A Fixed-Point Algorithm for Nonnegative Independent Component Analysis

Author

Shi, Zhenwei ; Tan, Xueyan ; Zhu, Zhanxing ; Jiang, Zhiguo

Author_Institution

Sch. of Astronaut., Beijing Univ. of Aeronaut. & Astronaut., Beijing, China

Volume

2

fYear

2009

fDate

14-16 Aug. 2009

Firstpage

482

Lastpage

485

Abstract

This paper proposes a fixed-point algorithm for nonnegative independent component analysis, based on the mutual independency of source signals and `nonpositive´ parts of source signals. The algorithm is computationally simple, provides fast convergence and does not need choose any learning step sizes. Simulations by independent source signals which are nonnegative and well grounded verify the efficient implementation of the proposed method.

Keywords

independent component analysis; signal processing; fast convergence; fixed-point algorithm; independent source signals; nonnegative independent component analysis; Blind source separation; Computational modeling; Convergence; Covariance matrix; Equations; Image processing; Independent component analysis; Signal processing algorithms; Source separation; Speech enhancement; Blind source separation (BSS); fixed-point algorithm; independent component analysis (ICA); nonnegative independent component analysis;

fLanguage

English

Publisher

ieee

Conference_Titel

Natural Computation, 2009. ICNC '09. Fifth International Conference on

Conference_Location

Tianjin

Print_ISBN

978-0-7695-3736-8

Type

conf

DOI

10.1109/ICNC.2009.329

Filename

5366678