Open AccessPositive stability analysis of pseudo almost periodic solutions for HDCNNs accompanying $ D $ operator
Author(s) -
Lilun Zhang,
Li Le,
Chuangxia Huang
Publication year - 2022
Publication title -
discrete and continuous dynamical systems. series s
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.481
H-Index - 34
eISSN - 1937-1632
pISSN - 1937-1179
DOI - 10.3934/dcdss.2021160
Subject(s) - mathematics , bounded function , stability (learning theory) , operator (biology) , exponential stability , lyapunov function , differential operator , pure mathematics , discrete mathematics , mathematical analysis , computer science , physics , nonlinear system , biochemistry , chemistry , repressor , quantum mechanics , machine learning , transcription factor , gene
In this study, the stable dynamics of a kind of high-order cellular neural networks accompanying \begin{document}$ D $\end{document} operators and mixed delays are analyzed. The global existence of bounded positive solutions is substantiated by applying some novel differential inequality analyses. Meanwhile, by exploiting Lyapunov function method, some sufficient criteria are gained to validate the positiveness and globally exponential stability of pseudo almost periodic solutions on the addressed networks. In addition, computer simulations are produced to test the derived analytical findings.