New stability criteria for recurrent neural networks with interval time-varying delay

• A new Lyapunov functional containing triple-integral terms is proposed.
• Some less conservative stability conditions are obtained.
• The proposed method involves fewer decision variables than free-weighting matrices method.

This paper is concerned with the problem of stability analysis of recurrent neural networks with time-varying delay belonging to a given interval. By constructing a novel augmented Lyapunov functional which contains some triple-integral terms, improved delay-dependent stability criteria are derived in terms of linear matrix inequality (LMI) by introducing some free-weighting matrices and using integral inequality technique and convex combination method. Numerical examples are given to illustrate the effectiveness of the proposed method.