Author(s)

Feiran Wang, Zhensheng Yu, Chang Gao

College of Science, University of Shanghai for Science and Technology, Shanghai.

In this paper, we give a smoothing neural network algorithm for absolute value equations (AVE). By using smoothing function, we reformulate the AVE as a differentiable unconstrained optimization and we establish a steep descent method to solve it. We prove the stability and the equilibrium state of the neural network to be a solution of the AVE. The numerical tests show the efficient of the proposed algorithm.

Absolute Value Equations, Neural Network, Smoothing Function, Linear Complementarity Problem

Wang, F. , Yu, Z. and Gao, C. (2015) A Smoothing Neural Network Algorithm for Absolute Value Equations. Engineering, 7, 567-576. doi: 10.4236/eng.2015.79052.