Robustness analysis of fuzzy BAM cellular neural network with time-varying delays and stochastic disturbances
Robustness analysis for the global exponential stability of fuzzy bidirectional associative memory cellular neural network (FBAMCNN) is explored in this paper. By applying Gronwall-Bellman lemma and other inequality techniques, the range limits of both time-varying delays and the intensity of noise...
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| Format: | Article |
| Language: | English |
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AIMS Press
2023-02-01
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| Series: | AIMS Mathematics |
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| Online Access: | https://www.aimspress.com/article/doi/10.3934/math.2023471?viewType=HTML |
| _version_ | 1811160939619155968 |
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| author | Wenxiang Fang Tao Xie Biwen Li |
| author_facet | Wenxiang Fang Tao Xie Biwen Li |
| author_sort | Wenxiang Fang |
| collection | DOAJ |
| description | Robustness analysis for the global exponential stability of fuzzy bidirectional associative memory cellular neural network (FBAMCNN) is explored in this paper. By applying Gronwall-Bellman lemma and other inequality techniques, the range limits of both time-varying delays and the intensity of noise that FBAMCNN can withstand to maintain globally exponentially stable is estimated. It means that if the intensities of interference are larger than the bounds we derived, then the perturbed system may lose global exponential stability. Several instances are given to support our main results. |
| first_indexed | 2024-04-10T06:06:13Z |
| format | Article |
| id | doaj.art-7a085c44c4284ddab21e2369fb2f596e |
| institution | Directory Open Access Journal |
| issn | 2473-6988 |
| language | English |
| last_indexed | 2024-04-10T06:06:13Z |
| publishDate | 2023-02-01 |
| publisher | AIMS Press |
| record_format | Article |
| series | AIMS Mathematics |
| spelling | doaj.art-7a085c44c4284ddab21e2369fb2f596e2023-03-03T01:26:52ZengAIMS PressAIMS Mathematics2473-69882023-02-01849365938410.3934/math.2023471Robustness analysis of fuzzy BAM cellular neural network with time-varying delays and stochastic disturbancesWenxiang Fang0Tao Xie1Biwen Li2School of mathematics and statistics, Hubei Normal University, Huangshi 435002, Hubei, ChinaSchool of mathematics and statistics, Hubei Normal University, Huangshi 435002, Hubei, ChinaSchool of mathematics and statistics, Hubei Normal University, Huangshi 435002, Hubei, ChinaRobustness analysis for the global exponential stability of fuzzy bidirectional associative memory cellular neural network (FBAMCNN) is explored in this paper. By applying Gronwall-Bellman lemma and other inequality techniques, the range limits of both time-varying delays and the intensity of noise that FBAMCNN can withstand to maintain globally exponentially stable is estimated. It means that if the intensities of interference are larger than the bounds we derived, then the perturbed system may lose global exponential stability. Several instances are given to support our main results.https://www.aimspress.com/article/doi/10.3934/math.2023471?viewType=HTMLrobustness analysisfuzzy bidirectional memory cellular neural networktime-varying delaysstochastic disturbances |
| spellingShingle | Wenxiang Fang Tao Xie Biwen Li Robustness analysis of fuzzy BAM cellular neural network with time-varying delays and stochastic disturbances AIMS Mathematics robustness analysis fuzzy bidirectional memory cellular neural network time-varying delays stochastic disturbances |
| title | Robustness analysis of fuzzy BAM cellular neural network with time-varying delays and stochastic disturbances |
| title_full | Robustness analysis of fuzzy BAM cellular neural network with time-varying delays and stochastic disturbances |
| title_fullStr | Robustness analysis of fuzzy BAM cellular neural network with time-varying delays and stochastic disturbances |
| title_full_unstemmed | Robustness analysis of fuzzy BAM cellular neural network with time-varying delays and stochastic disturbances |
| title_short | Robustness analysis of fuzzy BAM cellular neural network with time-varying delays and stochastic disturbances |
| title_sort | robustness analysis of fuzzy bam cellular neural network with time varying delays and stochastic disturbances |
| topic | robustness analysis fuzzy bidirectional memory cellular neural network time-varying delays stochastic disturbances |
| url | https://www.aimspress.com/article/doi/10.3934/math.2023471?viewType=HTML |
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