By Gustavo Deco,Dragan Obradovic

a close formula of neural networks from the information-theoretic standpoint. The authors convey how this attitude presents new insights into the layout conception of neural networks. specifically they reveal how those equipment will be utilized to the themes of supervised and unsupervised studying, together with characteristic extraction, linear and non-linear self sufficient part research, and Boltzmann machines. Readers are assumed to have a uncomplicated knowing of neural networks, yet all of the suitable innovations from info conception are rigorously brought and defined. for that reason, readers from diverse medical disciplines, significantly cognitive scientists, engineers, physicists, statisticians, and desktop scientists, will locate this an exceptionally helpful creation to this topic.

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An Information-Theoretic Approach to Neural Computing (Perspectives in Neural Computing) by Gustavo Deco,Dragan Obradovic

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