Information Theoretic Learning: Renyi's Entropy and Kernel Perspectives (Information Science and Statistics)

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.