ArticleScientific reports2023
Finite-time complete periodic synchronization of memristive neural networks with mixed delays.
Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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2 citing papers in PubMed.
- Physics-informed Koopman learning approach for fixed-time synchronization of stochastic neural dynamics.Scientific reports · 2026Article
- Adaptive control for memristive system via compensatory controller and Chebyshev neural network.Scientific reports · 2024Article
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Authors and funding
6 authors.
Funding
Abstract
In this paper we study the oscillatory behavior of a new class of memristor based neural networks with mixed delays and we prove the existence and uniqueness of the periodic solution of the system based on the concept of Filippov solutions of the differential equation with discontinuous right-hand side. In addition, some assumptions are determined to guarantee the globally exponentially stability of the solution. Then, we study the adaptive finite-time complete periodic synchronization problem and by applying Lyapunov-Krasovskii functional approach, a new adaptive controller and adaptive update rule have been developed. A useful finite-time complete synchronization condition is established in terms of linear matrix inequalities. Finally, an illustrative simulation is given to substantiate the main results.
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