Su, Lijuan; Zhou, Liqun Exponential stability of anti-periodic for a class of cellular neural networks with proportional delays. (Chinese. English summary) Zbl 1389.34219 Chin. J. Eng. Math. 34, No. 2, 143-154 (2017). Summary: In this paper, the global exponential stability of anti-periodic solutions of a class of cellular neural networks with proportional delays is discussed. Firstly, a class of cellular neural networks with proportional delays is transformed equivalently into a class of cellular neural networks with constant delays and variable coefficients. Then, by establishing appropriate delay differential inequalities and applying an inequality technique, a delay-dependent sufficient condition is obtained to ensure the existence and global exponential stability of anti-periodic solutions of the system. Finally, numerical results indicate that the proposed method is correct and less conservative than the existing results. MSC: 34K13 Periodic solutions to functional-differential equations 34K20 Stability theory of functional-differential equations 92B20 Neural networks for/in biological studies, artificial life and related topics Keywords:proportional delays; cellular neural networks; anti-periodic solution; exponential stability PDFBibTeX XMLCite \textit{L. Su} and \textit{L. Zhou}, Chin. J. Eng. Math. 34, No. 2, 143--154 (2017; Zbl 1389.34219) Full Text: DOI