On-line estimation of smooth signals with partial observation

On-line estimation of smooth signals with partial observation The paper concerns the estimation of a smooth signal S(t) and its derivatives in the presence of a noise depending on a small parameter ε based on a partial observation. A nonlinear Kalman-type filter is proposed to perform on-line estimation. For the signal S in a given class of smooth functions, the convergence rate for the estimation risks, as ε → 0, is obtained. It is proved that such rates are optimal in a minimax sense. In contrast to the complete observation case, the rates are reduced, due to incomplete information. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Problems of Information Transmission Springer Journals

On-line estimation of smooth signals with partial observation

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Publisher
Nauka/Interperiodica
Copyright
Copyright © 2006 by Pleiades Publishing, Inc.
Subject
Engineering; Communications Engineering, Networks; Electrical Engineering; Information Storage and Retrieval; Systems Theory, Control
ISSN
0032-9460
eISSN
1608-3253
D.O.I.
10.1134/S0032946006040053
Publisher site
See Article on Publisher Site

Abstract

The paper concerns the estimation of a smooth signal S(t) and its derivatives in the presence of a noise depending on a small parameter ε based on a partial observation. A nonlinear Kalman-type filter is proposed to perform on-line estimation. For the signal S in a given class of smooth functions, the convergence rate for the estimation risks, as ε → 0, is obtained. It is proved that such rates are optimal in a minimax sense. In contrast to the complete observation case, the rates are reduced, due to incomplete information.

Journal

Problems of Information TransmissionSpringer Journals

Published: Jan 24, 2006

References

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