A robust variable step size fractional least mean square (RVSS-FLMS) algorithm

Shujaat Khan; Muhammad Usman; Imran Naseem; Roberto Togneri; Mohammed Bennamoun

doi:10.1109/CSPA.2017.8064914

A robust variable step size fractional least mean square (RVSS-FLMS) algorithm

Shujaat Khan, Muhammad Usman, Imran Naseem, Roberto Togneri, Mohammed Bennamoun

Research output: Chapter in Book/Conference paper › Conference paper › peer-review

11 Citations (Scopus)

Abstract

In this paper, we propose an adaptive framework for the variable step size of the fractional least mean square (FLMS) algorithm. The proposed algorithm named the robust variable step size-FLMS (RVSS-FLMS), dynamically updates the step size of the FLMS to achieve high convergence rate with low steady state error. For the evaluation purpose, the problem of system identification is considered. The experiments clearly show that the proposed approach achieves better convergence rate compared to the FLMS and adaptive step-size modified FLMS (AMFLMS).

Original language	English
Title of host publication	Proceedings - 2017 IEEE 13th International Colloquium on Signal Processing and its Applications, CSPA 2017
Editors	Mohd Nasir Taib
Publisher	IEEE, Institute of Electrical and Electronics Engineers
Pages	1-6
Number of pages	6
ISBN (Electronic)	9781509011841
DOIs	https://doi.org/10.1109/CSPA.2017.8064914
Publication status	Published - 2017
Event	13th IEEE International Colloquium on Signal Processing and its Applications, CSPA 2017 - Penang, Malaysia Duration: 10 Mar 2017 → 12 Mar 2017

Conference

Conference	13th IEEE International Colloquium on Signal Processing and its Applications, CSPA 2017
Country/Territory	Malaysia
City	Penang
Period	10/03/17 → 12/03/17

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10.1109/CSPA.2017.8064914

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Khan, S., Usman, M., Naseem, I., Togneri, R., & Bennamoun, M. (2017). A robust variable step size fractional least mean square (RVSS-FLMS) algorithm. In M. N. Taib (Ed.), Proceedings - 2017 IEEE 13th International Colloquium on Signal Processing and its Applications, CSPA 2017 (pp. 1-6). Article 8064914 IEEE, Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/CSPA.2017.8064914

@inproceedings{9b09ef42bc1f4a9d880381e6d909cb19,

title = "A robust variable step size fractional least mean square (RVSS-FLMS) algorithm",

abstract = "In this paper, we propose an adaptive framework for the variable step size of the fractional least mean square (FLMS) algorithm. The proposed algorithm named the robust variable step size-FLMS (RVSS-FLMS), dynamically updates the step size of the FLMS to achieve high convergence rate with low steady state error. For the evaluation purpose, the problem of system identification is considered. The experiments clearly show that the proposed approach achieves better convergence rate compared to the FLMS and adaptive step-size modified FLMS (AMFLMS).",

keywords = "adaptive filter, adaptive step-size modified fractional LMS (AMFLMS), channel equalization, fractional calculus, fractional LMS (FLMS), high convergence, Least mean square (LMS), low steady state error, modified fractional LMS (MFLMS), plant identification, robust variable step size (RVSS), robust variable step size FLMS (RVSS-FLMS)",

author = "Shujaat Khan and Muhammad Usman and Imran Naseem and Roberto Togneri and Mohammed Bennamoun",

year = "2017",

doi = "10.1109/CSPA.2017.8064914",

language = "English",

pages = "1--6",

editor = "Taib, {Mohd Nasir }",

booktitle = "Proceedings - 2017 IEEE 13th International Colloquium on Signal Processing and its Applications, CSPA 2017",

publisher = "IEEE, Institute of Electrical and Electronics Engineers",

address = "United States",

note = "13th IEEE International Colloquium on Signal Processing and its Applications, CSPA 2017 ; Conference date: 10-03-2017 Through 12-03-2017",

}

Khan, S, Usman, M, Naseem, I , Togneri, R & Bennamoun, M 2017, A robust variable step size fractional least mean square (RVSS-FLMS) algorithm. in MN Taib (ed.), Proceedings - 2017 IEEE 13th International Colloquium on Signal Processing and its Applications, CSPA 2017., 8064914, IEEE, Institute of Electrical and Electronics Engineers, pp. 1-6, 13th IEEE International Colloquium on Signal Processing and its Applications, CSPA 2017, Penang, Malaysia, 10/03/17. https://doi.org/10.1109/CSPA.2017.8064914

A robust variable step size fractional least mean square (RVSS-FLMS) algorithm. / Khan, Shujaat; Usman, Muhammad; Naseem, Imran et al.
Proceedings - 2017 IEEE 13th International Colloquium on Signal Processing and its Applications, CSPA 2017. ed. / Mohd Nasir Taib. IEEE, Institute of Electrical and Electronics Engineers, 2017. p. 1-6 8064914.

Research output: Chapter in Book/Conference paper › Conference paper › peer-review

TY - GEN

T1 - A robust variable step size fractional least mean square (RVSS-FLMS) algorithm

AU - Khan, Shujaat

AU - Usman, Muhammad

AU - Naseem, Imran

AU - Togneri, Roberto

AU - Bennamoun, Mohammed

PY - 2017

Y1 - 2017

N2 - In this paper, we propose an adaptive framework for the variable step size of the fractional least mean square (FLMS) algorithm. The proposed algorithm named the robust variable step size-FLMS (RVSS-FLMS), dynamically updates the step size of the FLMS to achieve high convergence rate with low steady state error. For the evaluation purpose, the problem of system identification is considered. The experiments clearly show that the proposed approach achieves better convergence rate compared to the FLMS and adaptive step-size modified FLMS (AMFLMS).

AB - In this paper, we propose an adaptive framework for the variable step size of the fractional least mean square (FLMS) algorithm. The proposed algorithm named the robust variable step size-FLMS (RVSS-FLMS), dynamically updates the step size of the FLMS to achieve high convergence rate with low steady state error. For the evaluation purpose, the problem of system identification is considered. The experiments clearly show that the proposed approach achieves better convergence rate compared to the FLMS and adaptive step-size modified FLMS (AMFLMS).

KW - adaptive filter

KW - adaptive step-size modified fractional LMS (AMFLMS)

KW - channel equalization

KW - fractional calculus

KW - fractional LMS (FLMS)

KW - high convergence

KW - Least mean square (LMS)

KW - low steady state error

KW - modified fractional LMS (MFLMS)

KW - plant identification

KW - robust variable step size (RVSS)

KW - robust variable step size FLMS (RVSS-FLMS)

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BT - Proceedings - 2017 IEEE 13th International Colloquium on Signal Processing and its Applications, CSPA 2017

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Y2 - 10 March 2017 through 12 March 2017

ER -

A robust variable step size fractional least mean square (RVSS-FLMS) algorithm

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