Event-triggered H∞ filtering for discrete-time Markov jump delayed neural networks with quantizations
The problem of event-triggered $ H_\infty $ filtering for discrete-time Markov jump delayed neural networks with quantizations is investigated in this paper. Firstly, an event-triggered communication scheme is proposed to determine whether or not the current sampled data can be transmitted to the qu...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2018-09-01
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| Series: | Systems Science & Control Engineering |
| Subjects: | |
| Online Access: | http://dx.doi.org/10.1080/21642583.2018.1531360 |
| _version_ | 1819154454019047424 |
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| author | Tingting Zhang Jinfeng Gao Jiahao Li |
| author_facet | Tingting Zhang Jinfeng Gao Jiahao Li |
| author_sort | Tingting Zhang |
| collection | DOAJ |
| description | The problem of event-triggered $ H_\infty $ filtering for discrete-time Markov jump delayed neural networks with quantizations is investigated in this paper. Firstly, an event-triggered communication scheme is proposed to determine whether or not the current sampled data can be transmitted to the quantizer. Secondly, a quantizer is used to quantify the sampled data, which can reduce the data transmission rate in the network. Next, through the analysis of network-induced delay's intervals, the discrete-time neural network, the event-triggered scheme and network-induced delay are unified into a discrete-time Markov jump delayed neural network. As a result, the sufficient conditions are obtained to guarantee the stability and $ H_\infty $ performance of the augmented system and to present the $ H_\infty $ filter design. Finally, a numerical example is given to demonstrate the effectiveness of the proposed method. |
| first_indexed | 2024-12-22T15:21:20Z |
| format | Article |
| id | doaj.art-8d3958cf8a1a441588424b6fca737eed |
| institution | Directory Open Access Journal |
| issn | 2164-2583 |
| language | English |
| last_indexed | 2024-12-22T15:21:20Z |
| publishDate | 2018-09-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Systems Science & Control Engineering |
| spelling | doaj.art-8d3958cf8a1a441588424b6fca737eed2022-12-21T18:21:37ZengTaylor & Francis GroupSystems Science & Control Engineering2164-25832018-09-0163748410.1080/21642583.2018.15313601531360Event-triggered H∞ filtering for discrete-time Markov jump delayed neural networks with quantizationsTingting Zhang0Jinfeng Gao1Jiahao Li2Zhejiang Sci-Tech UniversityZhejiang Sci-Tech UniversityZhejiang Sci-Tech UniversityThe problem of event-triggered $ H_\infty $ filtering for discrete-time Markov jump delayed neural networks with quantizations is investigated in this paper. Firstly, an event-triggered communication scheme is proposed to determine whether or not the current sampled data can be transmitted to the quantizer. Secondly, a quantizer is used to quantify the sampled data, which can reduce the data transmission rate in the network. Next, through the analysis of network-induced delay's intervals, the discrete-time neural network, the event-triggered scheme and network-induced delay are unified into a discrete-time Markov jump delayed neural network. As a result, the sufficient conditions are obtained to guarantee the stability and $ H_\infty $ performance of the augmented system and to present the $ H_\infty $ filter design. Finally, a numerical example is given to demonstrate the effectiveness of the proposed method.http://dx.doi.org/10.1080/21642583.2018.1531360Event-triggered schemeMarkov jump neural networksquantization $ H_\infty $ filtering |
| spellingShingle | Tingting Zhang Jinfeng Gao Jiahao Li Event-triggered H∞ filtering for discrete-time Markov jump delayed neural networks with quantizations Systems Science & Control Engineering Event-triggered scheme Markov jump neural networks quantization $ H_\infty $ filtering |
| title | Event-triggered H∞ filtering for discrete-time Markov jump delayed neural networks with quantizations |
| title_full | Event-triggered H∞ filtering for discrete-time Markov jump delayed neural networks with quantizations |
| title_fullStr | Event-triggered H∞ filtering for discrete-time Markov jump delayed neural networks with quantizations |
| title_full_unstemmed | Event-triggered H∞ filtering for discrete-time Markov jump delayed neural networks with quantizations |
| title_short | Event-triggered H∞ filtering for discrete-time Markov jump delayed neural networks with quantizations |
| title_sort | event triggered h∞ filtering for discrete time markov jump delayed neural networks with quantizations |
| topic | Event-triggered scheme Markov jump neural networks quantization $ H_\infty $ filtering |
| url | http://dx.doi.org/10.1080/21642583.2018.1531360 |
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