Delay-Dependent Stability Criteria for Generalized Neural Networks With Two Delay Components | IEEE Journals & Magazine | IEEE Xplore

Delay-Dependent Stability Criteria for Generalized Neural Networks With Two Delay Components


Abstract:

This paper investigates the delay-dependent stability for generalized continuous neural networks with time-varying delays. A novel Lyapunov-Krasovskii functional (LKF) th...Show More

Abstract:

This paper investigates the delay-dependent stability for generalized continuous neural networks with time-varying delays. A novel Lyapunov-Krasovskii functional (LKF) that considers more information on activation functions of delayed neural networks and delay upper bounds is developed. Simultaneously, most commonly used techniques for treating the derivative of the LKF are reviewed and compared with each other. With the way of introducing slack matrices, those techniques are classified into two categories, including free-weighting matrix (FWM)-based techniques and reciprocally convex combination-based techniques. It is found that the introduced slack matrices play an important role in conservatism reducing and those four types of FWM-based methods lead to same results and are equivalent. Moreover, the obtained criteria are extended to the system with a single time-varying delay. Two numerical examples are given to verify the effectiveness of the proposed method.
Page(s): 1263 - 1276
Date of Publication: 18 October 2013

ISSN Information:

Funding Agency:


References

References is not available for this document.