Development of LMS Algorithm with Adapted and Unadapted Step Size
Mohaned Mohammed Hani, Asmaa Hameed Rasheed
Journal of Information Technology Review, Vol. 9, No. 3, 2018.
DOI: https://doi.org/10.6025/jitr/2018/9/3/85-93
Link: http://www.dline.info/jitr/fulltext/v9n3/jitrv9n3_2.pdf
Abstract:
Adaptive algorithms play a major role in all adaptive processing systems. One of the most important and wellknown
algorithms is the least mean square (LMS) algorithm due to simplicity, stability and fast convergence rate. In this
paper, two different types of the LMS algorithm were reviewed and analyzed: adapted and unadapted variable step size. The
adapted step size varies its value according to signal features while unadapted step size varies its value with a fixed
predefined constant. The performance of each algorithm measured in the scope of adaptive noise canceling system. Performance
quality was determined with respect to mean square error (MSE), convergence rate and algorithm stability. According to the
obtained simulation results the Adapted variable step size VSS-LMS algorithm was performed very well and converged
rapidly also it was stable through the adaptation process, as a result, it behaves better than unadapted VSS-LMS algorithm.
And both adapted and unadapted VSS-LMS algorithms give an enhanced performance for the ordinary fixed step size LMS
algorithm.