Practical neural network recipes in C++ / Timothy Masters.
Publication details: Boston : Academic Press, c1993.Description: xviii, 493 p. : ill. ; 24 cm. + 1 computer disk (5 1/4 in.)ISBN:- 0124790402 (alk. paper)
- 006.32 20 MAS
| Item type | Current library | Call number | Copy number | Status | Date due | Barcode |
|---|---|---|---|---|---|---|
Book Open Access
|
Engineering Library | 006.32 MAS 1 (Browse shelf(Opens below)) | 1 | Available | 0007678 |
Contents
1. Foundations.
2. Classification.
3. Auto association.
4.Time Series Prediction.
5. Function Approximation.
6. Multilayer Feed forward Networks.
7. Eluding Local Minimai: Simulated Annealing.
8. Eluding Local Minima II: Genetic Optimisation.
9. Regression and Neural Networks.
10. Designing Feedforward Network Architectures.
11. Interpreting Weights: How Does This Thing Work?
12. Probalistic Neural Networks.
13. Functional Link Networks.
14. Hybrid Networks.
15. Designing the Training Set.
16. Preparing Input Data.
17. Fuzzy Data and Processing.
18. Unsupervised Training.
19. Evaluating Performance of Neural Networks.
20. Confidence Measures.
21. Optimizing the Decision Threshold.
22. Using the NEURAL Program. Appendix.
Bibliography.
Includes bibliographical references (p. 479-490) and index.
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