Delay-dependent stability for neural networks with time-varying delays via a novel partitioning method

In this brief, a novel partitioning method for the conditions on bounding the activation function in the stability analysis of neural networks systems with time-varying delays is presented. Certain further improved delay-dependent stability conditions, which are expressed in terms of linear matrix inequalities (LMIs), are derived by employing a suitable Lyapunov-Krasovskii functional (LKF) and utilizing the Wirtinger integral inequality. Two well-known examples are investigated in a comparison mode with results to show the effectiveness and improvements achieved by the new results proposed.