Global exponential stability of fractional‐order impulsive neural network with time‐varying and distributed delay
H. M. Srivastava, Syed Haider Abbas, Swati Tyagi, Dhaou Lassoued · Mathematical Methods in the Applied Sciences · 2018
In this article, we present several results on global exponential stability of a fractional‐order cellular neural network with impulses and with time‐varying and distributed delay. By using the Lyapunov‐like function methods in conjunction with the Razumikhin techniques, we derive sufficient condition for the exponential stability with an exponential convergence rate. The obtained outcomes of our present investigation significantly extend and generalize the corresponding results existing in the current literature. Finally, we give 2 illustrative examples to demonstrate the theoretical findings.