A note on NSRLMS, NSRLMF, and NSRLMMN adaptive algorithms

Ulla Faiz, M. and Zerguine, A. 2015. A note on NSRLMS, NSRLMF, and NSRLMMN adaptive algorithms. 2018 15th International Multi-Conference on Systems, Signals & Devices (SSD). Yasmine Hammamet, Tunisia 19 - 22 Mar 2018 IEEE . https://doi.org/10.1109/ssd.2018.8570653

TitleA note on NSRLMS, NSRLMF, and NSRLMMN adaptive algorithms
AuthorsUlla Faiz, M. and Zerguine, A.
TypeConference paper
Abstract

In this paper, we compare the expressions for the steady-state mean-square error (MSE), the optimum step-size, and the corresponding minimum tracking MSE of the normalized sign regressor least mean square (NSRLMS), the normalized sign regressor least mean fourth (NSRLMF), and the normalized sign regressor least mean mixed-norm (NSRLMMN) algorithms for the case of real-valued data. The expressions for the steady-state MSE, the optimum step-size, and the corresponding minimum tracking MSE of the NSRLMF and NSRLMMN algorithms based on energy conservation relation approach are available in the literature for the case of real-valued data. Thus, in order to compare these three algorithms, we have derived the expressions for the steady-state MSE, the optimum stepsize, and the corresponding minimum tracking MSE of the NSRLMS algorithm based on energy conservation relation approach for the case of real-valued data. Finally, simulation results to substantiate the analytical results of the NSRLMS algorithm are also presented for the case of real-valued data.

Year2015
Conference2018 15th International Multi-Conference on Systems, Signals & Devices (SSD)
PublisherIEEE
Publication dates
Published2018
Journal2018 15th International Multi-Conference on Systems, Signals and Devices, SSD 2018
Digital Object Identifier (DOI)https://doi.org/10.1109/ssd.2018.8570653

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