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by Kay Chen Tan,Zhang Yi,Huajin Tang

  • ISBN: 3540692258
  • Category: Technology
  • Author: Kay Chen Tan,Zhang Yi,Huajin Tang
  • Subcategory: Computer Science
  • Other formats: mbr txt rtf azw
  • Language: English
  • Publisher: Springer; 2007 edition (March 27, 2007)
  • Pages: 300 pages
  • FB2 size: 1849 kb
  • EPUB size: 1971 kb
  • Rating: 4.1
  • Votes: 841
Download Neural Networks: Computational Models and Applications (Studies in Computational Intelligence) fb2

Authors: Tang, Huajin, Tan, Kay Chen, Yi, Zhang .

Authors: Tang, Huajin, Tan, Kay Chen, Yi, Zhang. Besides laying down fundamentals on artificial neural networks, this book also studies biologically inspired neural networks. Some typical computational models are discussed, and subsequently applied to objection recognition, scene analysis and associative memory. The studies of bio-inspired models have important implications in computer vision and robotic navigation, as well as new efficient algorithms for image analysis.

Huajin Tang, Kay Chen Tan and Zhang Yi. Neural Networks: Computational Models and Applications. Hierarchical regression analyses showed that common predictors of inter- and intrapersonal PTG were intrusive, hyper-aroused, and avoidant states, perceived family emotional support, and being married. Younger age, pre-disaster employment, and disaster-related traumatic experiences were specific predictors of interpersonal PTG, while adaptive coping was a specific predictor of intrapersonal PTG Implications and limitations of this study were discussed.

Neural Networks: Computational Models and Applications (Studies in Computational Intelligence, Volume 53). Huajin Tang, Kay Chen Tan, Zhang Yi. Download (pdf, . 8 Mb) Donate Read. Epub FB2 mobi txt RTF. Converted file can differ from the original. If possible, download the file in its original format.

Includes bibliographical references. Personal Name: Tan, K. C. Personal Name: Zhang, Yi, 1963-. Rubrics: Neural networks (Computer science). Download now Neural networks : computational models and applications Huajin Tang, Kay Chen Tan, Zhang Y. Download PDF book format. Download DOC book format.

Дата издания: 2007 Серия: Studies in Computational Intelligence Язык: ENG Читательская аудитория: Science . Описание: This book presents a powerful hybrid intelligent system based on fuzzy logic, neural networks, genetic algorithms and related intelligent techniques.

Дата издания: 2007 Серия: Studies in Computational Intelligence Язык: ENG Читательская аудитория: Science Поставляется из: Германии.

by Tang Huajin E. l, Kay Chen Tan, Zhang Y. Neural Networks: Computational Models and Applications presents important theoretical and practical. l, Kay Chen Tan, Zhang Yi. Hardcover, 300 Pages, Published 2007. more issues in neural networks, including the learning algorithms of feed-forward neural networks, various dynamical properties of recurrent neural networks, winner-take-all networks and their applications in broad manifolds of computational intelligence: pattern recognition, uniform approximation, constrained optimization, NP-hard problems, and image segmentation.

by Huajin Tang, Kay Chen Tan, Zhang Y.

Besides laying down fundamentals on artificial neural networks, this book also studies biologically inspired neural networks.

Neural Networks: Computational Models and Applications Huajin Tang; Kay Chen Tan; Zhang Yi Springer 9783540692256 : Presents theoretical and practical issues in neural networks, including th. Дата издания: 2007 Серия: Studies in Computational Intelligence Язык: ENG Иллюстрации: 103 black & white illustrations, 27 black & white tables, biography Размер: 234 x 156 x 19 Читательская аудитория: Professional & vocational Рейтинг

neural networks, winner-take-all networks and their applications in broad .

Neural Networks: Computational Models and Applications - Studies in Computational Intelligence 53 (Paperback). Neural Networks: Computational Models and Applications presents important theoretical and practical issues in neural networks, including the learning algorithms of feed-forward neural networks, various dynamical properties of recurrent neural networks, winner-take-all networks and their applications in broad manifolds of computational intelligence: pattern recognition, uniform approximation, constrained optimization, NP-hard problems, and image segmentation.

Neural Networks : Computational Models and Applications Huajin Tang.

Neural Networks : Computational Models and Applications. View graph of relations. Kay Chen Tan. Zhang Yi. Detail(s).

Neural Networks: Computational Models and Applications presents important theoretical and practical issues in neural networks, including the learning algorithms of feed-forward neural networks, various dynamical properties of recurrent neural networks, winner-take-all networks and their applications in broad manifolds of computational intelligence: pattern recognition, uniform approximation, constrained optimization, NP-hard problems, and image segmentation. The book offers a compact, insightful understanding of the broad and rapidly growing neural networks domain.



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