Independent component analysis P17
Independent component analysis P17
... real- valued m -component mixing function, and s is an n -vector whose elements are the n unknown independent components. Assume now for simplicity that the number of independent components n equals ... consider extension of the linear model to nonlinear mixing models. For instantaneous 315 Independent Component Analysis. Aapo Hyv ¨ arinen, Juha Karhunen, Erkki Oja Copyright 2001...
Independent component analysis P15
... by principal component analysis (PCA); see Sections 13.1.2 and 13.2.2. In noisy ICA, we also encounter a new problem: estimation of the noise-free realizations of the independent components (ICs). ... factor analysis and signal processing, and allows for a simple formulation of the noisy model. Thus, the noisy ICA model can be expressed as x = As + n (15.1) 293 Independent Componen...
Independent component analysis P16
... Overcomplete Bases A difficult problem in independent component analysis (ICA) is encountered if the number of mixtures x i is smaller than the number of independent components s i .This means that the ... the independent components (ICs) by simply inverting the mixing matrix A . Therefore, even if we knew the mixing matrix exactly, we could not recover the exact values of the indep...
Independent component analysis P18
... 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, ... allow for the estimation of the model. These assumptions are alternatives to the
341
Independent Component Analysis. Aapo Hyv
¨
arinen, Juha Karhunen, Erkki Oja
Copyright
200...
Independent component analysis P19
... 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...
Independent component analysis P20
... independence of the components. In the model
called independent subspace analysis, the components are divided into subspaces that
are independent, but the components inside the subspaces are not independent. ... 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 de...
Independent component analysis P21
... into independent
components. One can always obtain uncorrelated components, and this is what we
obtain with FastICA. In image feature extraction, however, one can clearly see that
the ICA components ... Part IV
APPLICATIONS OF ICA
Independent Component Analysis. Aapo Hyv
¨
arinen, Juha Karhunen, Erkki Oja
Copyright
2001 John Wiley & ... subspace is relatively independent of the...
Independent component analysis P22
... 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 growth and great importance; some kinds ... help
in answering the question: What parts of the brain are needed for a given task?
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Independent Component Analysis. Aapo Hyv
¨
arinen, Juha Karhunen, Erkki Oja
Copyright
2001 J...
Independent component analysis P23
... by coding these signals using principal component analysis
[344].
23
Telecommunications
This chapter deals with applications of independent component analysis (ICA) and
blind source separation ... to enable each user of the system to communicate despite the fact that the other
417
Independent Component Analysis. Aapo Hyv
¨
arinen, Juha Karhunen, Erkki Oja
Copyright
2001 John...
Independent component analysis P24
... Applications
In this chapter, we consider some further applications of independent component
analysis (ICA), including analysis of financial time series and audio signal separation.
24.1 FINANCIAL ... time-varying underlying factor or
independent component
s
j
(t)
on the measured time series is approximately linear.
The assumption of having some underlying independent components...
Từ khóa:
- on independent component analysis for multimedia signals
- independent component analysis versus principle component analysis
- independent component analysis for audio and biosignal applications
- introduction independent component analysis
- nonlinear independent component analysis for eeg based brain computer interface systems
- application of polynomial spline independent component analysis to fmri data
- principal component analysis and independent component analysis
- improving probabilistic latent semantic analysis with principal component analysis