Research Article
LMS Adaptive Filter Design and Implementation of a Low Complexity LMS Filter
@INPROCEEDINGS{10.4108/eai.7-12-2021.2314966, author={Kalpana P}, title={LMS Adaptive Filter Design and Implementation of a Low Complexity LMS Filter}, proceedings={Proceedings of the First International Conference on Combinatorial and Optimization, ICCAP 2021, December 7-8 2021, Chennai, India}, publisher={EAI}, proceedings_a={ICCAP}, year={2021}, month={12}, keywords={adaptive filter least mean square algorithms lms adaptive filter adaptation delay area delay}, doi={10.4108/eai.7-12-2021.2314966} }- Kalpana P
Year: 2021
LMS Adaptive Filter Design and Implementation of a Low Complexity LMS Filter
ICCAP
EAI
DOI: 10.4108/eai.7-12-2021.2314966
Abstract
In real-time applications, an adaptive filter is used to model the applied input and output signals of the filter iteratively. Errors are minimised through the use of an adaptive algorithm that iteratively changes filter coefficients (n). For the LMS method, the coefficients of filters are adjusted by an adaptive algorithm. Error computation and weight-update blocks comprise the LMS adaptive filter's direct form. These blocks of filter determine the filter's efficiency. A low-power, small-area adaptive filter is presented in this paper in two different architectures, namely a zero adaptation delay and a two adaptation delay version. A zero adaptation delay adaptive filter saves nearly 52% of the area compared to a conventional adaptive filter, and the delay is reduced by 26%. Thus, the proposed filter structures can be used in high-speed applications that require minimal space.
