Passivity and robust passivity of inertial memristive neural networks with time-varying delays via non-reduced order method.

Journal: Neural networks : the official journal of the International Neural Network Society
Published Date:

Abstract

This study examines the concepts of passivity and robust passivity in inertial memristive neural networks (IMNNs) that feature time-varying delays. By using non-smooth analysis and the passivity theorem, algebraic criteria for both passivity and robust passivity are derived by using the non-reduced order method. The proposed criteria, based on the non-reduced order method, effectively reduce the complexity of derivation and computation, thereby simplifying the verification process. Furthermore, asymptotic stability criteria for IMNNs are established in relation to the passivity conditions. In conclusion, two numerical examples are provided to confirm the theoretical results.

Authors

  • Weizhe Xu
    Biomedical and Health Informatics, University of Washington.
  • Zihao Li
    School of Mechanical Engineering and Automation, Harbin Institute of Technology(Shenzhen), Shenzhen, 518055, China.
  • Song Zhu
    College of Sciences, China University of Mining and Technology, Xuzhou, 221116, China. Electronic address: songzhu82@gmail.com.