02049    a2200253   4500003000500000005001700005020001800022020002200040040000900062082001300071100002000084245010800104260002900212300002600241440008500267505117100352650003401523700001901557700001501576856006701591942001201658999001901670952010601689Nust20170207154017.0  a0-471-22131-7  a978-0-471-22131-9  cNust1 a519.53541 aHyv䲩nen, Aapo00aIndependent component analysis-(E-BOOK)h[Elektronisk resurs]cAapo Hyv䲩nen, Juha Karhunen, Erkki Oja  aNew York :bWiley,c2002  aPDF-fil (xxi, 481 s.) 0aAdaptive and learning systems for signal processing, communications and control,  a Introduction (Page-1) Part I MATHEMATICAL PRELIMINARIES, 2 Random Vectors and Independence (Page-15) 3 Gradients and Optimization Methods (Page-57) 4 Estimation Theory (Page-77) 5 Information Theory (page-105) 6 Principal Component Analysis and Whitening (page-125), Part II BASIC INDEPENDENT COMPONENT ANALYSIS, 7 What is Independent Component Analysis? (Page-147) 8 ICA by Maximization of Nongaussianity (page-165) 9 ICA by Maximum Likelihood Estimation (page-203) 10 ICA by Minimization of Mutual Information (pag-221) 11 ICA by Tensorial Methods (page-229) 12 ICA by Nonlinear Decorrelation and Nonlinear PCA (page-239) 13 Practical Considerations (page-263) 14 Overview and Comparison of Basic ICA Methods(Page-273) Part III EXTENSIONS AND RELATED METHODS, 15 Noisy ICA (page-293) 16 ICA with Overcomplete Bases (Page-305) 17 Nonlinear ICA (page-315) 18 Methods using Time Structure (page-341) 19 Convolutive Mixtures and Blind Deconvolution (page-355) 20 Other Extensions (page-371) Part IV APPLICATIONS OF ICA, 21 Feature Extraction by ICA (page-391) 22 Brain Imaging Applications (page-407) 23 Telecommunications (page-417) 24 Other Applications (Page-441)  7aPrincipal components analysis1 aKarhunen, Juha1 aOja, Erkki40uhttp://www3.interscience.wiley.com/cgi-bin/booktoc?ID=93520448  2ddccBK  c191468d191468  00102ddc40708NFICaMCSbMCSd2016-12-12l0o519.5354   HYVpMCSEB-741r2016-12-08w2016-12-12yBK