Tài liệu Independent component analysis P7 docx

... IS INDEPENDENT COMPONENT ANALYSIS? 7.1 Show that given a random vector , there is only one symmetric positive semidefinite whitening Part II BASIC INDEPENDENT COMPONENT ANALYSIS Independent Component ... vertical axis: . s n 158 WHAT IS INDEPENDENT COMPONENT ANALYSIS? Fig. 7.9 The joint distribution of the observed mixtures and , obtained from super- gaussian independe...

Ngày tải lên: 26/01/2014, 07:20

... supergaussian independent components, the pdf defined by (9.9) is usually used. This means that the component- wise nonlinearity is the tanh function: (9.18) For subgaussian independent components, ... the nature o f the independent components, and converges f ast to the maximum lik elihood solution. Here, the sol ution was found in 2 iterations for subgaussian independent components....

Ngày tải lên: 26/01/2014, 07:20

... sources corresponding to the independent components fell on the brain regions expected to be activated by the particular stimulus. Applications of ICA have been proposed for analysis of other kinds ... interpretation of their properties. This is a very promising area of application for independent component analysis (ICA). Not only is this an area of rapid g rowth and great importan...

Ngày tải lên: 20/01/2014, 11:20

... showing how to estimate the independent components one- by-one. This is possible by a deflationary orthogonalization of the estimates of the individual independent components. With every estimation ... the classic optimization methods, for example, (stochastic) gradient methods and Newton 273 Independent Component Analysis. Aapo Hyv ¨ arinen, Juha Karhunen, Erkki Oja Copyright  2001...

Ngày tải lên: 23/12/2013, 07:19

... Overcomplete Bases A difficult problem in independent component analysis (ICA) is encountered if the number of mixtures is smaller than the number of independent components .This means that the mixing ... obtain the independent components (ICs) by simply inverting the mixing matrix . Therefore, even if we knew the mixing matrix exactly, we could not recover the exact values of the i...

Ngày tải lên: 20/01/2014, 11:20

... unknown real- valued -component mixing function, and is an -vector whose elements are the unknown independent components. Assume now for simplicity that the number of independent components equals the ... quite nonlinear, because nonlinear factor analysis is able to explain the data with 10 components equally well as linear factor analysis (PCA) with 21 components. Different numbers...

Ngày tải lên: 20/01/2014, 11:20

... minimization. 18 Methods using Time Structure The model of independent component analysis (ICA) that we have considered so far consists of mixing independent random variables, usually linearly. In many applications, ... that the components of the vector (18.3) are white, is not enough to estimate the independent components. This is because there is an infinity of different matrices t...

Ngày tải lên: 20/01/2014, 11:20

... convolutive mixtures. Blind deconvolution is a signal processing problem that is closely related to basic independent component analysis (ICA) and blind source separation (BSS). In com- munications and related areas, ... and after that separation of convolutive mixtures. Many techniques for convolutive mix- 355 Independent Component Analysis. Aapo Hyv ¨ arinen, Juha Karhunen, Erkki...

Ngày tải lên: 20/01/2014, 11:20

... by independent subspaces analysis, to be explained next. 20.2.2 Independent subspace analysis Independent subspace analysis [204] is a simple model that models some dependen- cies between the components. ... independence of the components. In the model called independent subspace analysis, the components are divided into subspaces that are independent, but the components inside...

Ngày tải lên: 20/01/2014, 11:20