On the variance of the Least Mean Square squared-error sample curve
Methodology
2023-12-04 v1 Computation
Abstract
Most studies of adaptive algorithm behavior consider performance measures based on mean values such as the mean-square error. The derived models are useful for understanding the algorithm behavior under different environments and can be used for design. Nevertheless, from a practical point of view, the adaptive filter user has only one realization of the algorithm to obtain the desired result. This letter derives a model for the variance of the squared-error sample curve of the least-mean-square (LMS) adaptive algorithm, so that the achievable cancellation level can be predicted based on the properties of the steady-state squared error. The derived results provide the user with useful design guidelines.
Keywords
Cite
@article{arxiv.2312.00185,
title = {On the variance of the Least Mean Square squared-error sample curve},
author = {Marcos H. Maruo and José Carlos M. Bermudez},
journal= {arXiv preprint arXiv:2312.00185},
year = {2023}
}