System Parameter Identification: Information Criteria and Algorithms

Recently, criterion functions based on information theoretic measures (entropy, mutual information, information divergence) have attracted attention and become an emerging area of study in signal processing and system identification domain. This book presents a systematic framework for system identification and information processing, investigating system identification from an information theory point of view. The book is divided into six chapters, which cover the information needed to understand the theory and application of system parameter identification. The authors’ research provides a base for the book, but it incorporates the results from the latest international research publications.

Named a 2013 Notable Computer Book for Information Systems by Computing ReviewsOne of the first books to present system parameter identification with information theoretic criteria so readers can track the latest developmentsContains numerous illustrative examples to help the reader grasp basic methods

1.Introduction
2.Information Measures
3.Information Theoretic Estimation
4.System Identification Under Minimum Error Entropy Criteria
5.System Identification Under Information Divergence Criteria
6.System Identification Based on Mutual Information Criteria