Spline adaptive filtering algorithm based on Heaviside step function

Sihai Guan, Qing Cheng, Yong Zhao, Bharat Biswal

Research output: Contribution to journalArticlepeer-review

Abstract

To reduce the interference of impulsive noise when the spline adaptive filter (SAF) algorithm is used to identify nonlinear systems, this paper proposes a family of SAF algorithms using the Heaviside step function (HSF). The suitability of those cost functions proposed are investigated; those cost functions are design based on some HSF’s approximate functions. Then based on that, four SAF algorithms have been developed: SAF-HSF-sigmoid, SAF-HSF-erfc, SAF-HSF-atan, and SAF-HSF-tanh. Also, the bound of the learning rate has been derived for those proposed algorithms. The proposed SAF-HSF algorithms have been evaluated for nonlinear system identification and simulation studies to demonstrate their robustness.

Original languageEnglish (US)
JournalSignal, Image and Video Processing
DOIs
StateAccepted/In press - 2022
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Electrical and Electronic Engineering

Keywords

  • Heaviside step function
  • Impulisve noise
  • Nonlinear system
  • Spline adaptive filter

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