Learning and Soft Computing by Vojislav Kecman
This textbook provides a thorough introduction to the field of learning from experimental data and soft computing. Support vector machines (SVM) and neural networks (NN) are the mathematical structures, or models, that underlie learning, while fuzzy logic systems (FLS) enable us to embed structured human knowledge into workable algorithms. The book assumes that it is not only useful, but necessary, to treat SVM, NN, and FLS as parts of a connected whole. Throughout, the theory and algorithms are illustrated by practical examples, as well as by problem sets and simulated experiments. This approach enables the reader to develop SVM, NN, and FLS in addition to understanding them. The book also presents three case studies: on NN-based control, financial time series analysis, and computer graphics. A solutions manual and all of the MATLAB programs needed for the simulated experiments are available.-
An Introduction to Genetic Algorithms
-
Toward a Practice of Autonomous Systems
-
Genetic Programming
-
Artificial Life VII
-
Imitation in Animals and Artifacts
-
Dynamic Patterns
-
Understanding Complex Adaptive Systems
-
Toward a Science of Consciousness
-
An Introduction to Natural Computation
-
Adaptation in Natural and Artificial Systems
-
Elements of Artificial Neural Networks
| SKU | Unavailable |
| ISBN 13 | 9780262527903 |
| ISBN 10 | 0262527901 |
| Title | Learning and Soft Computing |
| Author | Vojislav Kecman |
| Series | Complex Adaptive Systems |
| Condition | Unavailable |
| Binding Type | Paperback |
| Publisher | MIT Press Ltd |
| Year published | 2001-06-08 |
| Number of pages | 576 |
| Cover note | Book picture is for illustrative purposes only, actual binding, cover or edition may vary. |
| Note | Unavailable |