Stability analysis of neutral type neural networks with mixed time-varying delays using triple-integral and delay-partitioning methods

- The system not only has time-varying discrete delay, but also distributed delay, which has never been discussed so far.
- Improved stability criteria are derived by employing the more general partitioning approach and generalizing the famous Jensen inequality.
- By constructing a newly augmented LKFs, novle stability criteria are established in terms of LIMs.

This paper investigates the asymptotical stability problem for a class of neutral type neural networks with mixed time-varying delays. The system not only has time-varying discrete delay, but also distributed delay, which has never been discussed in the previous literature. Firstly, improved stability criteria are derived by employing the more general delay partitioning approach and generalizing the famous Jensen inequality. Secondly, by constructing a newly augmented Lyapunov-Krasovskii functionals, some less conservative stability criteria are established in terms of linear matrix inequalities (LMIs). Finally, four numerical examples are given to illustrate the effectiveness and the advantage of the proposed main results.