Premium
Guaranteed Cost Stabilization of Cellular Neural Networks with Time‐Varying Delay
Author(s) -
He Hanlin,
Yan Lu,
Tu Jianjun
Publication year - 2013
Publication title -
asian journal of control
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.769
H-Index - 53
eISSN - 1934-6093
pISSN - 1561-8625
DOI - 10.1002/asjc.631
Subject(s) - cellular neural network , control theory (sociology) , exponential stability , quadratic equation , artificial neural network , stability (learning theory) , computer science , linear matrix inequality , matrix (chemical analysis) , control (management) , mathematics , mathematical optimization , artificial intelligence , nonlinear system , machine learning , physics , geometry , materials science , quantum mechanics , composite material
Guaranteed cost stabilization of cellular neural networks with time‐varying delay ( DCNNs ) is considered in this paper. Via applying the zoned discussion and maximum synthesis ( ZDMS ) in DCNNs and Lyapunov–Krasovskii functional, a less conservative feedback control law in the form of quadratic matrix inequality ( QMI ) is derived to achieve globally asymptotic stability of the system.
Accelerating Research
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom
Address
John Eccles HouseRobert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom