Almost periodic solutions of Cohen–Grossberg neural networks with time-varying delay and variable impulsive perturbations

2020 ◽  
Vol 80 ◽  
pp. 104952 ◽  
Author(s):  
Martin Bohner ◽  
Gani Tr. Stamov ◽  
Ivanka M. Stamova
Keyword(s):  
Neural Networks ◽  
Periodic Solutions ◽  
Time Varying ◽  
Almost Periodic Solutions ◽  
Almost Periodic ◽  
Time Varying Delay ◽  
Impulsive Perturbations ◽  
Varying Delay

scholarly journals Global Exponential Stability of Positive Almost Periodic Solutions for a Fishing Model with a Time-Varying Delay

2014 ◽  
Vol 2014 ◽  
pp. 1-11
Author(s):  
Hong Zhang ◽  
Shuhua Gong ◽  
Jianying Shao
Keyword(s):  
Numerical Simulation ◽  
Exponential Stability ◽  
Periodic Solutions ◽  
Global Exponential Stability ◽  
Time Varying ◽  
Almost Periodic Solutions ◽  
Almost Periodic ◽  
Time Varying Delay ◽  
Varying Delay ◽  
Positive Almost Periodic Solutions

This paper is concerned with a nonautonomous fishing model with a time-varying delay. Under proper conditions, we employ a novel argument to establish a criterion on the global exponential stability of positive almost periodic solutions of the model with almost periodic coefficients and delays. Moreover, an example and its numerical simulation are given to illustrate the main results.

scholarly journals C1-Almost Periodic Solutions of BAM Neural Networks with Time-Varying Delays on Time Scales

2015 ◽  
Vol 2015 ◽  
pp. 1-15 ◽  
Author(s):  
Yongkun Li ◽  
Lili Zhao ◽  
Li Yang
Keyword(s):  
Neural Networks ◽  
Periodic Solutions ◽  
Time Scales ◽  
Sufficient Conditions ◽  
Time Varying ◽  
Bam Neural Networks ◽  
Almost Periodic Solutions ◽  
Almost Periodic ◽  
New Type ◽  
Inequality Techniques

On a new type of almost periodic time scales, a class of BAM neural networks is considered. By employing a fixed point theorem and differential inequality techniques, some sufficient conditions ensuring the existence and global exponential stability ofC1-almost periodic solutions for this class of networks with time-varying delays are established. Two examples are given to show the effectiveness of the proposed method and results.

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