tasks that rrquire written :>rocedures, procedure performance evali.ration, and a procedure critewi checklist are given in the next three appenditres. The last two contain numeroiis esmiples of fornits for procedures and ojxmting limits tab.es. In summixiiy. this btmk is iecommended for anyone invo
Neural networks and their applications: Edited by J. G. Taylor. John Wiley & Sons, New York. (1996). 293 pages. $69.95
- Publisher
- Elsevier Science
- Year
- 1997
- Tongue
- English
- Weight
- 112 KB
- Volume
- 33
- Category
- Article
- ISSN
- 0898-1221
No coin nor oath required. For personal study only.
β¦ Synopsis
List of contributors. 1. Modelling and controller design of an EGR solenoid valve using neural networks (M.A. Arain). 2. Neural networks as decoders in error-correcting systems for digital data transmission (J. Serra-Sagrist~). 3. Estimating helicopter strain using a neural network approach (A.D. Vella et al.). 4. Neural networks for texture classification (J.F. Boyce and J.F. Haddon). 5. Modelling psychiatric decisions with linear regression and neural networks (W. Penny and D.P. Frost). 6. Visualizing nuclear magnetic resonance spectra with self-organizing neural networks (A. Koski et al.). 7. Comparative study of two self organizing and structurally adaptive dynamic neural tree networks. (K. Butchart et al.). 8. A clustering algorithm to produce context rich networks (N. Allot et al.). 9. Robust financial modelling by combining neural network estimators of mean and median (A.N. Burgess). 10. ISTRIA: An on-line neural network system for the analysis of financial markets (S. DiPasquale et al.). 11. Prediction of the S&P 500 index with neural networks (J. Angstenberger). 12. Neural network based models for forecasting iX. Ding et al.). 13. GA to train NNs using sharing and pruning: Global GA search combined with local BP search (M. Schmidt and T. Stidsen). 14. Evolutionary neurocontrol of chaos and the attitude control problem (D.C. Dracopoulos). 15. An object-oriented framework for NE-SS hybrid systems (A.I. Vermesan and O. Vermesan). 16. Using correlation matrix memories for inferencing in expert systems (J. Austin and R. Filer). 17. Neural networks in VLSI hardware ( T. Clarkson). 18. Optimal VLSI implementation of neural networks ( V. Beiu). 19. New avenues in neural networks. Index.
π SIMILAR VOLUMES
## BOOK REVIEW Methods and Applications of Linear Models: on examining the data and transformations as well as theorems. Almost all the topics I use to test the Regression and the Analysis of Variance by Ronald R. Hocking, Wiley, New York, 1996. No. coverage were in the index -those that were not