A systematic exploration of both classic and contemporary
algorithms in blind source separation with practical case studies
The book presents an overview of Blind Source Separation, a
relatively new signal processing method. Due to the
multidisciplinary nature of the subject, the book has been written
so as to appeal to an audience from very different backgrounds.
Basic mathematical skills (e.g. on matrix algebra and foundations
of probability theory) are essential in order to understand the
algorithms, although the book is written in an introductory,
accessible style. This book offers a general overview of the basics
of Blind Source Separation, important solutions and algorithms, and
in-depth coverage of applications in 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 geoanomalies information recognition. Firstly, the
background and theory basics of blind source separation are
introduced, which provides the foundation for the following work.
Matrix operation, foundations of probability theory and information
theory basics are included here. There follows the fundamental
mathematical model and fairly new but relatively established blind
source separation algorithms, such as Independent Component
Analysis (ICA) and its improved algorithms (Fast ICA, Maximum
Likelihood ICA, Overcomplete ICA, Kernel ICA, Flexible ICA,
Non-negative ICA, Constrained ICA, Optimised ICA). The last part of
the book considers the very recent algorithms in BSS e.g. Sparse
Component Analysis (SCA) and Non-negative Matrix Factorization
(NMF). Meanwhile, in-depth cases are presented for each algorithm
in order to help the reader understand the algorithm and its
application field. * A systematic exploration of both classic and
contemporary algorithms in blind source separation with practical
case studies * Presents new improved algorithms aimed at different
applications, such as image feature extraction, remote sensing
image fusion, mixed-pixel decomposition of SAR images, image object
recognition, and MRI medical image processing * With applications
in geochemical and geophysical data mining, mineral resources
prediction and geoanomalies information recognition * Written by an
expert team with accredited innovations in blind source separation
and its applications in natural science * Accompanying website
includes a software system providing codes for most of the
algorithms mentioned in the book, enhancing the learning experience
Essential reading for postgraduate students and researchers engaged
in the area of signal processing, data mining, image processing and
recognition, information, geosciences, life sciences.
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