Advances in Neural Networks - ISNN 2006 (eBook, PDF)

Third International Symposium on Neural Networks, ISNN 2006, Chengdu, China, May 28 - June 1, 2006, Proceedings, Part I
Redaktion: Wang, Jun; Hujun, Yin; Lu, Bao-Liang; Zurada, Jacek M.; Yi, Zhang

• Format: PDF

Produktbeschreibung

This is Volume I of a three volume set constituting the refereed proceedings of the Third International Symposium on Neural Networks, ISNN 2006. 616 revised papers are organized in topical sections on neurobiological analysis, theoretical analysis, neurodynamic optimization, learning algorithms, model design, kernel methods, data preprocessing, pattern classification, computer vision, image and signal processing, system modeling, robotic systems, transportation systems, communication networks, information security, fault detection, financial analysis, bioinformatics, biomedical and industrial applications, and more.

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Produktdetails

• Verlag: Springer Berlin Heidelberg
• Seitenzahl: 1444
• Erscheinungstermin: 10. Mai 2006
• Englisch
• ISBN-13: 9783540344407
• Artikelnr.: 44122303

Autorenporträt

Jun Wang, The Chinese University of Hong Kong / Zhang Yi, University of Electronic Science and Technology, Chengdu, China / Jacek M. Zurada, University of Louisville, KY, USA / Bao-Liang Lu, Shanghai Jiao Tong University, China / Yin Hujun, University of Manchester, UK

Inhaltsangabe

Neurobiological Analysis.- Theoretical Analysis.- Neurodynamic Optimization.- Learning Algorithms.- Model Design.- Kernel Methods.- ICA and BSS.- Data Preprocessing.

Rezensionen

From the reviews:

"It addresses the domain of artificial Intelligence (AI) and presents state-of-the-art research, development, and education in the field. ... a useful resource for scientists and educators interested in the field of NN systems ... . gives the reader a sense of the applications and challenges of the filed, and provides an extensive bibliography for further investigation. ... The collection offers a broad perspective on a topic that is widely discussed and underlines many of its applications. This makes it highly recommendable to the AI community." (M. Caramihai, Computing Reviews, December, 2006)