Neural networks and computing : learning algorithms and applications / Tommy W.S. Chow, Siu-Yeung Cho.
Material type:
TextSeries: Series in electrical and computer engineering ; v. 7.Publication details: London : Imperial College Press ; Singapore ; Hackensack, NJ : Distributed by World Scientific, 2007.Description: 1 online resource (xii, 309 pages) : illustrationsContent type: - text
- computer
- online resource
- 9781860949692
- 186094969X
- 1281869457
- 9781281869456
- 9786611869458
- 661186945X
- Neural networks (Computer science)
- Machine learning
- Computer programming
- Neural Networks, Computer
- Algorithms
- Réseaux neuronaux (Informatique)
- Programmation (Informatique)
- Algorithmes
- Apprentissage automatique
- computer programming
- algorithms
- COMPUTERS -- Neural Networks
- Machine learning
- Neural networks (Computer science)
- 006.3/2 22
- QA76.87 .C48 2007eb
| Item type | Current library | Collection | Call number | Status | Date due | Barcode | Item holds | |
|---|---|---|---|---|---|---|---|---|
eBook
|
e-Library | EBSCO Computers | Available |
Some online versions lack accompanying media packaged with the printed version.
Includes bibliographical references (pages 291-304) and index.
Introduction -- Learning performance and enhancement -- Generalization and performance enhancement -- Basis function networks for classification -- Self-organizing maps -- Classification and feature selection -- Engineering applications.
Print version record.
This book covers neural networks with special emphasis on advanced learning methodologies and applications. It includes practical issues of weight initializations, stalling of learning, and escape from a local minima, which have not been covered by many existing books in this area. Additionally, the book highlights the important feature selection problem, which baffles many neural networks practitioners because of the difficulties handling large datasets. It also contains several interesting IT, engineering and bioinformatics applications.
English.
WorldCat record variable field(s) change: 650