Almost periodic solutions for a memristor-based neural networks with leakage, time-varying and distributed delays. (English) Zbl 1397.34144
Summary: In this paper, we study the existence and global exponential stability of almost periodic solution for memristor-based neural networks with leakage, time-varying and distributed delays. Using a new Lyapunov function method, we prove that this delayed neural network has a unique almost periodic solution, which is globally exponentially stable. Moreover, the obtained conclusion on the almost periodic solution is applied to prove the existence and stability of periodic solution (or equilibrium point) for this delayed neural network with periodic coefficients (or constant coefficients).
MSC:
| 34K60 | Qualitative investigation and simulation of models involving functional-differential equations |
| 94C05 | Analytic circuit theory |
| 34K14 | Almost and pseudo-almost periodic solutions to functional-differential equations |
| 34K20 | Stability theory of functional-differential equations |
| 92B20 | Neural networks for/in biological studies, artificial life and related topics |
Keywords:
memristor-based neural networks; almost periodic solution; global exponential stability; leakage; time-varying and distributed delaysReferences:
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