DocumentCode :
893192
Title :
Maximum a posteriori estimation of multichannel Bernoulli-Gaussian sequences
Author :
Dai, Guan-Zhong ; Mendel, Jerry M.
Volume :
35
Issue :
1
fYear :
1989
fDate :
1/1/1989 12:00:00 AM
Firstpage :
181
Lastpage :
183
Abstract :
General problems and solutions are described for maximum a posteriori estimation of multichannel Bernoulli-Gaussian sequences, which are inputs to a linear discrete-time multivariable system. The authors first develop a separation principle, which indicates that one can estimate multichannel Gaussian amplitudes and Bernoulli events separately. They then discuss approaches for estimation of these quantities
Keywords :
discrete time systems; estimation theory; information theory; linear systems; multivariable systems; Bernoulli events; information theory; linear discrete-time multivariable system; maximum a posteriori estimation; multichannel Bernoulli-Gaussian sequences; multichannel Gaussian amplitudes; separation principle; Amplitude estimation; Computer science; Deconvolution; Gaussian noise; Helium; MIMO; Maximum a posteriori estimation; Noise measurement; State estimation; Vectors;
fLanguage :
English
Journal_Title :
Information Theory, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9448
Type :
jour
DOI :
10.1109/18.42189
Filename :
42189
Link To Document :
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