DocumentCode :
2546496
Title :
Robust super-exponential methods for blind deconvolution of MIMO-IIR systems with Gaussian noise
Author :
Kohno, Kiyotaka ; Inouye, Y. ; Kawamoto, Mitsuru
Author_Institution :
Dept. of Electron. & Control Syst. Eng., Shimane Univ.
fYear :
2006
fDate :
21-24 May 2006
Abstract :
The so called "super-exponential" methods (SEMs) are attractive methods for solving multichannel blind deconvolution problem. The conventional SEMs, however, have such a drawback that they are very sensitive to Gaussian noise. To overcome this drawback, the robust super-exponential method (RSEM) was proposed for single-input single-output infinite impulse response (SISO-IIR) channels and for multi-input multi-output (MIMO) static channels (instantaneous mixtures). While the conventional SEMs use the second- and higher-order cumulants of observations, the RSEM uses only the higher-order cumulants of observations. Since higher-order cumulants are insensitive to Gaussian noise, the RSEM is robust to Gaussian noise. We proposed an RSEM extended to the case of MIMO-IIR channels (convolutive mixtures). To show the validity of the proposed RSEM, some simulation results are presented
Keywords :
Gaussian noise; MIMO systems; blind source separation; deconvolution; telecommunication channels; Gaussian noise; MIMO-IIR channels; MIMO-IIR systems; SISO-IIR channels; convolutive mixtures; higher-order cumulants; multichannel blind deconvolution; multiinput multioutput static channels; robust super-exponential methods; second-order cumulants; single-input single-output infinite impulse response; Centralized control; Control systems; Deconvolution; Gaussian noise; Independent component analysis; Industrial electronics; MIMO; Noise robustness; Robust control; Signal processing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Circuits and Systems, 2006. ISCAS 2006. Proceedings. 2006 IEEE International Symposium on
Conference_Location :
Island of Kos
Print_ISBN :
0-7803-9389-9
Type :
conf
DOI :
10.1109/ISCAS.2006.1693405
Filename :
1693405
Link To Document :
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