Tài liệu Independent component analysis P11 ppt

... the cumulant tensor, we could easily obtain the independent components. If the eigenvalues of the tensor, i.e., the kurtoses of the independent components, are distinct, every eigenmatrix corresponds to ... obtained as linear combinations of the cumulants of . This can be seen using the additive 229 Independent Component Analysis. Aapo Hyv ¨ arinen, Juha Karhunen, Erkki Oja Copyright...

Ngày tải lên: 26/01/2014, 07:20

... standard independent component analysis: it is impossible to estimate the ICA model for gaussian data, that is, one cannot blindly separate Part I MATHEMATICAL PRELIMINARIES Independent Component Analysis. ... usually optimal for gaussian data. For example, independent component analysis does not bring out anything new com- pared with standard principal component analysis...

Ngày tải lên: 21/01/2014, 06:20

... implications in independent component analysis. Al- gebraic, cumulant-based methods proposed for ICA are typically based on estimating fourth-order moments and cross-moments of the components of ... always assumed to be time-invariant. The meth- ods that are widely used in context with independent component analysis (ICA) are emphasized in this chapter. More information on estimati...

Ngày tải lên: 21/01/2014, 06:20

... low-pass filtered the mixed signals, prior to the independent component analysis, using a 10 delay moving average filter. Taking the same amount of principal components as in d,wecanseethatweloseallthe original ... methods that are not necessary in theory, but are often very useful in practice. 263 Independent Component Analysis. Aapo Hyv ¨ arinen, Juha Karhunen, Erkki Oja Copyright ...

Ngày tải lên: 26/01/2014, 07:20

... 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 ... covariance matrix) can be utilized, and therefore, the independent components can be actually separated, which is not possible by PCA and classic factor analysis. Often, the data is prep...

Ngày tải lên: 26/01/2014, 07:20

... 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