Verlag: Springer- Verlag, New York City, 2005
ISBN 10: 3540287558 ISBN 13: 9783540287551
Sprache: Englisch
Anbieter: Doss-Haus Books, Redondo Beach, CA, USA
Hardcover. Zustand: Very Good. No Jacket. Hardcover 2005 Part 2, library bound edition. Ex-library book with stamps and labels attached. Binding firm. Pages unmarked and clean. Laminated covers and text in very good condition. Series: Lecture Notes in Computer Science ;3697.
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Verlag: Springer Berlin Heidelberg, 2005
ISBN 10: 3540287558 ISBN 13: 9783540287551
Sprache: Englisch
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In den WarenkorbPaperback. Zustand: Brand New. 1st edition. 1045 pages. 9.25x6.25x1.50 inches. In Stock.
Verlag: Springer, Berlin Apr 2009, 2009
ISBN 10: 3540287558 ISBN 13: 9783540287551
Sprache: Englisch
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Taschenbuch. Zustand: Neu. Neuware - The two volume set LNCS 3696 and LNCS 3697 constitutes the refereed proceedings of the 15th International Conference on Artificial Neural Networks, ICANN 2005, held in Warsaw, Poland in September 2005. The over 600 papers submitted to ICANN 2005 were thoroughly reviewed and carefully selected for presentation. The first volume includes 106 contributions related to Biological Inspirations; topics addressed are modeling the brain and cognitive functions, development of cognitive powers in embodied systems spiking neural networks, associative memory models, models of biological functions, projects in the area of neuroIT, evolutionary and other biological inspirations, self-organizing maps and their applications, computer vision, face recognition and detection, sound and speech recognition, bioinformatics, biomedical applications, and information- theoretic concepts in biomedical data analysis. The second volume contains 162 contributions related to Formal Models and their Applications and deals with new neural network models, supervised learning algorithms, ensemble-based learning, unsupervised learning, recurent neural networks, reinforcement learning, bayesian approaches to learning, learning theory, artificial neural networks for system modeling, decision making, optimalization and control, knowledge extraction from neural networks, temporal data analysis, prediction and forecasting, support vector machines and kernel-based methods, soft computing methods for data representation, analysis and processing, data fusion for industrial, medical and environmental applications, non-linear predictive models for speech processing, intelligent multimedia and semantics, applications to natural language processing, various applications, computational intelligence in games, and issu es in hardware implementation.