Pseudo Almost Automorphic Solutions of Recurrent Neural Networks with Time-Varying Coefficients and Mixed Delays

Pseudo Almost Automorphic Solutions of Recurrent Neural Networks with Time-Varying Coefficients and Mixed Delays

In this paper, existence, uniqueness and global exponential stability of pseudo almost automorphic solutions for a class of recurrent neural networks with time-varying coefficients and mixed delays are established by employing the fixed point theorem and differential inequality. Numerical example wi...

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Veröffentlicht in:Neural processing letters 2017-02, Vol.45 (1), p.121-140
Hauptverfasser: Aouiti, Chaouki, M’hamdi, Mohammed Salah, Touati, Abderrahmane
Format: Artikel
Sprache:eng
Schlagworte:
Artificial Intelligence
Banach spaces
Complex Systems
Computational Intelligence
Computer Science
Fixed points (mathematics)
Neural networks
Neurons
Ordinary differential equations
Recurrent neural networks
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Zusammenfassung:In this paper, existence, uniqueness and global exponential stability of pseudo almost automorphic solutions for a class of recurrent neural networks with time-varying coefficients and mixed delays are established by employing the fixed point theorem and differential inequality. Numerical example with graphical illustration is given to illuminate our main results.
ISSN:1370-4621
1573-773X
DOI:10.1007/s11063-016-9515-0