Neural Network Learning: Theoretical Foundations. Martin Anthony, Peter L. Bartlett
ISBN: 052111862X,9780521118620 | 404 pages | 11 Mb
Neural Network Learning: Theoretical Foundations Martin Anthony, Peter L. Bartlett
Some titles of books I've been reading in the past two weeks: M. Bartlett — Neural Network Learning: Theoretical Foundations; M. Biggs — Computational Learning Theory; L. 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, .. 20120003110024) and the National Natural Science Foundation of China (Grant no. Ci-dessous donc la liste de mes bouquins favoris sur le sujet:A theory of learning an… Hébergé par OverBlog. Neural Network Learning: Theoretical foundations, M. Cheap This important work describes recent theoretical advances in the study of artificial neural networks.