Steady-state and tracking analysis of the SSLMS algorithm

Mohammed Mujahid Ulla Faiz; Azzedine Zerguine

doi:10.1109/SSD.2018.8570395

Steady-state and tracking analysis of the SSLMS algorithm

Mohammed Mujahid Ulla Faiz, Azzedine Zerguine

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

This paper presents expressions for the steady-state mean-square error (MSE), the optimum stepsize, and the corresponding minimum value of the tracking MSE of the sign-sign least mean square (SSLMS) algorithm for the case of real-valued data. Then, simulation results are presented to support our analytical findings and found to corroborate them very well. Also, the performance of the SSLMS algorithm is compared to that of the LMS algorithm in the case where the noise statistics are uniformly distributed.

Original language	English
Title of host publication	2018 15th International Multi-Conference on Systems, Signals and Devices, SSD 2018
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	45-48
Number of pages	4
ISBN (Electronic)	9781538653050
DOIs	https://doi.org/10.1109/SSD.2018.8570395
State	Published - 7 Dec 2018

Publication series

Name	2018 15th International Multi-Conference on Systems, Signals and Devices, SSD 2018

Bibliographical note

Publisher Copyright:
© 2018 IEEE.

Keywords

SSA
SSLMS
steady-state
tracking

ASJC Scopus subject areas

Computer Networks and Communications
Signal Processing
Control and Optimization
Instrumentation

Access to Document

10.1109/SSD.2018.8570395

Cite this

Ulla Faiz, M. M., & Zerguine, A. (2018). Steady-state and tracking analysis of the SSLMS algorithm. In 2018 15th International Multi-Conference on Systems, Signals and Devices, SSD 2018 (pp. 45-48). Article 8570395 (2018 15th International Multi-Conference on Systems, Signals and Devices, SSD 2018). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SSD.2018.8570395

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abstract = "This paper presents expressions for the steady-state mean-square error (MSE), the optimum stepsize, and the corresponding minimum value of the tracking MSE of the sign-sign least mean square (SSLMS) algorithm for the case of real-valued data. Then, simulation results are presented to support our analytical findings and found to corroborate them very well. Also, the performance of the SSLMS algorithm is compared to that of the LMS algorithm in the case where the noise statistics are uniformly distributed.",

keywords = "SSA, SSLMS, steady-state, tracking",

author = "{Ulla Faiz}, {Mohammed Mujahid} and Azzedine Zerguine",

note = "Publisher Copyright: {\textcopyright} 2018 IEEE.",

year = "2018",

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day = "7",

doi = "10.1109/SSD.2018.8570395",

language = "English",

series = "2018 15th International Multi-Conference on Systems, Signals and Devices, SSD 2018",

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Ulla Faiz, MM & Zerguine, A 2018, Steady-state and tracking analysis of the SSLMS algorithm. in 2018 15th International Multi-Conference on Systems, Signals and Devices, SSD 2018., 8570395, 2018 15th International Multi-Conference on Systems, Signals and Devices, SSD 2018, Institute of Electrical and Electronics Engineers Inc., pp. 45-48. https://doi.org/10.1109/SSD.2018.8570395

Steady-state and tracking analysis of the SSLMS algorithm. / Ulla Faiz, Mohammed Mujahid; Zerguine, Azzedine.
2018 15th International Multi-Conference on Systems, Signals and Devices, SSD 2018. Institute of Electrical and Electronics Engineers Inc., 2018. p. 45-48 8570395 (2018 15th International Multi-Conference on Systems, Signals and Devices, SSD 2018).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AB - This paper presents expressions for the steady-state mean-square error (MSE), the optimum stepsize, and the corresponding minimum value of the tracking MSE of the sign-sign least mean square (SSLMS) algorithm for the case of real-valued data. Then, simulation results are presented to support our analytical findings and found to corroborate them very well. Also, the performance of the SSLMS algorithm is compared to that of the LMS algorithm in the case where the noise statistics are uniformly distributed.

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Steady-state and tracking analysis of the SSLMS algorithm

Abstract

Publication series

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

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Cite this