Title:
Principles of neurocomputing for science and engineering
Personal Author:
Publication Information:
New York, NY : McGraw Hill, 2001
ISBN:
9780070259669
Added Author:
Available:*
Library | Item Barcode | Call Number | Material Type | Item Category 1 | Status |
|---|---|---|---|---|---|
Searching... | 30000004605741 | QA76.87 H35 2001 | Open Access Book | Book | Searching... |
On Order
Summary
Summary
Unlike other neural network books, this is written specifically for scientists and engineers who want to apply neural networks to solve complex problems. For each neurocomputing concept, a solid mathematical foundation is presented along with illustrative examples to accompany that particular architecture and associated training algorithm. It incorporates many detailed examples and an extensive set of end-of-chapter problems.
Table of Contents
| 1 Introduction to Neurocomputing |
| 2 Fundamental Neurocomputing Concepts |
| 3 Mapping Networks |
| 4 Self-Organizing Networks |
| 5 Recurrent Networks and Temporal Feedforward Networks |
| 6 Neural Networks for Optimization Problems |
| 7 Solving Matrix Algebra Problems with Neural Networks |
| 8 Solution of Linear Algebraic Equations Using Neural Networks |
| 9 Statistical Methods Using Neural Networks |
| 10 Identification, Control, and Estimation Using Neural Networks |
| Appendix Mathematical Foundation for Neurocomputing |
