31 mai 2016 ~ Commentaires fermés

Neural Network Learning: Theoretical Foundations ebook

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


Neural Network Learning: Theoretical Foundations ebook Kv9k4HI

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. Artificial Neural Networks Mathematical foundations of neural networks. 20120003110024) and the National Natural Science Foundation of China (Grant no. Cheap This important work describes recent theoretical advances in the study of artificial neural networks. In this paper, the SOFM algorithm SOFM neural network uses unsupervised learning and produces a topologically ordered output that displays the similarity between the species presented to it [18, 19]. Because of its theoretical advantages, it is expected to apply Self-Organizing Feature Map to functional diversity analysis. Learning theory (supervised/ unsupervised/ reinforcement learning) Knowledge based networks. The network consists of two layers, .. 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. 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.

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