Improved stability results for neural networks of neutral type with additive time‐varying delays and Markovian jumping parameters
This paper investigates stability problem for neural networks of neutral type with additive time‐varying delays and Markovian jump parameters. By constructing an improved Lyapunov‐Krasovskii functional with triple and four integral terms and applying the free matrix variables in approximating certai...
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Veröffentlicht in: | Mathematical methods in the applied sciences 2024-12 |
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Hauptverfasser: | , , |
Format: | Artikel |
Sprache: | eng |
Online-Zugang: | Volltext |
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Zusammenfassung: | This paper investigates stability problem for neural networks of neutral type with additive time‐varying delays and Markovian jump parameters. By constructing an improved Lyapunov‐Krasovskii functional with triple and four integral terms and applying the free matrix variables in approximating certain integral quadratic terms, applying the free matrix variables in approximating certain integral quadratic terms, we derived the stability condition in terms of linear matrix inequalities (LMIs). Two numerical examples are provided to show the effectiveness of the proposed method. The obtained results are compared with the existing results to show the conservativeness. |
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ISSN: | 0170-4214 1099-1476 |
DOI: | 10.1002/mma.10597 |