Adaptive filtering of a random signal in Gaussian white noise

Adaptive filtering of a random signal in Gaussian white noise We consider the problem of estimating an infinite-dimensional vector θ observed in Gaussian white noise. Under the condition that components of the vector have a Gaussian prior distribution that depends on an unknown parameter β, we construct an adaptive estimator with respect to β. The proposed method of estimation is based on the empirical Bayes approach. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Problems of Information Transmission Springer Journals

Adaptive filtering of a random signal in Gaussian white noise

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Publisher
SP MAIK Nauka/Interperiodica
Copyright
Copyright © 2008 by Pleiades Publishing, Ltd.
Subject
Engineering; Systems Theory, Control; Information Storage and Retrieval ; Electrical Engineering; Communications Engineering, Networks
ISSN
0032-9460
eISSN
1608-3253
D.O.I.
10.1134/S0032946008040054
Publisher site
See Article on Publisher Site

Abstract

We consider the problem of estimating an infinite-dimensional vector θ observed in Gaussian white noise. Under the condition that components of the vector have a Gaussian prior distribution that depends on an unknown parameter β, we construct an adaptive estimator with respect to β. The proposed method of estimation is based on the empirical Bayes approach.

Journal

Problems of Information TransmissionSpringer Journals

Published: Jan 24, 2009

References

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