Further Improvement on Delay-range-dependent Stability Criteria for Delayed Recurrent Neural Networks with Interval Time-varying Delays

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Abstract

This paper considers the problem of delay-range-dependent stability analysis for a class of delayed recurrent neural networks (DRNNs) with a time-varying delay in a range. Based on the Lyapunov-Krasovskii functional and derive the time derivative of this with integral inequality approach (IIA), new delay-dependent stability criteria for the system are established in terms of linear matrix inequalities (LMIs), which can be solved easily by various efficient convex optimization algorithms. Information about the lower bound of the delay is fully used in the Lyapunov functional. Two examples are given to illustrate the effectiveness and the reduced conservatism of the proposed results.

Keywords

Integral inequality approach (IIA) interval time-varying delay linear matrix inequality (LMI) recurrent neural network 

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Copyright information

© Institute of Control, Robotics and Systems and The Korean Institute of Electrical Engineers and Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of Automation Engineering Institute of Mechatronoptic SystemChienkuo Technology UniversityChanghuaTaiwan, R.O.C.

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