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Convergence of a distributed parameter estimator for sensor networks with local averaging of the estimates | IEEE Conference Publication | IEEE Xplore

Convergence of a distributed parameter estimator for sensor networks with local averaging of the estimates

Publisher: IEEE

Abstract:

The paper addresses the convergence of a decentralized Robbins-Monro algorithm for networks of agents. This algorithm combines local stochastic approximation steps for fi...View more

Abstract:

The paper addresses the convergence of a decentralized Robbins-Monro algorithm for networks of agents. This algorithm combines local stochastic approximation steps for finding the root of an objective function, and a gossip step for consensus seeking between agents. We provide verifiable sufficient conditions on the stochastic approximation procedure and on the network so that the decentralized Robbins-Monro algorithm converges to a consensus. We also prove that the limit points of the algorithm correspond to the roots of the objective function. We apply our results to Maximum Likelihood estimation in sensor networks.
Date of Conference: 22-27 May 2011
Date Added to IEEE Xplore: 11 July 2011
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ISSN Information:

Publisher: IEEE
Conference Location: Prague, Czech Republic

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