Document Zbl 1510.93325

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Math. Comput.</a> <a href="/?q=in%3A482162" title="Articles in this Issue">424, Article ID 127016, 12 p. (2022)</a>. </div> <div class="abstract">Summary: This dissertation studies the delay-probability-dependent $H_\infty$ state estimation issue of neural networks (NNs) with hybrid delays. First, more general system model and state estimator are established by considering discrete delay, distributed delay and probability distribution of time delays. Second, a innovative Lyapunov-Krasovskii functional (LKF) containing augmented non-integral and single-integral quadratic terms is put forward, which can inflect internal connections of multiple functional terms. Meanwhile, in order to handle the infinitesimal operators of LKF effectively, generalized free-weighting-matrix integral inequality (GFWMII) is chosen to cooperate with wirtinger-based inequality. As a consequence, less conservative criteria are obtained, which ensure that the considered system is asymptotically mean-square stable with a desired $H_\infty$ performance. Finally, two simulated examples are displayed to bring out the advantage of the achieved approach.</div> <div class="clear"></div> <div class="classification"> <h3>MSC:</h3> <table><tr> <td> <a class="mono" href="/classification/?q=cc%3A93E11" title="MSC2020">93E11</a> </td> <td class="space"> Filtering in stochastic control theory </td> </tr><tr> <td> <a class="mono" href="/classification/?q=cc%3A92B20" title="MSC2020">92B20</a> </td> <td class="space"> Neural networks for/in biological studies, artificial life and related topics </td> </tr><tr> <td> <a class="mono" href="/classification/?q=cc%3A93B36" title="MSC2020">93B36</a> </td> <td class="space"> $H^\infty$-control </td> </tr><tr> <td> <a class="mono" href="/classification/?q=cc%3A93B53" title="MSC2020">93B53</a> </td> <td class="space"> Observers </td> </tr></table> </div><div class="keywords"> <h3>Keywords:</h3><a href="/?q=ut%3Aneural+networks">neural networks</a>; <a href="/?q=ut%3Ahybrid+delays">hybrid delays</a>; <a href="/?q=ut%3Aprobability+distribution">probability distribution</a>; <a href="/?q=ut%3A%5C%28H_%5Cinfty%5C%29+state+estimation">$H_\infty$ state estimation</a>; <a href="/?q=ut%3Adesired+performance">desired performance</a></div>  <div class="modal fade" id="metadataModal" tabindex="-1" role="dialog" aria-labelledby="myModalLabel"> <div class="modal-dialog" role="document"> <div class="modal-content"> <div class="modal-header"> <button type="button" class="close" data-dismiss="modal" aria-label="Close"><span aria-hidden="true">×</span></button> <h4 class="modal-title" id="myModalLabel">Cite</h4> </div> <div class="modal-body"> <div class="form-group"> <label for="select-output" class="control-label">Format</label> <select id="select-output" class="form-control" aria-label="Select Metadata format"></select> </div> <div class="form-group"> <label for="metadataText" class="control-label">Result</label> <textarea class="form-control" id="metadataText" rows="10" style="min-width: 100%;max-width: 100%"></textarea> </div> <div id="metadata-alert" class="alert alert-danger" role="alert" style="display: none;">  </div> </div> <div class="modal-footer"> <button type="button" class="btn btn-primary" onclick="copyMetadata()">Copy to clipboard</button> <button type="button" class="btn btn-default" data-dismiss="modal">Close</button> </div> </div> </div> </div> <div class="functions clearfix"> <div class="function">  <a type="button" class="btn btn-default btn-xs pdf" data-toggle="modal" data-target="#metadataModal" data-itemtype="Zbl" data-itemname="Zbl 1510.93325" data-ciurl="/ci/07529330" data-biburl="/bibtex/07529330.bib" data-amsurl="/amsrefs/07529330.bib" data-xmlurl="/xml/07529330.xml" > Cite </a> <a class="btn btn-default btn-xs pdf" data-container="body" type="button" href="/pdf/07529330.pdf" title="Zbl 1510.93325 as PDF">Review PDF</a> </div> <div class="fulltexts"> <span class="fulltext">Full Text:</span> <a class="btn btn-default btn-xs" type="button" href="https://doi.org/10.1016/j.amc.2022.127016" aria-label="DOI for “Delay-probability-dependent state estimation for neural networks with hybrid delays”" title="10.1016/j.amc.2022.127016">DOI</a> </div> <div class="sfx" style="float: right;"> </div> </div> <div class="references"> <h3>References:</h3> <table><tr> <td>[1]</td> <td class="space">Shen, H.; Ru, T.; Xia, J.; Cao, J.; Wang, J., Finite-time energy-to-peak quantized filtering for markov jump networked systems under weighted try-once-discard protocol, Int. 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