The Effect of Measurement Distribution on System Identification and Detection of Behavior of Nonlinearities of Data

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Distribution on System Identification and Detection of Behavior of Nonlinearities of Data</title> <meta name="description" content="The Effect of Measurement Distribution on System Identification and Detection of Behavior of Nonlinearities of Data"> <meta name="keywords" content="Gaussian process, nonlinearity distribution, particle filter, system identification"> <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 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87480</div> </div> </div> </div> <div class="card publication-listing mt-3 mb-3"> <h5 class="card-header" style="font-size:.9rem">The Effect of Measurement Distribution on System Identification and Detection of Behavior of Nonlinearities of Data</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mohammad%20Javad%20Mollakazemi">Mohammad Javad Mollakazemi</a>, <a href="https://publications.waset.org/abstracts/search?q=Farhad%20Asadi"> Farhad Asadi</a>, <a href="https://publications.waset.org/abstracts/search?q=Aref%20Ghafouri"> Aref Ghafouri</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, we considered and applied parametric modeling for some experimental data of dynamical system. In this study, we investigated the different distribution of output measurement from some dynamical systems. Also, with variance processing in experimental data we obtained the region of nonlinearity in experimental data and then identification of output section is applied in different situation and data distribution. Finally, the effect of the spanning the measurement such as variance to identification and limitation of this approach is explained. <iframe src="https://publications.waset.org/abstracts/17632.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=Gaussian%20process" title="Gaussian process">Gaussian process</a>, <a href="https://publications.waset.org/abstracts/search?q=nonlinearity%20distribution" title=" nonlinearity distribution"> nonlinearity distribution</a>, <a href="https://publications.waset.org/abstracts/search?q=particle%20filter" title=" particle filter"> particle filter</a>, <a href="https://publications.waset.org/abstracts/search?q=system%20identification" title=" system identification"> system identification</a> </p> <a 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The Effect of Measurement Distribution on System Identification and Detection of Behavior of Nonlinearities of Data