New Results on Robust Finite-Time Passivity for Fractional-Order Neural Networks with Uncertainties

  • Mai Viet ThuanEmail author
  • Dinh Cong Huong
  • Duong Thi Hong


In this paper, the robust finite-time passivity for a class of fractional-order neural networks with uncertainties is considered. Firstly, the definition of finite-time passivity of fractional-order neural networks is introduced. Then, by using finite-time stability theory and linear matrix inequality approach, new sufficient conditions that ensure the finite-time passivity of the fractional-order neural network systems are derived via linear matrix inequalities which can be effectively solved by various computational tools. Finally, three numerical examples with simulation results are given to illustrate the effectiveness of the proposed method.


Fractional order neural networks Finite-time stability Finite-time passivity Linear matrix inequalities 



The authors sincerely thank the anonymous reviewers for their constructive comments that helped improve the quality and presentation of this paper. This paper was revised when the authors were working as researchers at Vietnam Institute for Advance Study in Mathematics (VIASM). Authors would like to thank the VIASM for providing a fruitful research environment and extending support and hospitality during their visit.


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Authors and Affiliations

  1. 1.Department of Mathematics and InformaticsThainguyen University of ScienceThai NguyenVietnam
  2. 2.Department for Management of Science and Technology DevelopmentTon Duc Thang UniversityHo Chi Minh CityVietnam
  3. 3.Faculty of Applied SciencesTon Duc Thang UniversityHo Chi Minh CityVietnam

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