NDLI: The decentralized estimation of the sample covariance

Content Provider	IEEE Xplore Digital Library
Author	Scaglione, A. Pagliari, R. Krim, H.
Copyright Year	2008
Description	Author affiliation: Sch. of Electr. & Comput. Eng., Cornell Univ., Ithaca, NY (Scaglione, A.; Pagliari, R.; Krim, H.)
Abstract	In this paper we consider the problem of estimating the eigenvectors of the sample covariance matrix of decentralized measurements in a distributed fashion. The need for a distributed scheme is motivated by the many moment based methods that resort to the covariance of the data to extract information from the measurements. For large sensor network, gathering the data at a central processor generates a communication bottleneck. Our algorithm is based on a combination of the so called power method, that is used to compute the eigenvectors, and the average consensus protocol, that is utilized to structure the information exchange into a gossiping protocol. Our work shows how a completely distributed scheme based on near neighbors communications is feasible, and applies the proposed method to the estimation of the direction of arrival of a signal source.
Starting Page	1722
Ending Page	1726
File Size	250428
Page Count	5
File Format	PDF
ISBN	9781424429400
ISSN	10586393
DOI	10.1109/ACSSC.2008.5074720
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-10-26
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Protocols Covariance matrix Routing Distributed computing Direction of arrival estimation Statistical distributions State estimation Data mining Computer architecture Computer network management
Content Type	Text
Resource Type	Article
Subject	Signal Processing Computer Networks and Communications

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