A neurodynamic optimization approach for complex-variables programming problem.

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

Abstract

A neural network model upon differential inclusion is designed for solving the complex-variables convex programming, and the chain rule for real-valued function with the complex-variables is established in this paper. The model does not need to choose penalty parameters when applied to practical problems, which makes it easier to design. The result is obtained that its state reaches the feasible region in finite time. Furthermore, the convergence for its state to an optimal solution is proved. Some typical examples are shown for the effectiveness of the designed model.

Authors

  • Shuxin Liu
    Institute of Operations Research and Control Theory, School of Mathematical Sciences, Dalian University of Technology, Dalian 116024, PR China; College of Mathematics and Physics, Xinjiang Agricultural University, Urumqi 830052, PR China.
  • Haijun Jiang
    College of Mathematics and System Sciences, Xinjiang University, Urumqi, 830046, Xinjiang, PR China. Electronic address: jianghaijunxju@163.com.
  • Liwei Zhang
  • Xuehui Mei
    College of Mathematics and System Sciences, Xinjiang University, Urumqi 830046, PR China.