Title
Independent component analysis in signals with multiplicative noise using fourth-order statistics
Abstract
The existence of multiplicative noise greatly limits the applicability of independent component analysis (ICA), because it does not take into account the existence of the noise. This paper proposes a method to extend ICA to this kind of noisy environment, without any limitation in the nature of the sources or the noise. In order to do this, the statistical structure of a linear transformation of the noisy data is studied up to fourth order, and then this structure is used to find the inverse of the mixing matrix through the minimization of a cost function. The method designed is able to extract the mixing matrix and some statistical features of the noise and the sources, notably improving the performance of the standard ICA methods when the mixture is contaminated by multiplicative noise.
Year
DOI
Venue
2007
10.1016/j.sigpro.2007.01.030
Signal Processing
Keywords
Field
DocType
noisy environment,fourth-order statistic,independent component analysis,multiplicative noise,statistical structure,standard ica method,noisy data,linear transformation,cost function,statistical feature,blind source separation,order statistic
Value noise,Background noise,Noise measurement,Independent component analysis,Statistics,Blind signal separation,Gaussian noise,Multiplicative noise,Mathematics,Gradient noise
Journal
Volume
Issue
ISSN
87
8
Signal Processing
Citations 
PageRank 
References 
1
0.37
10
Authors
4
Name
Order
Citations
PageRank
D. Blanco1101.99
Bernard Mulgrew263989.00
D. P. Ruiz3103.76
M. C. Carrión4214.86