Quantum Calculus-based Volterra LMS for Nonlinear Channel Estimation
Optimization and Control
2019-08-08 v1 Information Theory
Signal Processing
math.IT
Abstract
A novel adaptive filtering method called -Volterra least mean square (-VLMS) is presented in this paper. The -VLMS is a nonlinear extension of conventional LMS and it is based on Jackson's derivative also known as -calculus. In Volterra LMS, due to large variance of input signal the convergence speed is very low. With proper manipulation we successfully improved the convergence performance of the Volterra LMS. The proposed algorithm is analyzed for the step-size bounds and results of analysis are verified through computer simulations for nonlinear channel estimation problem.
Keywords
Cite
@article{arxiv.1908.02510,
title = {Quantum Calculus-based Volterra LMS for Nonlinear Channel Estimation},
author = {Muhammad Usman and Muhammad Sohail Ibrahim and Jawwad Ahmad and Syed Saiq Hussain and Muhammad Moinuddin},
journal= {arXiv preprint arXiv:1908.02510},
year = {2019}
}