Abstract
In this manuscript, fuzzy delayed cellular neural networks with impulse are studied. Applying time scale calculus knowledge, mathematical inequalities and constructing Lyapunov function, we establish a sufficient criterion that guarantees the existence and exponential stability of anti-periodic solutions for fuzzy delayed cellular neural networks with impulse. In addition, an example with its numerical simulations is given to illustrate our theoretical predictions.
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The work is supported by National Natural Science Foundation of China (No. 61673008), Project of High-level Innovative Talents of Guizhou Province ([2016]5651), Major Research Project of The Innovation Group of The Education Department of Guizhou Province ([2017]039), Project of Key Laboratory of Guizhou Province with Financial and Physical Features ([2017]004), Foundation of Science and Technology of Guizhou Province ([2019]1051), and Hunan Provincial Key Laboratory of Mathematical Modeling and Analysis in Engineering (Changsha University of Science & Technology) (2018MMAEZD21), University Science and Technology Top Talents Project of Guizhou Province (KY[2018]047) and Guizhou University of Finance and Economics (2018XZD01).
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Xu, C., Liao, M., Li, P. et al. Anti-periodic Oscillations of Fuzzy Delayed Cellular Neural Networks with Impulse on Time Scales. Neural Process Lett 51, 2379–2402 (2020). https://doi.org/10.1007/s11063-020-10203-0
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DOI: https://doi.org/10.1007/s11063-020-10203-0