Hammerstein Spline Adaptive Filtering based on Normalised Least Mean Square Algorithm

Prongnuch, Sethakarn; Sitjongsataporn, Suchada; Wiangtong, Theerayod

doi:10.1109/ISPACS48206.2019.8986401

Hammerstein Spline Adaptive Filtering based on Normalised Least Mean Square Algorithm

Author(s)

Prongnuch, Sethakarn

Sitjongsataporn, Suchada

Wiangtong, Theerayod

Date Issued

December 1, 2019

Type

Conference Paper

DOI

10.1109/ISPACS48206.2019.8986401

Abstract

This paper proposes a normalised least mean square algorithm based on Hammerstein spline adaptive filtering. A nonlinear Hammerstein adaptive filters consists of memory-less function modified during learning and the spline control point is automatically controlled by gradient-based method. Simulation results demonstrate that the proposed algorithm exhibits more robust performance compared with the conventional spline adaptive filtering algorithms.

Citation

Proceedings 2019 International Symposium on Intelligent Signal Processing and Communication Systems Ispacs 2019, 2019