This paper concerns with the problem of exponential stabilization for a class of non-autonomous
neural networks with mixed discrete and distributed time-varying delays. Two
cases of discrete time-varying delay, namely (i) slowly time-varying; and (ii) fast timevarying,
are considered. By constructing an appropriate Lyapunov–Krasovskii functional
in case (i) and utilizing the Razumikhin technique in case (ii), we establish some new
delay-dependent conditions for designing a memoryless state feedback controller which
stabilizes the system with an exponential convergence of the resulting closed-loop system.
The proposed conditions are derived through solutions of some types of Riccati differential
equations. Applications to control a class of autonomous neural networks with mixed
time-varying delays are also discussed in this paper. Some numerical examples are
provided to illustrate the effectiveness of the obtained results.

Tải file Exponential stabilization of non-autonomous delayed neural networks via Riccati equations tại đây