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  4. Existence and Uniqueness of Pseudo Almost-Periodic Solutions of Recurrent Neural Networks With Time-Varying Coefficients and Mixed Delays
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Category: Consumer Electronics Magazine
By MTech Projects
MTech Projects
31.Jan
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Existence and Uniqueness of Pseudo Almost-Periodic Solutions of Recurrent Neural Networks With Time-Varying Coefficients and Mixed Delays

ABSTRACT:

This paper is concerned with the existence and uniqueness of pseudo almost-periodic solutions to recurrent delayed neural networks. Several conditions guaranteeing the existence and uniqueness of such solutions are obtained in a suitable convex domain. Furthermore, several methods are applied to establish sufficient criteria for the globally exponential stability of this system. The approaches are based on constructing suitable Lyapunov functionals and the well-known Banach contraction mapping principle. Moreover, the attractivity and exponential stability of the pseudo almost-periodic solution are also considered for the system. A numerical example is given to illustrate the effectiveness of our results.

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Previous article: ICCE-Berlin 2011 [ICCE Update] ICCE-Berlin 2011 [ICCE Update] Next article: Extended Hamiltonian Learning on Riemannian Manifolds: Numerical Aspects Extended Hamiltonian Learning on Riemannian Manifolds: Numerical Aspects
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