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Mobile Agent Based Distributed EM Algorithm For Data Clustering In Sensor Networks


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Abstract

In this paper, a mobile agent based distributed EM (Expectation Maximization) algorithm is developed for density estimation and data clustering in sensor networks. It has been assumed that sensor measurements can be statistically modeled by a common Gaussian mixture model. This algorithm not only executes the EM algorithm in a distributed manner, but reduces the number of iterations of the EM algorithm and increases its convergence rate. Convergence of the proposed method will also be studied analytically and will be shown that the estimated parameters will eventually converge to their true values. Finally, the proposed method will be applied to synthetic data sets in order to show its promising performance.


Keywords


Pages

Total Pages: 16
Pages: 45-60

DOI
10.1080/10798587.2015.1039246


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Published

Volume: 22
Issue: 1
Year: 2015

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JOURNAL INFORMATION


ISSN PRINT: 1079-8587
ISSN ONLINE: 2326-005X
DOI PREFIX: 10.31209
10.1080/10798587 with T&F
IMPACT FACTOR: 0.652 (2017/2018)
Journal: 1995-Present




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