Normalized LMS adaptive filter algorithm: principles and verilog HDL implementation
Abstract This article offers a detailed exploration of the Normalized Least Mean Squares (NLMS) algorithm, highlighting its enhanced adaptive filtering capabilities and robust performance in managing input signal correlations. It delves into the foundational principles of the NLMS algorithm and outlines the essential modules required for its implementation in Verilog HDL. The implementation and simulation of the NLMS adaptive filter are studied. The simulation outcomes indicate that the convergence rate of the algorithm is superior to that of the conventional LMS algorithm.
Authors
- Dezhen Yang (ORCID: https://orcid.org/0000-0002-7183-6492)
- Peiyuan Wan (ORCID: https://orcid.org/0000-0003-4875-6432)
- Ming Liu (ORCID: https://orcid.org/0000-0002-0666-3564)
- Xu Liu (ORCID: https://orcid.org/0000-0003-4461-8884)
- Bingjie Li (ORCID: https://orcid.org/0000-0002-8528-1889)
- Zhijie Chen (ORCID: https://orcid.org/0000-0003-2705-065X)
- Haoxu Wang (ORCID: https://orcid.org/0009-0008-7346-5497)
Institutions
- Beijing University of Technology (CN)
Publication Details
- Journal
- Journal of Physics Conference Series
- Published
- 2025-04-01
- DOI
- https://doi.org/10.1088/1742-6596/2991/1/012021
- Citations
- 1
- Primary Topic
- Advanced Adaptive Filtering Techniques
- Type
- article
- Field-Weighted Citation Impact
- 1.33