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

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

Bartlett — Neural Network Learning: Theoretical Foundations; M. 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]. Underlying this need is the concept of “ connectionism”, which is concerned with the computational and learning capabilities of assemblies of simple processors, called artificial neural networks. Biggs — Computational Learning Theory; L. Artificial neural networks, a biologically inspired computing methodology, have the ability to learn by imitating the learning method used in the human brain. Download free Neural Networks and Computational Complexity (Progress in Theoretical Computer Science) H. Download free ebooks rapidshare, usenet,bittorrent. This important work describes recent theoretical advances in the study of artificial neural networks. Some titles of books I've been reading in the past two weeks: M. 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. The network consists of two layers, ..