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

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class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Mohammad%20Javad%20Mollakazemi">Mohammad Javad Mollakazemi</a>, <a href="https://publications.waset.org/search?q=Farhad%20Asadi"> Farhad Asadi</a>, <a href="https://publications.waset.org/search?q=Aref%20Ghafouri"> Aref Ghafouri</a> </p> <p class="card-text"><strong>Abstract:</strong></p> <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.</p> <iframe src="https://publications.waset.org/10000463.pdf" style="width:100%; height:400px;" frameborder="0"></iframe> <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Gaussian%20process" title="Gaussian process">Gaussian process</a>, <a href="https://publications.waset.org/search?q=Nonlinearity%20distribution" title=" Nonlinearity distribution"> Nonlinearity distribution</a>, <a href="https://publications.waset.org/search?q=Particle%0D%0Afilter." title=" Particle filter."> Particle filter.</a> </p> <p class="card-text"><strong>Digital Object Identifier (DOI):</strong> <a href="https://doi.org/10.5281/zenodo.1099148" target="_blank">doi.org/10.5281/zenodo.1099148</a> </p> <a href="https://publications.waset.org/10000463/the-effect-of-measurement-distribution-on-system-identification-and-detection-of-behavior-of-nonlinearities-of-data" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/10000463/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/10000463/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/10000463/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/10000463/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/10000463/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/10000463/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/10000463/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/10000463/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/10000463/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/10000463/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/10000463.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">1722</span> </span> <p class="card-text"><strong>References:</strong></p> <br>[1] E-W Bai, “A blind approach to Hammerstein-Wiener model identification,” Automatica, 38(6):967–979, 2002. <br>[2] Johan Dahlin, Fredrik Lindsten and Thomas B. Schön, “Particle Metropolis Hastings using gradient and Hessian information”. Statistics and Computing, 2014. (accepted for publication) <br>[3] Johan Dahlin, Fredrik Lindsten and Thomas B. Schön, “Second-order Particle MCMC for Bayesian parameter inference, in Proceedings of the 18th” World Congress of the International Federation of Automatic Control (IFAC), Cape Town, South Africa, August 2014. <br>[4] Johan Dahlin, Fredrik Lindsten and Thomas B. Schön,” Particle Metropolis Hastings using Langevin dynamics”, in Proceedings of the 38th International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Vancouver, Canada, May 2013. <br>[5] G. Pillonetto and A. Chiuso, “Gaussian processes for Wiener- Hammerstein system identification”. In Proceedings of the 15th IFAC Symposium on System Identification, Saint-Malo, France. <br>[6] Fredrik Lindsten, Thomas B. Schön and Michael I. Jordan,” A semiparametric Bayesian approach to Wiener system identification”, in Proceedings of the 16th IFAC Symposium on System Identification (SYSID), Brussels, Belgium, July 2012 <br>[7] Johan Dahlin, Fredrik Lindsten, Thomas B. Schön and Adrian Wills, “Hierarchical Bayesian ARX models for robust inference”, in Proceedings of the 16th IFAC Symposium on System Identification (SYSID), Brussels, Belgium, July 2012. <br>[8] T. Choi and M. J. Schervish, “On posterior consistency in nonparametric regression problems”. Journal of Multivariate Analysis, 98(10):1969–1987, 2007. <br>[9] Farhad Asadi, Mohammad javad Mollakazemi, “Investigation of fluctuation locations and effect of data distribution in time series dynamical regimes”.. Accepted and oral presentation in ICBCBBE 2014: XII International Conference on Bioinformatics, Computational Biology and Biomedical Engineering, October, 27-28, 2014, Istanbul, turkey. <br>[10] Farhad Asadi, Mohammad javad Mollakazemi, Aref Ghafouri, “The influence of parameters of modeling and data distribution for optimal condition on locally weighted projection regression method”.. Accepted and oral presentation in ICMSE 2014: XII International Conference on Mathematics and Statistical Engineering, October, 27-28, 2014, Istanbul, turkey. <br>[11] Mohammad javad Mollakazemi, Farhad Asadi, “Real-time adaptive obstacle avoidance in dynamic environments with different D-S”.. Accepted and oral presentation in ICARM 2014: XII International Conference on Automation, Robotics and Mechatronics, October, 27-28, 2014, Istanbul, turkey. </div> </div> </div> </main> <footer> <div id="infolinks" class="pt-3 pb-2"> <div class="container"> <div style="background-color:#f5f5f5;" class="p-3"> <div class="row"> <div class="col-md-2"> <ul class="list-unstyled"> About <li><a href="https://waset.org/page/support">About Us</a></li> <li><a href="https://waset.org/page/support#legal-information">Legal</a></li> <li><a target="_blank" rel="nofollow" href="https://publications.waset.org/static/files/WASET-16th-foundational-anniversary.pdf">WASET celebrates its 16th foundational anniversary</a></li> </ul> </div> <div class="col-md-2"> <ul class="list-unstyled"> Account <li><a href="https://waset.org/profile">My Account</a></li> </ul> </div> <div class="col-md-2"> <ul class="list-unstyled"> Explore <li><a href="https://waset.org/disciplines">Disciplines</a></li> <li><a href="https://waset.org/conferences">Conferences</a></li> <li><a href="https://waset.org/conference-programs">Conference Program</a></li> <li><a href="https://waset.org/committees">Committees</a></li> <li><a href="https://publications.waset.org">Publications</a></li> </ul> </div> <div class="col-md-2"> <ul class="list-unstyled"> Research <li><a href="https://publications.waset.org/abstracts">Abstracts</a></li> <li><a href="https://publications.waset.org">Periodicals</a></li> <li><a href="https://publications.waset.org/archive">Archive</a></li> </ul> </div> <div class="col-md-2"> <ul class="list-unstyled"> Open Science <li><a target="_blank" rel="nofollow" href="https://publications.waset.org/static/files/Open-Science-Philosophy.pdf">Open Science Philosophy</a></li> <li><a target="_blank" rel="nofollow" href="https://publications.waset.org/static/files/Open-Science-Award.pdf">Open Science Award</a></li> <li><a target="_blank" rel="nofollow" href="https://publications.waset.org/static/files/Open-Society-Open-Science-and-Open-Innovation.pdf">Open Innovation</a></li> <li><a target="_blank" rel="nofollow" href="https://publications.waset.org/static/files/Postdoctoral-Fellowship-Award.pdf">Postdoctoral Fellowship Award</a></li> <li><a target="_blank" rel="nofollow" href="https://publications.waset.org/static/files/Scholarly-Research-Review.pdf">Scholarly Research Review</a></li> </ul> </div> <div class="col-md-2"> <ul class="list-unstyled"> Support <li><a href="https://waset.org/page/support">Support</a></li> <li><a href="https://waset.org/profile/messages/create">Contact Us</a></li> <li><a href="https://waset.org/profile/messages/create">Report Abuse</a></li> </ul> </div> </div> </div> </div> </div> <div class="container text-center"> <hr style="margin-top:0;margin-bottom:.3rem;"> <a href="https://creativecommons.org/licenses/by/4.0/" target="_blank" class="text-muted small">Creative Commons Attribution 4.0 International License</a> <div id="copy" class="mt-2">© 2024 World Academy of Science, Engineering and Technology</div> </div> </footer> <a href="javascript:" id="return-to-top"><i class="fas fa-arrow-up"></i></a> <div class="modal" id="modal-template"> <div class="modal-dialog"> <div class="modal-content"> <div class="row m-0 mt-1"> <div class="col-md-12"> <button type="button" class="close" data-dismiss="modal" aria-label="Close"><span aria-hidden="true">×</span></button> </div> </div> <div class="modal-body"></div> </div> </div> </div> <script src="https://cdn.waset.org/static/plugins/jquery-3.3.1.min.js"></script> <script src="https://cdn.waset.org/static/plugins/bootstrap-4.2.1/js/bootstrap.bundle.min.js"></script> <script src="https://cdn.waset.org/static/js/site.js?v=150220211556"></script> <script> jQuery(document).ready(function() { /*jQuery.get("https://publications.waset.org/xhr/user-menu", function (response) { jQuery('#mainNavMenu').append(response); });*/ jQuery.get({ url: "https://publications.waset.org/xhr/user-menu", cache: false }).then(function(response){ jQuery('#mainNavMenu').append(response); }); }); </script> </body> </html>

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