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A Method for Tracking the Time Evolution of Steady-State Evoked Potentials
Published on: May 25, 2019
Stability and dissipativity criteria for neural networks with time-varying delays via an augmented zero equality
1School of Electrical Engineering, Chungbuk National University, Cheongju 28644, Republic of Korea.
Abstract:
This work investigates the stability and dissipativity problems for neural networks with time-varying delay. By the construction of new augmented Lyapunov-Krasovskii functionals based on integral inequality and the use of zero equality approach, three improved results are proposed in the forms of linear matrix inequalities. And, based on the stability results, the dissipativity analysis for NNs with time-varying delays was investigated. Through some numerical examples, the superiority and effectiveness of the proposed results are shown by comparing the existing works.
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