Journal
IEEE TRANSACTIONS ON NEURAL NETWORKS
Volume 19, Issue 2, Pages 366-370Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TNN.2007.910738
Keywords
Cohen-Grossberg neural networks (CGNNs); delay-dependent criteria; linear matrix inequality (LMI); Markovian jumping; mixed delay
Ask authors/readers for more resources
In this letter, the global asymptotical stability analysis problem is considered for a class of Markovian jumping stochastic Cohen-Grossberg neural networks (CGNNs) with mixed delays including discrete delays and distributed delays. An alternative delay-dependent stability analysis result is established based on the linear matrix inequality (LMI) technique, which can easily be checked by utilizing the numerically efficient Matlab LMI toolbox. Neither system transformation nor free-weight matrix via Newton-Leibniz formula is required. Two numerical examples are included to show the effectiveness of the result.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available