@article{Li2022, 
author = {Qiang Li and Weiqiang Gong and Linzhong Zhang and Kai Wang},
title = {Robust dissipativity and passivity of stochastic Markovian switching CVNNs with partly unknown transition rates and probabilistic time-varying delay},
year = {2022},
journal = {AIMS Mathematics},
volume = {7},
number = {10},
pages = {19458-19480},
keywords = {complex-valued neural networks, dissipativity, Markovian switching, partly unknown transition rates, probabilistic time-varying delay},
url = {https://www.sciopen.com/article/10.3934/math.20221068},
doi = {10.3934/math.20221068},
abstract = {This article addresses the robust dissipativity and passivity problems for a class of Markovian switching complex-valued neural networks with probabilistic time-varying delay and parameter uncertainties. The main objective of this article is to study the proposed problem from a new perspective, in which the relevant transition rate information is partially unknown and the considered delay is characterized by a series of random variables obeying bernoulli distribution. Moreover, the involved parameter uncertainties are considered to be mode-dependent and norm-bounded. Utilizing the generalized It             o      ^      's formula under the complex version, the stochastic analysis techniques and the robust analysis approach, the    (  M  ,  N  ,  W  )-dissipativity and passivity are ensured by means of complex matrix inequalities, which are mode-delay-dependent. Finally, two simulation examples are provided to verify the effectiveness of the proposed results.}
}