Journal
INTERNATIONAL JOURNAL OF MACHINE LEARNING AND CYBERNETICS
Volume 8, Issue 5, Pages 1607-1613Publisher
SPRINGER HEIDELBERG
DOI: 10.1007/s13042-016-0531-1
Keywords
Cellular neural networks; Anti-periodic solution; Exponential stability; Oscillating coefficient; Leakage term
Categories
Funding
- Natural Scientific Research Fund of Hunan Provincial of China [2016JJ6103, 2016JJ6104]
- Construction Program of the Key Discipline in Hunan University of Arts and Science-Applied Mathematics
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This paper is concerned with the anti-periodic solutions for a class of cellular neural network model with oscillating coefficients in leakage terms. By applying contraction mapping fixed point theorem and differential inequality techniques, we establish some sufficient conditions to guarantee the existence and exponential stability of anti-periodic solutions for this model, which improve and supplement existing ones. Moreover, an example and its numerical simulations are given to support the theoretical results.
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