Fpga Design and Optimization of Adaptive Filters

DOI

10.2991/978-94-6463-864-6_12How to use a DOI?

Keywords

Adaptive Filters; FPGA; LMS; RLS; DSP

Abstract

This paper discusses the role of adaptive digital filters in modern signal processing systems, highlighting their ability to dynamically adjust to varying signal environments. Two widely used algorithms, Least Mean Squares and Recursive Least Squares are analysed. LMS is computationally efficient and suitable for low-resource hardware but has limited convergence speed and sensitivity to signal correlation. RLS offers faster convergence and higher accuracy at the cost of increased computational complexity. With the increasing demand for real-time and low-power processing in fields such as wireless communication, biomedical devices, and industrial automation, Field Programmable Gate Arrays have become a preferred platform. Recent developments in FPGA-based adaptive filtering include optimization techniques such as sparse computation, pipeline parallelism, distributed arithmetic, and approximate computing. These strategies enhance performance while reducing power and hardware usage. Furthermore, methods like delayed LMS and diagonal loading RLS improve adaptability and stability in real-time systems. FPGA-optimized adaptive filters demonstrate high efficiency, robustness, making them ideal for high-throughput, low-latency, and dynamic applications.

Copyright

© 2025 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Yueran Shen
PY  - 2025
DA  - 2025/10/23
TI  - Fpga Design and Optimization of Adaptive Filters
BT  - Proceedings of the 2025 2nd International Conference on Electrical Engineering and Intelligent Control (EEIC 2025)
PB  - Atlantis Press
SP  - 108
EP  - 115
SN  - 2352-5401
UR  - https://doi.org/10.2991/978-94-6463-864-6_12
DO  - 10.2991/978-94-6463-864-6_12
ID  - Shen2025
ER  -