Information Theoretic Learning
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Information Theoretic Learning
Author | : Jose C. Principe |
Publisher | : Springer Science & Business Media |
Total Pages | : 538 |
Release | : 2010-04-06 |
Genre | : Computers |
ISBN | : 1441915702 |
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This book is the first cohesive treatment of ITL algorithms to adapt linear or nonlinear learning machines both in supervised and unsupervised paradigms. It compares the performance of ITL algorithms with the second order counterparts in many applications.
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A detailed formulation of neural networks from the information-theoretic viewpoint. The authors show how this perspective provides new insights into the design