Title :
Robust Super-exponential methods for deflationary blind source separation of instantaneous mixtures
Author :
Kawamoto, Mitsuru ; Kohno, Kiyotaka ; Inouye, Yujiro
Author_Institution :
Dept. of Electron. & Control Syst. Eng., Shimane Univ., Nagoya, Japan
fDate :
5/1/2005 12:00:00 AM
Abstract :
The so-called "super-exponential" methods (SEMs) are attractive methods for solving blind signal processing problems. The conventional SEMs, however, have such a drawback that they are very sensitive to Gaussian noise. To overcome this drawback, we propose a new SEM. While the conventional SEMs use the second- and higher order cumulants of observations, the proposed SEM uses only the higher order cumulants of observations. Since higher order cumulants are insensitive to Gaussian noise, the proposed SEM is robust to Gaussian noise, which is referred to as a robust super-exponential method (RSEM). To show the validity of the proposed RSEM, some simulation results are presented.
Keywords :
Gaussian noise; blind source separation; higher order statistics; Gaussian noise; blind signal processing; deflationary blind source separation; higher order cumulant; instantaneous mixture; robust super-exponential method; Blind source separation; Control systems; Filters; Gaussian noise; Independent component analysis; Modeling; Noise robustness; Source separation; Systems engineering and theory; Vectors; Blind source separation; Gaussian noise; deflationary approach; instantaneous mixtures; super-exponential methods;
Journal_Title :
Signal Processing, IEEE Transactions on
DOI :
10.1109/TSP.2005.845491