Predictive Modular Neural Networks Applications to Time Series
The subject of this book is predictive modular neural networks and their ap plication to time series problems: classification, prediction and identification. The intended audience is researchers and graduate students in the fields of neural networks, computer science, statistical pattern recognitio...
| Main Authors: | , |
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| Format: | eBook |
| Language: | English |
| Published: |
New York, NY
Springer US
1998, 1998
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| Edition: | 1st ed. 1998 |
| Series: | The Springer International Series in Engineering and Computer Science
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| Subjects: | |
| Online Access: | |
| Collection: | Springer Book Archives -2004 - Collection details see MPG.ReNa |
Table of Contents:
- 1. Introduction
- 1.1 Classification, Prediction and Identification: an Informal Description
- 1.2 Part I: Known Sources
- 1.3 Part II: Applications
- 1.4 Part III: Unknown Sources
- 1.5 Part IV: Connections
- I Known Sources
- 2. Premonn Classification and Prediction
- 3. Generalizations of the Basic Premonn
- 4. Mathematical Analysis
- 5. System Identification by the Predictive Modular Approach
- II Applications
- 6. Implementation Issues
- 7. Classification of Visually Evoked Responses
- 8. Prediction of Short Term Electric Loads
- 9. Parameter Estimation for and Activated Sludge Process
- III Unknown Sources
- 10. Source Identification Algorithms
- 11. Convergence of Parallel Data Allocation
- 12. Convergence of Serial Data Allocation
- IV Connections
- 13. Bibliographic Remarks
- 14. Epilogue
- Appendices
- A— Mathematical Concepts
- A.1 Notation
- A.2 Probability Theory
- A.3 Sequences of Bernoulli Trials
- A.4 Markov Chains
- References