| 书目名称 | Neural Networks: Computational Models and Applications | | 编辑 | Huajin Tang,Kay Chen Tan,Zhang Yi | | 视频video | | | 概述 | Latest research on computational models and applications of neural networks.Includes supplementary material: | | 丛书名称 | Studies in Computational Intelligence | | 图书封面 |  | | 描述 | .Neural Networks: Computational Models and Applications covers a wealth of 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. By presenting various computational models, this book is developed to provide readers with a quick but insightful understanding of the broad and rapidly growing areas in the neural networks domain...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. Another significant feature of the book is that it begins with fundamental dynamical problems in pre | | 出版日期 | Book 2007 | | 关键词 | algorithms; artificial neural network; combinatorial optimization; computer vision; data mining; image an | | 版次 | 1 | | doi | https://doi.org/10.1007/978-3-540-69226-3 | | isbn_softcover | 978-3-642-08871-1 | | isbn_ebook | 978-3-540-69226-3Series ISSN 1860-949X Series E-ISSN 1860-9503 | | issn_series | 1860-949X | | copyright | Springer-Verlag Berlin Heidelberg 2007 |
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发表于 2025-3-21 17:53:17
