LMS Convergence and the Step Size ($ \mu $) Parameter

1. What is step size in LMS?
2. What is LSM algorithm?
3. What is LMS in Arduino?
4. Why is NLMS better than LMS?

What is step size in LMS?

The inherent feature of the Least Mean Squares (LMS) algorithm is the step size, and it requires careful adjustment. Small step size, required for small excess mean square error, results in slow convergence. Large step size, needed for fast adaptation, may result in loss of stability.

What is LSM algorithm?

6.1 Introduction. The Least Mean Square (LMS) algorithm, introduced by Widrow and Hoff in 1959 [12] is an adaptive algorithm, which uses a gradient-based method of steepest decent [10]. LMS algorithm uses the estimates of the gradient vector from the available data.

What is LMS in Arduino?

Abstract: In this work, the least mean square (LMS) filter module is modeled, implemented and verified on a low-cost microcontroller to eliminate acoustic noise, which is a problem in voice communications.

Why is NLMS better than LMS?

The NLMS algorithm considerably improves speech quality with noise suppression levels of up to 13 dB, while the LMS algorithm is giving up to 10 dB. In different ways of SNR measure was under various types of blocking matrix, step sizes and various noise locations.