Paisarn Muneesawang, Ling Guan9780387256276, 0-387-25627-X
Highlights include:
* Exploring an adaptive machine that can learn from its environment
* Optimizing the learning system by incorporating self-organizing adaptation into the retrieval process
* Demonstrating state-of-the-art applications within small, medium, and large databases
The authors also include applications related to Digital Asset Management (DAM), Computer Aided Referral (CAR) System, Geographical Database Retrieval, retrieval of Art Documents, and Films and Video Retrieval.
Multimedia Database Retrieval: A Human-Centered Approach presents the fundamental and advanced aspects of these topics, as well as the philosophical directions in the field. The methods detailed in this book possess broad applications which will advance the technology in this fast developing topical area.
Table of contents :
cover-image.pdf……Page 1
front-matter.pdf……Page 2
PREFACE……Page 7
CONTENTS……Page 11
1 Introduction to Nonlinear Systems.pdf……Page 14
2 Polynomial Models of Nonlinear Systems.pdf……Page 31
3 Volterra and Wiener Nonlinear Models.pdf……Page 51
4 Nonlinear System Identification Methods.pdf……Page 89
5 Introduction to Adaptive Signal Processing.pdf……Page 97
6 Nonlinear Adaptive System Identification Based on Volterra Models.pdf……Page 127
7 Nonlinear Adaptive System Identification Based on Wiener Models (Part 1).pdf……Page 141
8 Nonlinear Adaptive System Identification Based on Wiener Models (Part 2).pdf……Page 170
9 Nonlinear Adaptive System Identification Based on Wiener Models (Part 3).pdf……Page 197
10 Nonlinear Adaptive System Identification Based on Wiener Models (Part 4).pdf……Page 208
11 Conclusions, Recent Results, and New Directions.pdf……Page 222
REFERENCES……Page 225
INDEX……Page 233
Reviews
There are no reviews yet.