Title:
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Global stability of Clifford-valued Takagi-Sugeno fuzzy neural networks with time-varying delays and impulses (English) |
Author:
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Sriraman, Ramalingam |
Author:
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Nedunchezhiyan, Asha |
Language:
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English |
Journal:
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Kybernetika |
ISSN:
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0023-5954 (print) |
ISSN:
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1805-949X (online) |
Volume:
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58 |
Issue:
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4 |
Year:
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2022 |
Pages:
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498-521 |
Summary lang:
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English |
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Category:
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math |
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Summary:
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In this study, we consider the Takagi-Sugeno (T-S) fuzzy model to examine the global asymptotic stability of Clifford-valued neural networks with time-varying delays and impulses. In order to achieve the global asymptotic stability criteria, we design a general network model that includes quaternion-, complex-, and real-valued networks as special cases. First, we decompose the $n$-dimensional Clifford-valued neural network into $2^mn$-dimensional real-valued counterparts in order to solve the noncommutativity of Clifford numbers multiplication. Then, we prove the new global asymptotic stability criteria by constructing an appropriate Lyapunov-Krasovskii functionals (LKFs) and employing Jensen's integral inequality together with the reciprocal convex combination method. All the results are proven using linear matrix inequalities (LMIs). Finally, a numerical example is provided to show the effectiveness of the achieved results. (English) |
Keyword:
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global stability |
Keyword:
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T-S fuzzy |
Keyword:
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Clifford-valued neural networks |
Keyword:
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Lyapunov--Krasovskii functionals |
Keyword:
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impulses |
MSC:
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03E72 |
MSC:
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34D08 |
MSC:
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35R12 |
MSC:
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92B20 |
idZBL:
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Zbl 07655844 |
idMR:
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MR4521853 |
DOI:
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10.14736/kyb-2022-4-0498 |
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Date available:
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2022-12-02T13:09:21Z |
Last updated:
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2023-03-13 |
Stable URL:
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http://hdl.handle.net/10338.dmlcz/151162 |
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