Considering the Reliability of Measurements Issue in Distributed Adaptive Estimation Algorithms

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Measurements Issue in Distributed Adaptive Estimation Algorithms</title> <meta name="description" content="Considering the Reliability of Measurements Issue in Distributed Adaptive Estimation Algorithms"> <meta name="keywords" content="adaptive filter, distributed estimation, sensor network, IDLMS algorithm"> <meta name="viewport" content="width=device-width, initial-scale=1, minimum-scale=1, maximum-scale=1, user-scalable=no"> <meta charset="utf-8"> <link href="https://cdn.waset.org/favicon.ico" type="image/x-icon" rel="shortcut icon"> <link href="https://cdn.waset.org/static/plugins/bootstrap-4.2.1/css/bootstrap.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/plugins/fontawesome/css/all.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/css/site.css?v=150220211555" rel="stylesheet"> </head> <body> <header> <div class="container"> <nav class="navbar navbar-expand-lg navbar-light"> <a class="navbar-brand" href="https://waset.org"> <img 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publication-listing mt-3 mb-3"> <h5 class="card-header" style="font-size:.9rem">Considering the Reliability of Measurements Issue in Distributed Adaptive Estimation Algorithms</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Wael%20M.%20Bazzi">Wael M. Bazzi</a>, <a href="https://publications.waset.org/abstracts/search?q=Amir%20Rastegarnia"> Amir Rastegarnia</a>, <a href="https://publications.waset.org/abstracts/search?q=Azam%20Khalili"> Azam Khalili</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper we consider the issue of reliability of measurements in distributed adaptive estimation problem. To this aim, we assume a sensor network with different observation noise variance among the sensors and propose new estimation method based on incremental distributed least mean-square (IDLMS) algorithm. The proposed method contains two phases: I) Estimation of each sensors observation noise variance, and II) Estimation of the desired parameter using the estimated observation variances. To deal with the reliability of measurements, in the second phase of the proposed algorithm, the step-size parameter is adjusted for each sensor according to its observation noise variance. As our simulation results show, the proposed algorithm considerably improves the performance of the IDLMS algorithm in the same condition. <iframe src="https://publications.waset.org/abstracts/27648.pdf" style="width:100%; height:400px;" frameborder="0"></iframe> <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=adaptive%20filter" title="adaptive filter">adaptive filter</a>, <a href="https://publications.waset.org/abstracts/search?q=distributed%20estimation" title=" distributed estimation"> distributed estimation</a>, <a href="https://publications.waset.org/abstracts/search?q=sensor%0D%0Anetwork" title=" sensor network"> sensor network</a>, <a href="https://publications.waset.org/abstracts/search?q=IDLMS%20algorithm" title=" IDLMS algorithm"> IDLMS algorithm</a> </p> <a href="https://publications.waset.org/abstracts/27648/considering-the-reliability-of-measurements-issue-in-distributed-adaptive-estimation-algorithms" class="btn 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Considering the Reliability of Measurements Issue in Distributed Adaptive Estimation Algorithms