DocumentCode :
437023
Title :
Relative gradient on SO(N): case of source separation
Author :
Su Yong ; Zhongfu, Ye
Author_Institution :
Dept. of EEIS, Univ. of Sci. & Technol. of China, Hefei, China
Volume :
1
fYear :
2004
fDate :
31 Aug.-4 Sept. 2004
Firstpage :
459
Abstract :
Whitening is a popular method to reduce the complexity of the problems in ICA. In the linear instantaneous mixing model, the search space of the separation matrix is restricted to the special orthogonal group SO(N) by the prewhitening of the observations. This paper proposes a new learning rule in blind source separation using RGOSOG (relative gradient on SO(N)) method. We show that when the contrast function is the Renyi´s mutual information (RMI), the algorithm based on RGOSOG is easier to implement and the complexity of RGOSOG method is less than that of the conventional gradient descent method. Simulation illustrate that the new algorithm has the same performance on signal-to-distortion ratio as the conventional one.
Keywords :
blind source separation; computational complexity; distortion; gradient methods; matrix algebra; Renyi mutual information; blind source separation; complexity reduction; contrast function; conventional gradient descent method; learning rule; linear instantaneous mixing model; relative gradient on SO(N); search space; separation matrix; signal-to-distortion ratio; special orthogonal group; Argon; Computer aided software engineering; DH-HEMTs; Eigenvalues and eigenfunctions; Independent component analysis; Petroleum; Source separation; Stochastic processes;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Signal Processing, 2004. Proceedings. ICSP '04. 2004 7th International Conference on
Print_ISBN :
0-7803-8406-7
Type :
conf
DOI :
10.1109/ICOSP.2004.1452681
Filename :
1452681
Link To Document :
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