DocumentCode :
2452563
Title :
Independent vector analysis by entropy rate bound minimization
Author :
Geng-Shen Fu ; Anderson, Matthew ; Adali, Tulay
Author_Institution :
Dept. of Comput. Sci. & Electr. Eng., Univ. of Maryland, Baltimore, MD, USA
fYear :
2015
fDate :
18-20 March 2015
Firstpage :
1
Lastpage :
6
Abstract :
An extension of independent component analysis from one to multiple datasets, independent vector analysis, has recently become a subject of significant research interest. Since in many applications, latent sources are non-Gaussian, have sample dependence, and have dependence across multiple data sets, it is desirable to exploit all these properties jointly. Mutual information rate, which leads to the minimization of entropy rate, provides a natural cost for the task. In this paper, we present a new algorithm by using an effective entropy rate estimator, which takes all these properties into account. Experimental results show that the new method accounts for these properties effectively.
Keywords :
entropy; independent component analysis; minimisation; datasets; entropy rate bound minimization; entropy rate estimator; entropy rate minimization; independent component analysis; independent vector analysis; mutual information rate; Brain modeling; Cost function; Data models; Entropy; Joints; Minimization; Mutual information; Entropy rate; Independent vector analysis; Maximum entropy distributions; Mutual information rate; vector autoregressive model;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Sciences and Systems (CISS), 2015 49th Annual Conference on
Conference_Location :
Baltimore, MD
Type :
conf
DOI :
10.1109/CISS.2015.7086842
Filename :
7086842
Link To Document :
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