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Optimal Sensor Design and Zero-Delay Source Coding for Continuous-Time Vector Gauss-Markov Processes
KTH, School of Electrical Engineering (EES).ORCID iD: 0000-0002-7926-5081
2017 (English)In: 2017 IEEE 56TH ANNUAL CONFERENCE ON DECISION AND CONTROL (CDC), IEEE , 2017Conference paper, Published paper (Refereed)
Abstract [en]

We consider the situation in which a continuoustime vector Gauss-Markov process is observed through a vector Gaussian channel (sensor) and estimated by the Kalman-Bucy filter. Unlike in standard filtering problems where a sensor model is given a priori, we are concerned with the optimal sensor design by which (i) the mutual information between the source random process and the reproduction (estimation) process is minimized, and (ii) the minimum mean-square estimation error meets a given distortion constraint. We show that such a sensor design problem is tractable by semidefinite programming. The connection to zero-delay source-coding is also discussed.

Place, publisher, year, edition, pages
IEEE , 2017.
Series
IEEE Conference on Decision and Control, ISSN 0743-1546
National Category
Computer and Information Sciences
Identifiers
URN: urn:nbn:se:kth:diva-223871DOI: 10.1109/CDC.2017.8264246ISI: 000424696903137Scopus ID: 2-s2.0-85046260388ISBN: 978-1-5090-2873-3 (print)OAI: oai:DiVA.org:kth-223871DiVA, id: diva2:1187662
Conference
IEEE 56th Annual Conference on Decision and Control (CDC), DEC 12-15, 2017, Melbourne, AUSTRALIA
Note

QC 20180305

Available from: 2018-03-05 Created: 2018-03-05 Last updated: 2018-11-19Bibliographically approved

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Skoglund, Mikael

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  • apa
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  • de-DE
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  • nn-NB
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  • Other locale
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Output format
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