Information Theoretic Learning

Renyi's Entropy and Kernel Perspectives

von Jose C Principe

448 Seiten, Hardcover

Kurzbeschreibung des Verlags

Information Theory, Machine Learning, and Reproducing Kernel Hilbert Spaces.- Renyi's Entropy, Divergence and Their Nonparametric Estimators.- Adaptive Information Filtering with Error Entropy and Error Correntropy Criteria.- Algorithms for Entropy and Correntropy Adaptation with Applications to Linear Systems.- Nonlinear Adaptive Filtering with MEE, MCC, and Applications.- Classification with EEC, Divergence Measures, and Error Bounds.- Clustering with ITL Principles.- Self-Organizing ITL Principles for Unsupervised Learning.- A Reproducing Kernel Hilbert Space Framework for ITL.- Correntropy for Random Variables: Properties and Applications in Statistical Inference.- Correntropy for Random Processes: Properties and Applications in Signal Processing.

• Themen: Informatik und Informationstechnologie Informatik Künstliche Intelligenz (KI)
• ISBN: 9781441915696
• Sprache: Englisch
• Erscheinungsdatum: 15.04.2010
• Größe: 244 x 167 mm
• Verlag: Springer New York