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040 _aDLC
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019 _a868491293
_a908035446
020 _a9781118679869
_q(Adobe PDF)
020 _a1118679865
_q(Adobe PDF)
020 _a9781118679876
_q(ePub)
020 _a1118679873
_q(ePub)
020 _a9781118679852
_q(electronic book)
020 _a1118679857
_q(electronic book)
020 _z9781118679845
_q(cloth)
020 _z1118679849
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035 _a(OCoLC)855858321
_z(OCoLC)868491293
_z(OCoLC)908035446
042 _apcc
050 0 0 _aTK5102.9
072 7 _aTEC
_x009070
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082 0 0 _a621.382/2
_223
049 _aMAIN
100 1 _aYu, Xianchuan.
245 1 0 _aBlind source separation :
_btheory and applications /
_cXianchuan Yu, Dan Hu, Jindong Xu.
264 1 _aSingapore :
_bJohn Wiley & Sons Singapore Pte. Ltd.,
_c2014.
300 _a1 online resource (xix, 366 pages)
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
504 _aIncludes bibliographical references and index.
505 0 _aPART 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.
588 0 _aPrint version record and CIP data provided by publisher.
520 _a"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"--Provided by publisher.
650 0 _aBlind source separation.
650 7 _aTECHNOLOGY & ENGINEERING
_xMechanical.
_2bisacsh
650 7 _aBlind source separation.
_2fast
_0(OCoLC)fst01739925
650 4 _aBlind source separation
_xHandbooks, manuals, etc.
650 4 _aBlind source separation.
655 4 _aElectronic books.
655 0 _aElectronic books.
700 1 _aHu, Dan,
_cPh.D.
700 1 _aXu, Jindong.
776 0 8 _iPrint version:
_aYu, Xianchuan.
_tBlind source separation.
_dSingapore : John Wiley & Sons Singapore Pte. Ltd., 2014
_z9781118679845
_w(DLC) 2013031750
_w(OCoLC)855858254
856 4 0 _uhttp://onlinelibrary.wiley.com/book/10.1002/9781118679852
_zWiley Online Library [Free Download only for SUST IP]
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