Waveform-preserving blind estimation of multiple independent sources
IEEE Transactions on Signal ProcessingPublished 1 July 1993
Lang Tong, Yasushi Inouye, R.-w. Liu
Citations197
SJR quartileQ1
SJR score2.05
SNIP2.36
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TL;DR
It is shown that the minimum-variance unbiased estimates can be obtained if and only if the transmission channel can be identified blindly, which 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.
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
Computer Science
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