Nonlinear dynamical systems : feedforward neural network perspectives / Irwin Sandberg ... [et al.].
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| Format: | Book |
| Language: | English |
| Published: |
New York :
John Wiley,
2001.
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| Subjects: |
Table of Contents:
- 1. Feedforward Neural Networks: An Introduction / Simon Haykin
- 1.1. Supervised Learning
- 1.2. Unsupervised Learning
- 1.3. Temporal Processing Using Feedforward Networks
- 1.4. Concluding Remarks
- 2. Uniform Approximation and Nonlinear Network Structures / Irwin W. Sandberg
- 2.1. Introduction
- 2.2. General Structures for Classification
- 2.3. Myopic Maps, Neural Network Approximations, and Volterra Series
- 2.4. Separation Conditions and Approximation of Discrete-Time and Discrete-Space Systems
- 2.5. Concluding Comments
- 2.6. Appendices
- 3. Robust Neural Networks / James T. Lo
- 3.1. Introduction
- 3.2. Preliminaries
- 3.3. General Risk-Sensitive Functionals
- 3.4. Approximation of Functions by MLPs
- 3.5. Approximation of Functions by RBFs
- 3.6. Formulation of Risk-Sensitive Identification of Systems
- 3.7. Series-Parallel Identification by Artificial Neural Networks [ANNs]
- 3.8. Paral lel Identification of ANNs
- 3.9. Conclusion
- 4. Modeling, Segmentation, and Classification of Nonlinear Nonstationary Time Series / Craig L. Fancourt and Jose C. Principe
- 4.1. Introduction
- 4.2. Supervised Sequential Change Detection
- 4.3. Unsupervised Sequential Segmentation
- 4.4. Memoryless Mixture Models
- 4.5. Mixture Models for Processes with Memory
- 4.6. Gated Competitive Experts
- 4.7. Competitive Temporal Principal Component Analysis
- 4.8. Output-Based Gating Algorithms
- 4.9. Other Approaches
- 4.10. Conclusions
- 5. Application of Feedforward Networks to Speech / Shigeru Katagiri
- 5.1. Introduction
- 5.2. Fundamentals of Speech Signals and Processing Technologies
- 5.3. Fundamental Issues of ANN Design
- 5.4. Speech Recognition
- 5.5. Applications to Other Types of Speech Processing
- 5.6. Concluding Remarks.