Stability analysis of delayed neural network using new delay-product based functionals - Mahto, Sharat Chandra; Ghosh, Sandip; Saket, R.K.; Nagar, Shyam Krishna (Neurocomputing (Amsterdam), 2020)
This paper concerns with stability analysis of neural networks with time varying delay. Two new delay-product type functionals (DPFs) are developed by introducing new states in the augmented vector of delay-product term. Then using these DPFs, two new Lyapunov-Krasovskii functionals (LKFs) are constructed. Based on these LKFs, two delay-dependent stability criterion are obtained in the form of linear matrix inequalities. The effectiveness of the proposed criterion for delayed neural network is demonstrated by considering two examples.