Abstract
Abstract In this brief, the mean square Lagrange stability for delayed recurrent neural networks with Markovian switching is studied. Firstly, stochastic vector Halandy inequalities are established by virtue of stochastic analysis and M-matrix techniques. Secondly, without additional restrictive conditions on the time-varying delay, the criteria on mean square Lagrange stability for delayed recurrent neural networks with Markovian switching are derived by means of the vector Halandy inequalities, and the global attractive sets in mean square sense are given. A numerical example is provided to examine the correctness of the derived results.
Full Text 
Sign-in/Register to access full text options
Sign-in/Register to access full text options 
Published version (
Free)
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
