Premium
Dynamics of interval Cohen‐Grossberg neural networks with time‐varying delays based on LMI computation
Author(s) -
Tan Manchun,
Song Zhiqiang,
Liu Yunfeng,
Li Zhong
Publication year - 2018
Publication title -
concurrency and computation: practice and experience
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.309
H-Index - 67
eISSN - 1532-0634
pISSN - 1532-0626
DOI - 10.1002/cpe.5023
Subject(s) - linear matrix inequality , uniqueness , exponential stability , interval (graph theory) , computation , equilibrium point , control theory (sociology) , artificial neural network , mathematics , lyapunov function , computer science , mathematical optimization , nonlinear system , algorithm , mathematical analysis , artificial intelligence , differential equation , physics , control (management) , combinatorics , quantum mechanics
Summary The problem of the global robust exponential stability of delayed interval Cohen‐Grossberg neural networks is considered. By constructing suitable Lyapunov functional and using the linear matrix inequality (LMI) technique, some sufficient conditions are derived to ensure the existence, uniqueness and robust exponential stability of the equilibrium point. Based on LMI computation, numerical examples are employed to show that the new results are less restrictive and less conservative than some existing results in the literature.