Adaptive Orthogonal Gradient Algorithm Based on Fair Cost Function

Sitjongsataporn, Suchada; Wiangtong, Theerayod

doi:10.1109/iEECON60677.2024.10537894

Adaptive Orthogonal Gradient Algorithm Based on Fair Cost Function

Author(s)

Sitjongsataporn, Suchada

Wiangtong, Theerayod

Date Issued

January 1, 2024

Type

Conference Paper

DOI

10.1109/iEECON60677.2024.10537894

Abstract

This paper presents an adaptive orthogonal gradient algorithm with the unconstrained Fair cost function. An adaptive orthogonal gradient-based algorithm is investigated with the help of orthogonal projection mechanism to update the approximate tap-weight vector for the convergence enhancement. Fair cost function is preferable with a smooth points that is able to detect the statistical characteristics of error. Objective of this work is to present an adaptive orthogonal gradient algorithm using Fair cost function (OGA-Fair) to enhance the performance. Simulation results show that proposed adaptive OGA-Fair algorithm can perform with the fast convergence rate and robustness better than the existing method.

Citation

Proceeding 12th International Electrical Engineering Congress Smart Factory and Intelligent Technology for Tomorrow Ieecon 2024, 2024

Subjects

adaptive algorithm

Fair cost function

orthogonal gradient a...