Abstract
This work repots results of the convergence analysis of the normalized sign-sign least mean square (NSSLMS) algorithm when the input is real-valued data. The results includes expressions for different parameters, such as the steady-state mean-square error, and the tracking mean-square error. Moreover, the performance of the normalized sign-sign LMS algorithm is compared with that of the sign-sign LMS algorithm. The convergence behavior includes the rate of convergence. Finally, simulation results suggest that the normalized sign-sign LMS algorithm can be used as a good replacement for the sign-sign LMS algorithm as the former algorithm offers comparatively much faster rate of convergence than the latter algorithm.
| Original language | English |
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| Title of host publication | 18th IEEE International Multi-Conference on Systems, Signals and Devices, SSD 2021 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 514-517 |
| Number of pages | 4 |
| ISBN (Electronic) | 9781665414937 |
| DOIs | |
| State | Published - 22 Mar 2021 |
Publication series
| Name | 18th IEEE International Multi-Conference on Systems, Signals and Devices, SSD 2021 |
|---|
Bibliographical note
Publisher Copyright:© 2021 IEEE.
Keywords
- NSS algorithm
- NSSLMS
- Sign-sign algorithm
- convergence
- sign-sign (SS) LMS
- tracking
ASJC Scopus subject areas
- Artificial Intelligence
- Computer Networks and Communications
- Computer Science Applications
- Signal Processing
- Electrical and Electronic Engineering