Schalkoff, Robert J. <br/><br/>
Artificial neural networks / 
Robert J. Schalkoff. 
 - New York :  McGraw-Hill,  c1997. 
 - xxi, 422 p. :  ill. ;  25 cm. 
 - McGraw-Hill series in computer science.  Artificial intelligence .
<br/><br/>Includes bibliographical references and index. 
<br/><br/> Overview: artificial neural networks and neural computing --<br/>  Mathematical fundamentals for ANN study --<br/>  Elementary ANN building blocks --<br/>  Single-unit mappings and the perceptron --<br/>  Introduction to neural mappings and pattern associator applications --<br/>  Feedforward networks and training: part 1 --<br/>  Feedforward networks, part 2: extensions and advanced topics --<br/>  Recurrent networks --<br/>  Competitive and self-organizing networks --<br/>  Radial Basis Function (RBF) networks and Time Delay Neural Networks (TDNNs) --<br/>  Fuzzy neural networks including fuzzy sets and logic and ANN implementations --<br/>  ANN hardware and implementation concerns. 
<br/><br/> Artificial Neural Networks brings together an identifiable core of ideas, techniques, and applications that characterize this emerging field. The text is intended for beginning graduate / advanced undergraduate students as well as practicing engineers and scientists. 
<br/><br/><label>ISBN: </label>007057118X 9780070571181 
<br/><br/><label>LCCN: </label>96049477  
<br/><br/><label>Subjects--Topical Terms: </label><br/>Neural networks (Computer science)
<br/><br/><label>LC Class. No.: </label>QA76.87  / .S3 1997 
<br/><br/><label>Dewey Class. No.: </label>006.32  / SCH