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

机译:传感器网络中基于移动代理的分布式EM算法

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摘要

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.
机译:本文针对传感器网络中的密度估计和数据聚类,开发了一种基于移动代理的分布式EM(期望最大化)算法。已经假定可以通过普通的高斯混合模型对传感器的测量值进行统计建模。该算法不仅以分布式方式执行EM算法,而且减少了EM算法的迭代次数并提高了收敛速度。拟议方法的收敛性也将进行分析研究,结果表明估计的参数最终将收敛至其真实值。最后,提出的方法将应用于合成数据集,以显示其有希望的性能。

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