DocumentCode :
353201
Title :
Blind identification of colored signals distorted by FIR channels
Author :
Hua, Yingbo ; Xiang, Yong ; Abed-Meraim, Karim
Author_Institution :
Dept. of Electr. & Electron. Eng., Melbourne Univ., Parkville, Vic., Australia
Volume :
5
fYear :
2000
fDate :
2000
Firstpage :
3124
Abstract :
This paper presents a new approach for blind identification of multiple colored stationary/nonstationary signals distorted by unknown FIR channels. The key idea of this approach is to use a bank of decorrelators to transform a multiple-input and multiple output system (driven by the desired signals) into a bank of single-input and single-output systems. This approach is referred to as BID, i.e., blind identification via decorrelation. The BID approach can uniquely (up to a permutation and scaling) identify the signals if (a) the signals are mutually uncorrelated and of distinct power spectra, and (b) each column of the system function is a coprime polynomial vector. No other method known to date can uniquely identify the signals under the above condition. The BID approach achieves the optimal identifiability potential predicted by Hua and Tugnait
Keywords :
MIMO systems; decorrelation; identification; polynomials; signal processing; spectral analysis; transforms; BID approach; FIR channels; blind identification; blind identification via decorrelation; colored signals; coprime polynomial vector; decorrelators; multiple colored nonstationary signals; multiple colored stationary signals; multiple-input multiple output system; optimal identifiability potential; power spectra; single-input single-output systems; transform; Decorrelation; Distortion; Finite impulse response filter; Higher order statistics; Image processing; Image recognition; Polynomials; Signal processing; Speech processing; Speech recognition;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Acoustics, Speech, and Signal Processing, 2000. ICASSP '00. Proceedings. 2000 IEEE International Conference on
Conference_Location :
Istanbul
ISSN :
1520-6149
Print_ISBN :
0-7803-6293-4
Type :
conf
DOI :
10.1109/ICASSP.2000.861199
Filename :
861199
Link To Document :
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