Masters, Timothy. <br/><br/>
Practical neural network recipes in C++ / 
Timothy Masters. 
 - Boston :  Academic Press,  c1993. 
 - xviii, 493 p. :  ill. ;  24 cm. +  1 computer disk (5 1/4 in.) 
<br/><br/> Contents<br/> 	<br/>1. Foundations. <br/>2. Classification. <br/>3. Auto association. <br/>4.Time Series Prediction. <br/>5. Function Approximation. <br/>6. Multilayer Feed forward Networks. <br/>7. Eluding Local Minimai: Simulated Annealing. <br/>8. Eluding Local Minima II: Genetic Optimisation. <br/>9. Regression and Neural Networks. <br/>10. Designing Feedforward Network Architectures. <br/>11. Interpreting Weights: How Does This Thing Work?<br/>12. Probalistic Neural Networks. <br/>13. Functional Link Networks. <br/>14. Hybrid Networks. <br/>15. Designing the Training Set. <br/>16. Preparing Input Data. <br/>17. Fuzzy Data and Processing. <br/>18. Unsupervised Training. <br/>19. Evaluating Performance of Neural Networks. <br/>20. Confidence Measures. <br/>21. Optimizing the Decision Threshold. <br/>22. Using the NEURAL Program. Appendix. <br/> 	Bibliography. <br/> 
<br/><br/>Includes bibliographical references (p. 479-490) and index. 
<br/><br/><label>ISBN: </label>0124790402 (alk. paper) 
<br/><br/><label>LCCN: </label>92047469  
<br/><br/><label>Subjects--Topical Terms: </label><br/>Neural networks (Computer science)<br/>C++ (Computer program language)
<br/><br/><label>Dewey Class. No.: </label>006.32  / MAS