Quantized passive filtering for switched delayed neural networks
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| Format: | Artículo científico |
| Langue: | en |
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Vilniaus Universitetas
2021
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| _version_ | 1876489547498389504 |
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| author | Zhoua Youmei |
| author_facet | Zhoua Youmei |
| contents | Quantized passive filtering for switched delayed neural networks Zhoua Youmei Liub Yajuan Zhoua Jianping Wang Zhen Matemáticas semi Quantization passive filter Markov switching arbitrary switching The issue of quantized passive filtering for switched delayed neural networks with noise interference is studied in this paper. Both arbitrary and semi-Markov switching rules are taken into account. By choosing Lyapunov functionals and applying several inequality techniques, sufficient conditions are proposed to ensure the filter error system to be not only exponentially stable, but also exponentially passive from the noise interference to the output error. The gain matrix for the proposed quantized passive filter is able to be determined through the feasible solution of linear matrix inequalities, which are computationally tractable with the help of some popular convex optimization tools. Finally, two numerical examples are given to illustrate the usefulness of the quantized passive filter design methods. 2021 artículo científico 1392-5113 https://www.redalyc.org/articulo.oa?id=694172828006 https://www.redalyc.org/journal/6941/694172828006/ https://www.redalyc.org/journal/6941/694172828006/html/ https://www.redalyc.org/journal/6941/694172828006/694172828006.epub https://www.redalyc.org/journal/6941/694172828006/movil https://doi.org/10.15388/namc.2021.26.20562 en http://www.redalyc.org/revista.oa?id=6941 Nonlinear Analysis: Modelling and Control application/pdf Vilniaus Universitetas Nonlinear Analysis: Modelling and Control (Lituania) Num.1 Vol.26 |
| format | Artículo científico |
| id | redalyc_694172828006 |
| institution | Redalyc |
| language | en |
| publishDate | 2021 |
| publisher | Vilniaus Universitetas |
| spellingShingle | Quantized passive filtering for switched delayed neural networks Zhoua Youmei Matemáticas semi Quantization passive filter Markov switching arbitrary switching Quantized passive filtering for switched delayed neural networks Zhoua Youmei Liub Yajuan Zhoua Jianping Wang Zhen Matemáticas semi Quantization passive filter Markov switching arbitrary switching The issue of quantized passive filtering for switched delayed neural networks with noise interference is studied in this paper. Both arbitrary and semi-Markov switching rules are taken into account. By choosing Lyapunov functionals and applying several inequality techniques, sufficient conditions are proposed to ensure the filter error system to be not only exponentially stable, but also exponentially passive from the noise interference to the output error. The gain matrix for the proposed quantized passive filter is able to be determined through the feasible solution of linear matrix inequalities, which are computationally tractable with the help of some popular convex optimization tools. Finally, two numerical examples are given to illustrate the usefulness of the quantized passive filter design methods. 2021 artículo científico 1392-5113 https://www.redalyc.org/articulo.oa?id=694172828006 https://www.redalyc.org/journal/6941/694172828006/ https://www.redalyc.org/journal/6941/694172828006/html/ https://www.redalyc.org/journal/6941/694172828006/694172828006.epub https://www.redalyc.org/journal/6941/694172828006/movil https://doi.org/10.15388/namc.2021.26.20562 en http://www.redalyc.org/revista.oa?id=6941 Nonlinear Analysis: Modelling and Control application/pdf Vilniaus Universitetas Nonlinear Analysis: Modelling and Control (Lituania) Num.1 Vol.26 |
| title | Quantized passive filtering for switched delayed neural networks |
| topic | Matemáticas semi Quantization passive filter Markov switching arbitrary switching |
| url | https://www.redalyc.org/articulo.oa?id=694172828006 https://www.redalyc.org/journal/6941/694172828006/ https://www.redalyc.org/journal/6941/694172828006/html/ https://www.redalyc.org/journal/6941/694172828006/694172828006.epub https://www.redalyc.org/journal/6941/694172828006/movil https://doi.org/10.15388/namc.2021.26.20562 |