Tài liệu Independent component analysis P10 doc

... 10 ICA by Minimization of Mutual Information An important approach for independent component analysis (ICA) estimation, in- spired by information theory, is minimization of mutual ... familiar with information theory are advised to read that chapter before this one. 221 Independent Component Analysis. Aapo Hyv ¨ arinen, Juha Karhunen, Erkki Oja Copyright  2001 John Wiley & ......

Ngày tải lên: 26/01/2014, 07:20

... and neural networks have been an inspiration to us over the years. Independent Component Analysis Independent Component Analysis. Aapo Hyv ¨ arinen, Juha Karhunen, Erkki Oja Copyright  2001 ... variables are assumed nongaussian and mutually independent, and they are called the independent components of the observed data. These independent components, also called sources or fa...

Ngày tải lên: 25/01/2014, 20:20

... 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