Existence and stability of almost periodic solutions in impulsive neural network models

2010 ◽  
Vol 217 (8) ◽  
pp. 4167-4177 ◽  
Author(s):  
Manuel Pinto ◽  
Gonzalo Robledo
Keyword(s):  
Neural Network ◽  
Periodic Solutions ◽  
Network Models ◽  
Almost Periodic Solutions ◽  
Almost Periodic ◽  
Neural Network Models ◽  
Existence And Stability

scholarly journals Impulsive Fractional Cohen-Grossberg Neural Networks: Almost Periodicity Analysis

2021 ◽  
Vol 5 (3) ◽  
pp. 78
Author(s):  
Ivanka Stamova ◽  
Sotir Sotirov ◽  
Evdokia Sotirova ◽  
Gani Stamov
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Fractional Derivatives ◽  
Network Models ◽  
Almost Periodicity ◽  
Periodic Waves ◽  
Almost Periodic ◽  
Neural Network Models ◽  
Caputo Fractional Derivatives ◽  
Periodicity Analysis

In this paper, a fractional-order Cohen–Grossberg-type neural network with Caputo fractional derivatives is investigated. The notion of almost periodicity is adapted to the impulsive generalization of the model. General types of impulsive perturbations not necessarily at fixed moments are considered. Criteria for the existence and uniqueness of almost periodic waves are proposed. Furthermore, the global perfect Mittag–Leffler stability notion for the almost periodic solution is defined and studied. In addition, a robust global perfect Mittag–Leffler stability analysis is proposed. Lyapunov-type functions and fractional inequalities are applied in the proof. Since the type of Cohen–Grossberg neural networks generalizes several basic neural network models, this research contributes to the development of the investigations on numerous fractional neural network models.

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