Finite-time peak-to-peak analysis for switched generalized neural networks comprised of finite-time unstable subnetworks

Sang，Hong1; Zhao，Ying1; Wang，Peng2; Wang，Yuzhong3; Yu，Shuanghe1; Dimirovski，Georgi M.4

2023-07-01

10.1016/j.chaos.2023.113555

Chaos, Solitons and Fractals   影响因子和分区

0960-0779

1873-2887

This research is concerned with finite-time stability and peak-to-peak performance analysis for the discrete-time switched generalized neural networks (SGNNs) with time-varying delay. Compared with the reported results, each individual subnetwork of the SGNNs is considered to be finite-time unstable in the present study. To accomplish the anticipatory objective, the quasi-time-dependent Lyapunov–Krasovskii functional is constructed, and the associated sufficient conditions are simultaneously formulated to confirm that the disturbance-free SGNNs are finite-time stable when the subnetwork satisfies a certain switching time interval. In addition, a prescribed disturbance attenuation level is also achieved for the perturbed SGNNs in the sense of peak-to-peak performance. Finally, the provided simulation example corroborates the effectiveness and applicability of the established finite-time analysis framework in the absence of finite-time stable subnetworks.

Discrete-time domain Finite-time analysis Peak-to-peak performance Switched generalized neural networks Unstable subnetworks

SCI ; EI

英语

其他

Natural Science Foundation of Liaoning Province[2023-BS-073];Natural Science Foundation of Liaoning Province[2023-MS-120];Fundamental Research Funds for the Central Universities[3132023105];National Natural Science Foundation of China[61973060];National Natural Science Foundation of China[62003070];National Natural Science Foundation of China[62203080];National Natural Science Foundation of China[62273068];

Mathematics ; Physics

Mathematics, Interdisciplinary Applications ; Physics, Multidisciplinary ; Physics, Mathematical

WOS:001018396200001

PERGAMON-ELSEVIER SCIENCE LTD

20232214166476

Mathematics:921

PHYSICS

2-s2.0-85160327050

Scopus

1.College of Marine Electrical Engineering,Dalian Maritime University,Dalian,116026,China
2.School of Mathematics and Statistics,Fuzhou University,Fuzhou,350108,China
3.Center for Control Science and Technology,Southern University of Science and Technology,Shenzhen,518055,China
4.Doctoral School FEIT,SS Cyril and Methodius University,Skopje,1000,North Macedonia

Sang，Hong,Zhao，Ying,Wang，Peng,et al. Finite-time peak-to-peak analysis for switched generalized neural networks comprised of finite-time unstable subnetworks[J]. Chaos, Solitons and Fractals,2023,172.

Sang，Hong,Zhao，Ying,Wang，Peng,Wang，Yuzhong,Yu，Shuanghe,&Dimirovski，Georgi M..(2023).Finite-time peak-to-peak analysis for switched generalized neural networks comprised of finite-time unstable subnetworks.Chaos, Solitons and Fractals,172.

Sang，Hong,et al."Finite-time peak-to-peak analysis for switched generalized neural networks comprised of finite-time unstable subnetworks".Chaos, Solitons and Fractals 172(2023).