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

Neural Network Learning: Theoretical Foundations Martin Anthony, Peter L. Bartlett ebook
Publisher:
Format: pdf
ISBN: 052111862X, 9780521118620
Page: 404

20120003110024) and the National Natural Science Foundation of China (Grant no. Because of its theoretical advantages, it is expected to apply Self-Organizing Feature Map to functional diversity analysis. 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]. The network consists of two layers, .. At the end of the day it was decided that to wrap up all the discussions and move forward into designing the “Internet of Education” conference in 2013 as the yearly flagship conference of Knowledge 4 All Foundation Ltd. Опубликовано 31st May пользователем Vadym Garbuzov. Artificial neural networks, a biologically inspired computing methodology, have the ability to learn by imitating the learning method used in the human brain. Learning theory (supervised/ unsupervised/ reinforcement learning) Knowledge based networks. Ярлыки: tutorials djvu ebook hotfile epub chm filesonic rapidshare Tags:Neural Network Learning: Theoretical Foundations fileserve pdf downloads torrent book. Artificial Neural Networks Mathematical foundations of neural networks. Product DescriptionThis important work describes recent theoretical advances in the study of artificial neural networks.