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Information Theoretic Learning (Record no. 21009)

000 -LEADER
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003 - CONTROL NUMBER IDENTIFIER
control field OSt
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20140310151109.0
007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION
fixed length control field cr nn 008mamaa
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fixed length control field 100427s2010 xxu| s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781441915702
978-1-4419-1570-2
050 #4 - LIBRARY OF CONGRESS CALL NUMBER
Classification number TK5102.9
Classification number TA1637-1638
Classification number TK7882.S65
082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 621.382
Edition number 23
264 #1 -
-- New York, NY :
-- Springer New York :
-- Imprint: Springer,
-- 2010.
912 ## -
-- ZDB-2-SCS
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Principe, Jose C.
Relator term author.
245 10 - IMMEDIATE SOURCE OF ACQUISITION NOTE
Title Information Theoretic Learning
Medium [electronic resource] :
Remainder of title Renyi's Entropy and Kernel Perspectives /
Statement of responsibility, etc by Jose C. Principe.
300 ## - PHYSICAL DESCRIPTION
Extent XIV, 448p.
Other physical details online resource.
440 1# - SERIES STATEMENT/ADDED ENTRY--TITLE
Title Information Science and Statistics,
International Standard Serial Number 1613-9011
505 0# - FORMATTED CONTENTS NOTE
Formatted contents note 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.
520 ## - SUMMARY, ETC.
Summary, etc This book presents the first cohesive treatment of Information Theoretic Learning (ITL) algorithms to adapt linear or nonlinear learning machines both in supervised or unsupervised paradigms. ITL is a framework where the conventional concepts of second order statistics (covariance, L2 distances, correlation functions) are substituted by scalars and functions with information theoretic underpinnings, respectively entropy, mutual information and correntropy. ITL quantifies the stochastic structure of the data beyond second order statistics for improved performance without using full-blown Bayesian approaches that require a much larger computational cost. This is possible because of a non-parametric estimator of Renyi’s quadratic entropy that is only a function of pairwise differences between samples. The book compares the performance of ITL algorithms with the second order counterparts in many engineering and machine learning applications. Students, practitioners and researchers interested in statistical signal processing, computational intelligence, and machine learning will find in this book the theory to understand the basics, the algorithms to implement applications, and exciting but still unexplored leads that will provide fertile ground for future research. José C. Principe is Distinguished Professor of Electrical and Biomedical Engineering, and BellSouth Professor at the University of Florida, and the Founder and Director of the Computational NeuroEngineering Laboratory. He is an IEEE and AIMBE Fellow, Past President of the International Neural Network Society, Past Editor-in-Chief of the IEEE Trans. on Biomedical Engineering and the Founder Editor-in-Chief of the IEEE Reviews on Biomedical Engineering. He has written an interactive electronic book on Neural Networks, a book on Brain Machine Interface Engineering and more recently a book on Kernel Adaptive Filtering, and was awarded the 2011 IEEE Neural Network Pioneer Award.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Engineering.
Topical term or geographic name as entry element Remote sensing.
Topical term or geographic name as entry element Engineering.
Topical term or geographic name as entry element Signal, Image and Speech Processing.
Topical term or geographic name as entry element Computational Intelligence.
Topical term or geographic name as entry element Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences.
Topical term or geographic name as entry element Remote Sensing/Photogrammetry.
710 2# - ADDED ENTRY--CORPORATE NAME
Corporate name or jurisdiction name as entry element SpringerLink (Online service)
773 0# - HOST ITEM ENTRY
Title Springer eBooks
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Display text Printed edition:
International Standard Book Number 9781441915696
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier http://dx.doi.org/10.1007/978-1-4419-1570-2
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme
Item type E-Book
Copies
Price effective from Permanent location Date last seen Not for loan Date acquired Source of classification or shelving scheme Koha item type Damaged status Lost status Withdrawn status Current location Full call number
2014-04-08AUM Main Library2014-04-08 2014-04-08 E-Book   AUM Main Library621.382
Languages: 
English |
العربية