Journal
AIMS MATHEMATICS
Volume 6, Issue 3, Pages 2539-2558Publisher
AMER INST MATHEMATICAL SCIENCES-AIMS
DOI: 10.3934/math.2021154
Keywords
Cohen-Grossberg; BAM neural networks; impulse; periodic solution; stability; Mawhin coincidence degree; Lyapunov function
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Funding
- Natural Science Foundation of China [11771185, 11871251]
- Natural Science Foundation of Jiangsu Higher Education Institutions [18KJB180027]
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This paper investigates a class of delayed Cohen-Grossberg-type bi-directional associative memory neural networks with impulses, and presents sufficient conditions to ensure the existence and stability of periodic solutions for the impulsive neural network systems. A simulation example is conducted to demonstrate the efficiency of the theoretical results.
This paper considers a class of delayed Cohen-Grossberg-type bi-directonal associative memory neural networks with impulses. By using Mawhin continuation theorem and constructing a new Lyapunov function, some sufficient conditions are presented to guarantee the existence and stability of periodic solutions for the impulsive neural network systems. A simulation example is carried out to illustrate the efficiency of the theoretical results.
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