DocumentCode
2428087
Title
Alternate Objective Functions for Independent Component Analysis
Author
Rajan, P.K. ; Santurri, E. ; Thang Vo
Author_Institution
Tennessee Tech Univ., Cookeville, TN
fYear
2007
fDate
4-6 March 2007
Firstpage
326
Lastpage
329
Abstract
To separate linearly mixed signals which are statistically independent, minimization of objective functions that characterize the independence of the components is employed. Kurtosis, entropy and likelihood functions are some of the functions employed as objective functions. In this paper, directly applying the condition for independence of random signals, alternate objective functions are developed. The suitability of these functions for independent component analysis is investigated.
Keywords
entropy; independent component analysis; signal processing; entropy; independent component analysis; kurtosis; likelihood functions; linearly mixed signals; objective function minimization; objective functions; Blind source separation; Entropy; Equations; Hydrogen; Independent component analysis; Microphones; Mutual information; Optimization methods; Signal processing algorithms; Source separation;
fLanguage
English
Publisher
ieee
Conference_Titel
System Theory, 2007. SSST '07. Thirty-Ninth Southeastern Symposium on
Conference_Location
Macon, GA
ISSN
0094-2898
Print_ISBN
1-4244-1126-2
Electronic_ISBN
0094-2898
Type
conf
DOI
10.1109/SSST.2007.352375
Filename
4160861
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