Abstract
In this manuscript, we investigate the stability problems of neutral-type neural networks with D-operator and mixed delays. Some sufficient conditions are obtained for guaranteeing the existence, uniqueness, and global asymptotical stability of periodic solutions to the considered neural networks. Finally, a numerical example is performed to illustrate the theoretical results.
Highlights
We obtain the existence, uniqueness, and global asymptotical stability of periodic solutions by using LMI approach, Lyapunov function, and a blend of matrix theory which are different from the methods in [8]
(2) Unlike the most existing results, we develop a new unified framework to deal with global asymptotical stability of interval neural networks by LMI approach, Lyapunov function, and a blend of matrix theory which may be of independent interest
We prove that x0(t) is a unique T− periodic solution of different T− periodic solutions of system (1), where system (1)
Summary
We consider the following neutral neural networks with D− operator and mixed delays:. Xn(t))⊤ corresponds to the state of the (t), ith unit at . . , (Anxn)(t))⊤, time which t and is defined (Ax)(t) by. E neutral-type operator A in (2) represents the D− operator form which was put forward by Hale [1]. En, we give the following properties for the difference operator A. [Ax](t) x(t) − cx(t − τ), ∀t ∈ R, where CT {x : x ∈ C(R, R), x(t + T) ≡ x(t)} and c is a constant
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
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
