TY - JOUR
T1 - Stability analysis for periodic solutions of fuzzy shunting inhibitory CNNs with delays
AU - Kashkynbayev, Ardak
AU - Cao, Jinde
AU - Damiyev, Zhaksybek
N1 - Funding Information:
The second author was supported by the National Natural Science Foundation of China under Grant Nos. 61833005, 61573096, and the Jiangsu Provincial Key Laboratory of Networked Collective Intelligence under Grant BM2017002.
PY - 2019/12/1
Y1 - 2019/12/1
N2 - We consider fuzzy shunting inhibitory cellular neural networks (FSICNNs) with time-varying coefficients and constant delays. By virtue of continuation theorem of coincidence degree theory and Cauchy–Schwartz inequality, we prove the existence of periodic solutions for FSICNNs. Furthermore, by employing a suitable Lyapunov functional we establish sufficient criteria which ensure global exponential stability of the periodic solutions. Numerical simulations that support the theoretical discussions are depicted.
AB - We consider fuzzy shunting inhibitory cellular neural networks (FSICNNs) with time-varying coefficients and constant delays. By virtue of continuation theorem of coincidence degree theory and Cauchy–Schwartz inequality, we prove the existence of periodic solutions for FSICNNs. Furthermore, by employing a suitable Lyapunov functional we establish sufficient criteria which ensure global exponential stability of the periodic solutions. Numerical simulations that support the theoretical discussions are depicted.
KW - Delay differential equations
KW - Fuzzy shunting inhibitory cellular neural networks
KW - Global exponential stability
KW - Lyapunov functional
KW - Periodic solutions
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U2 - 10.1186/s13662-019-2321-z
DO - 10.1186/s13662-019-2321-z
M3 - Article
AN - SCOPUS:85071752987
SN - 1687-1839
VL - 2019
JO - Advances in Difference Equations
JF - Advances in Difference Equations
IS - 1
M1 - 384
ER -