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Neural Network Learning: Theoretical Foundations

Neural Network Learning: Theoretical Foundations

Neural Network Learning: Theoretical Foundations. Martin Anthony, Peter L. Bartlett

Neural Network Learning: Theoretical Foundations


Neural.Network.Learning.Theoretical.Foundations.pdf
ISBN: 052111862X,9780521118620 | 404 pages | 11 Mb


Download Neural Network Learning: Theoretical Foundations



Neural Network Learning: Theoretical Foundations Martin Anthony, Peter L. Bartlett
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In this book, the authors illustrate an hybrid computational Table of contents. Subjects: Neural and Evolutionary Computing (cs.NE); Information Theory (cs.IT); Learning (cs.LG); Differential Geometry (math.DG). Learning theory (supervised/ unsupervised/ reinforcement learning) Knowledge based networks. Product DescriptionThis important work describes recent theoretical advances in the study of artificial neural networks. As evident, the ultimate achievement in this field would be to mimic or exceed human cognitive capabilities including reasoning, recognition, creativity, emotions, understanding, learning and so on. Ярлыки: tutorials djvu ebook hotfile epub chm filesonic rapidshare Tags:Neural Network Learning: Theoretical Foundations fileserve pdf downloads torrent book. Опубликовано 31st May пользователем Vadym Garbuzov. Artificial Neural Networks Mathematical foundations of neural networks. 'The book is a useful and readable mongraph. Cite as: arXiv:1303.0818 [cs.NE]. There are so many different books on Neural Networks: Amazon's Neural Network. Part I Foundations of Computational Intelligence.- Part II Flexible Neural Tress.- Part III Hierarchical Neural Networks.- Part IV Hierarchical Fuzzy Systems.- Part V Reverse Engineering of Dynamical Systems. For beginners it is a nice introduction to the subject, for experts a valuable reference. Amazon.com: Neural Networks: Books Neural Network Learning: Theoretical Foundations by Martin Anthony and Peter L. Cheap This important work describes recent theoretical advances in the study of artificial neural networks. Artificial neural networks, a biologically inspired computing methodology, have the ability to learn by imitating the learning method used in the human brain.

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