A proximal neurodynamic model for solving inverse mixed variational inequalities.

Journal: Neural networks : the official journal of the International Neural Network Society
Published Date: Jan 27, 2021

Abstract

This paper proposes a proximal neurodynamic model (PNDM) for solving inverse mixed variational inequalities (IMVIs) based on the proximal operator. It is shown that the PNDM has a unique continuous solution under the condition of Lipschitz continuity (L-continuity). It is also shown that the equilibrium point of the proposed PNDM is asymptotically stable or exponentially stable under some mild conditions. Finally, three numerical examples are presented to illustrate effectiveness of the proposed PNDM.

Authors

  • Xingxing Ju
    Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing, School of Electronic and Information Engineering, Southwest University, Chongqing 400715, China. Electronic address: bob211@email.swu.edu.cn.
  • Chuandong Li
    College of Electronic and Information Engineering, Southwest University, Chongqing 400044, PR China. Electronic address: licd@cqu.edu.cn.
  • Xing He
    University of Florida, Gainesville, Florida, USA.
  • Gang Feng
    Environment and Plant Protection Institute, Chinese Academy of Tropical Agricultural Science, Haikou 571010, People's Republic of China; Key Laboratory of Monitoring and Control of Tropical Agricultural and Forest Invasive Alien Pests, Ministry of Agriculture, Haikou 571010, People's Republic of China. Electronic address: feng8513@sina.com.

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