ℋ∞ Stability Conditions for Fuzzy Neural Networks
This paper presents a novel approach to assess the stability of fuzzy neural networks. First, we propose a new condition for the ℋ∞ stability of fuzzy neural networks. Second, a new ℋ∞ stability condition based on linear matrix inequality (LMI) is presented for fuzzy neural networks. These condition...
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2012-01-01
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| Series: | Advances in Fuzzy Systems |
| Online Access: | http://dx.doi.org/10.1155/2012/281821 |
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| _version_ | 1832558737956536320 |
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| author | Choon Ki Ahn |
| author_facet | Choon Ki Ahn |
| author_sort | Choon Ki Ahn |
| collection | DOAJ |
| description | This paper presents a novel approach to assess the stability of fuzzy neural
networks. First, we propose a new condition for the ℋ∞ stability of fuzzy neural
networks. Second, a new ℋ∞ stability condition based on linear matrix inequality
(LMI) is presented for fuzzy neural networks. These conditions also ensure asymptotic
stability without external input. |
| format | Article |
| id | doaj-art-88ef7b7f13cc487b82f23de439f82a45 |
| institution | Kabale University |
| issn | 1687-7101 1687-711X |
| language | English |
| publishDate | 2012-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Advances in Fuzzy Systems |
| spelling | doaj-art-88ef7b7f13cc487b82f23de439f82a452025-02-03T01:31:40ZengWileyAdvances in Fuzzy Systems1687-71011687-711X2012-01-01201210.1155/2012/281821281821ℋ∞ Stability Conditions for Fuzzy Neural NetworksChoon Ki Ahn0Department of Automotive Engineering, Seoul National University of Science & Technology, 172 Gongneung 2-dong, Nowon-gu, Seoul 139-743, Republic of KoreaThis paper presents a novel approach to assess the stability of fuzzy neural networks. First, we propose a new condition for the ℋ∞ stability of fuzzy neural networks. Second, a new ℋ∞ stability condition based on linear matrix inequality (LMI) is presented for fuzzy neural networks. These conditions also ensure asymptotic stability without external input.http://dx.doi.org/10.1155/2012/281821 |
| spellingShingle | Choon Ki Ahn ℋ∞ Stability Conditions for Fuzzy Neural Networks Advances in Fuzzy Systems |
| title | ℋ∞ Stability Conditions for Fuzzy Neural Networks |
| title_full | ℋ∞ Stability Conditions for Fuzzy Neural Networks |
| title_fullStr | ℋ∞ Stability Conditions for Fuzzy Neural Networks |
| title_full_unstemmed | ℋ∞ Stability Conditions for Fuzzy Neural Networks |
| title_short | ℋ∞ Stability Conditions for Fuzzy Neural Networks |
| title_sort | h∞ stability conditions for fuzzy neural networks |
| url | http://dx.doi.org/10.1155/2012/281821 |
| work_keys_str_mv | AT choonkiahn hstabilityconditionsforfuzzyneuralnetworks |