the general regression NN.

Reader Reviews
Anthony Zaknich wrote a book that provides the reader with a very broad knowledge about neural networks especially for signal processing. Fundamental facts are extracted and presented in a form that is very easy to read, such as listings, keywords, main formulas, diagrams and results from experiments. Zaknich avoided going into too much theoretical details which might only confuse beginners. But also for advanced and professionals his book is a good source of well-structured basic knowledge. This is the difference compared to other books about neural networks since the reader finds the essence that is crucial to understanding the basics. A huge selection of literature references enables the reader to quickly continue deeper studies about interesting topics. Furthermore, Zacknich' provides examples and results from experiments and simulations which he has done by himself for the most parts. He compares different neural network types and configurations for various real-world examples. These comparisons and results were a very valuable help for me in order to understand the differences and characteristics among the vast number of various network types. Finally, Zaknich's book helps me very much in my job for that it is very important to have application results and "benchmark-like" comparisons. His explanations are often with reference to his own developed Modified Probabilistic Neural Network (MPNN) and Advanced MPNN that animated me to carry out some tests based on his MPNN. Another idea in his book is the Integrated Sensory Intelligent System (ISIS) that he introduces. I would highly appreciate if Zaknich releases new books especially on the field of signal processing and his idea of the ISIS. Zaknich knows how to guide the reader through the different topics and not to bore him by long theoretical sequences and formulas. There is already a wide range of available literature that explains topics, such as classifications, control systems, robots etc. in more detail. Interesting quotations from different sources of literature attached to each chapter makes the book even more than merely a scientific book. Claas Richter Silicann Technologies (Japan/Germany)