Neural network based on systematically generated smoothing functions for absolute value equation

B. Saheya, Chieu Thanh Nguyen, Jein Shan Chen

Research output: Contribution to journalArticle

Abstract

In this paper, we summarize several systematic ways of constructing smoothing functions and illustrate eight smoothing functions accordingly. Then, based on these systematically generated smoothing functions, a unified neural network model is proposed for solving absolute value equation. The issues regarding the equilibrium point, the trajectory, and the stability properties of the neural network are addressed. Moreover, numerical experiments with comparison are presented, which suggests what kind of smoothing functions work well along with the neural network approach.

Original languageEnglish
Pages (from-to)533-558
Number of pages26
JournalJournal of Applied Mathematics and Computing
Volume61
Issue number1-2
DOIs
Publication statusPublished - 2019 Oct 1
Externally publishedYes

    Fingerprint

Keywords

  • Absolute value equations
  • Neural network
  • Smoothing function

ASJC Scopus subject areas

  • Computational Mathematics
  • Applied Mathematics

Cite this