Global exponential synchronization of switching neural networks with leakage time-varying delays
In this paper, the synchronization problem of a class of switching neural networks with leakage time-varying delays is studied. A system solution-based direct analysis method is proposed to derive the sufficient conditions of global exponential synchronization for master–slave systems. Firstly, the...
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Veröffentlicht in: | Communications in nonlinear science & numerical simulation 2024-06, Vol.133, p.107979, Article 107979 |
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Sprache: | eng |
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Zusammenfassung: | In this paper, the synchronization problem of a class of switching neural networks with leakage time-varying delays is studied. A system solution-based direct analysis method is proposed to derive the sufficient conditions of global exponential synchronization for master–slave systems. Firstly, the state variable expression of the error system is derived by constructing a suitable regulation function, in which the leakage delays are explicitly transformed outside the state variable. Then, on this basis, the corresponding synchronization conditions is obtained by using the transition condition ingeniously. In addition, the obtained sufficient conditions contain only some simple linear scalar inequalities, which is different from most publications and greatly reduces the computational complexity. Finally, the reliability of the theoretical results is verified by numerical simulation. It is worth noting that the synchronization problem of switching neural networks with time-varying leakage delays is studied for the first time in this paper, and the method adopted does not need to construct any Lyapunov–Krasovskii functionals, which simplifies the proof process.
•Synchronization problem of switching neural networks with leakage delays is studied.•A system solution-based direct method is proposed to achieve synchronization.•The proposed method simplifies proof process and reduces computational complexity.•The obtained synchronization criteria can be easily solved by using MATLAB. |
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ISSN: | 1007-5704 |
DOI: | 10.1016/j.cnsns.2024.107979 |