Blind source separation : theory and applications / Xianchuan Yu, Dan Hu and Jindong Xu.

Format:

Book

Author/Creator:

Yu, Xianchuan, author.

Hu, Dan, Ph.D., author.

Xu, Jindong, author.

Contributor:

ebrary, Inc.

Language:

English

Subjects (All):

Blind source separation.

Physical Description:

1 online resource ( xviii, 366 pages.)

Place of Publication:

Singapore : John Wiley & Sons Singapore Pte. Ltd., [2014]

System Details:

text file

Summary:

Blind source separation is a relatively new signal processing method combining artificial neural networks, statistical information processing and information theory. It has tremendous potential in applications such as processing of speech, image, and biomedical signals. The technique excels in signal extraction, enhancement, denoising, model reduction and classification problems. This book provides an overview of the basics of blind source separation along with important solutions and algorithms. Applications are also covered in-depth, including image feature extraction, remote sensing image fusion, mixed-pixel decomposition of SAR images, image object recognition, fMRI medical image processing, geochemical and geophysical data mining, mineral resources prediction and geo-anomalies information recognition. Given the multidisciplinary nature of the subject the book has been written in an accessible style so as to appeal to readers from very different backgrounds. Gives a systematic exploration of both classic and contemporary algorithms in blind source separation with practical case studies, Written by an expert team with innovations in blind source separation and its applications in natural science, Codes for most of the algorithms mentioned in the book available from the author This book is aimed at graduate students and researchers engaged in the areas of signal processing, data mining, image processing and recognition, computational geosciences, computational life sciences, and other field sciences. Book jacket.

Contents:

PART I. Theory basics of BSS

Mathematical foundation of blind source separation

General model and classical algorithm for BSS

Evaluation criteria for the bss algorithm

PART II. Independent component analysis

Independent component analysis

Fast independent component analysis and its application

Maximum likelihood independent component analysis and its application

Overcomplete independent component analysis algorithms and applications

Kernel independent component analysis

Non-negative independent component analysis and its application

Constraint independent component analysis algorithms and applications

Optimized independent component analysis algorithms and applications

Supervised learning independent component analysis algorithms and applications

PART III. Advances and applications of BSS

Non-negative matrix factorization algorithms and applications

Sparse component analysis and applications

Glossary.

Notes:

Includes bibliographical references and index.

Electronic reproduction. Palo Alto, Calif. Available via World Wide Web.

Description based on online resource; title from digital title page (viewed on April 16, 2014).

Other Format:

Print version: Yu, Xianchuan. Blind source separation

ISBN:

9781118679852

9781118679869

1118679865

1118679857

9781118679876

1118679873

Access Restriction:

Restricted for use by site license. Single-user access only.