Abstract
A novel adaptive filtering method called q-Volterra least mean square (q-VLMS) is presented in this paper. The q-VLMS is a nonlinear extension of conventional LMS and it is based on Jackson's derivative also known as q-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.
| Original language | English |
|---|---|
| Title of host publication | 2019 2nd International Conference on Latest Trends in Electrical Engineering and Computing Technologies, INTELLECT 2019 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| ISBN (Electronic) | 9781728124353 |
| DOIs | |
| State | Published - Nov 2019 |
| Externally published | Yes |
Publication series
| Name | 2019 2nd International Conference on Latest Trends in Electrical Engineering and Computing Technologies, INTELLECT 2019 |
|---|
Bibliographical note
Publisher Copyright:© 2019 IEEE.
Keywords
- Nonlinear Channel Estimation
- Quantum Calculus
- Volterra Series
ASJC Scopus subject areas
- Artificial Intelligence
- Computer Networks and Communications
- Computer Science Applications
- Electrical and Electronic Engineering
- Safety, Risk, Reliability and Quality
- Instrumentation
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