DocumentCode :
925170
Title :
Waveform-preserving blind estimation of multiple independent sources
Author :
Tong, Lang ; Inouye, Yujiro ; Liu, Ruey-wen
Author_Institution :
Dept. of Electr. & Comput. Eng., West Virginia Univ., Morgantown, WV, USA
Volume :
41
Issue :
7
fYear :
1993
fDate :
7/1/1993 12:00:00 AM
Firstpage :
2461
Lastpage :
2470
Abstract :
The problem of blind estimation of source signals is to estimate the source signals without knowing the characteristics of the transmission channel. It is shown that the minimum-variance unbiased estimates can be obtained if and only if the transmission channel can be identified blindly. It is shown that the channel can be blindly identified if and only if there is not more than one Gaussian source. This condition suggests that waveform-preserving blind estimation can be achieved over a wide range of signal processing applications, including those cases in which the source signals have identical nonGaussian distributions. The constructive proof of the necessary and sufficient condition serves as a foundation for the development of waveform-preserving blind signal estimation algorithms. Examples are presented to demonstrate the applications of the theoretical results
Keywords :
parameter estimation; signal processing; Gaussian source; blind channel identification; minimum-variance unbiased estimates; multiple independent sources; nonGaussian distributions; signal estimation algorithms; signal processing; transmission channel; waveform-preserving blind estimation; Array signal processing; Estimation; Gaussian distribution; Image restoration; Multiple signal classification; Sensor arrays; Signal processing; Signal processing algorithms; Signal restoration; Sufficient conditions;
fLanguage :
English
Journal_Title :
Signal Processing, IEEE Transactions on
Publisher :
ieee
ISSN :
1053-587X
Type :
jour
DOI :
10.1109/78.224254
Filename :
224254
Link To Document :
بازگشت