DocumentCode
478182
Title
Generalized Complexity Pursuit
Author
Shi, Zhenwei ; Jiang, Zhiguo ; Yin, Jihao
Author_Institution
Sch. of Astronaut., Beijing Univ. of Aeronaut. & Astronaut., Beijing
Volume
3
fYear
2008
fDate
18-20 Oct. 2008
Firstpage
199
Lastpage
203
Abstract
In this paper, we study the blind source separation (BSS) problem of temporally correlated signals via exploring the nonlinear temporal structure and high-order statistics of source signals. A BSS method based on the nonlinear predictability of original sources is proposed, which extends linear coding complexity used by the original complexity pursuit to nonlinear coding complexity. Simulations by nonstationarity sources verify the efficient implementation of the proposed method, especially its robustness to the outliers.
Keywords
blind source separation; encoding; linear codes; blind source separation; generalized complexity pursuit; linear coding complexity; nonlinear temporal structure; temporally correlated signals; Blind source separation; Data analysis; Image coding; Image processing; Independent component analysis; Predictive models; Source separation; Speech analysis; Statistics; Vectors; blind source separation (BSS); generalized complexitypursuit algorithm (GCP);
fLanguage
English
Publisher
ieee
Conference_Titel
Natural Computation, 2008. ICNC '08. Fourth International Conference on
Conference_Location
Jinan
Print_ISBN
978-0-7695-3304-9
Type
conf
DOI
10.1109/ICNC.2008.650
Filename
4667130
Link To Document