Global exponential stability of non-autonomous cellular neural networks with impulses and time-varying delays

In this paper, we investigate the exponential stability of non-autonomous cellular neural networks with impulses and time-varying delays. By using the property of MM-matrix, we establish a new differential inequality to effect for non-autonomous systems. Basing on the differential inequality, the sufficient conditions ensuring the global exponential stability of the considered system are obtained. Our results improve some early results in the literature. An example and its simulation were given to illustrate the effectiveness and superiority of our main results.

► A new inequality which is effective for non-autonomous systems is established.
► The non-autonomous neural networks with delay and impulses is investigated.
► The sufficient conditions of exponential stability of neural networks are obtained.
► We drop the differentiability of delay functions which is needed in many works.