Q-lmf: Quantum calculus-based least mean fourth algorithm

Alishba Sadiq; Muhammad Usman; Shujaat Khan; Imran Naseem; Muhammad Moinuddin; Ubaid M. Al-Saggaf

doi:10.1007/978-981-15-0637-6_25

Q-lmf: Quantum calculus-based least mean fourth algorithm

Alishba Sadiq
, Muhammad Usman
, Shujaat Khan^*
, Imran Naseem
, Muhammad Moinuddin
, Ubaid M. Al-Saggaf

^*Corresponding author for this work

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

8 Scopus citations

Abstract

Herein, we propose a new class of stochastic gradient algorithm for channel identification. The proposed q-least mean fourth (q-LMF) is an extension of the least mean fourth (LMF) algorithm and it is based on the q-calculus which is also known as Jackson’s derivative. The proposed algorithm utilizes a novel concept of error correlation energy and normalization of signal to ensure a high convergence rate, better stability, and low steady-state error. Contrary to conventional LMF, the proposed method has more freedom for large step sizes. Extensive experiments show significant gain in the performance of the proposed q-LMF algorithm in comparison to the contemporary techniques.

Original language	English
Title of host publication	4th International Congress on Information and Communication Technology, ICICT 2019, Volume 1
Editors	Xin-She Yang, Simon Sherratt, Nilanjan Dey, Amit Joshi
Publisher	Springer
Pages	303-311
Number of pages	9
ISBN (Print)	9789811506369
DOIs	https://doi.org/10.1007/978-981-15-0637-6_25
State	Published - 2020
Externally published	Yes

Publication series

Name	Advances in Intelligent Systems and Computing
Volume	1041
ISSN (Print)	2194-5357
ISSN (Electronic)	2194-5365

Bibliographical note

Publisher Copyright:
© Springer Nature Singapore Pte Ltd. 2020.

Keywords

Q-Calculus
Q-LMF
System identification

ASJC Scopus subject areas

Control and Systems Engineering
General Computer Science

Access to Document

10.1007/978-981-15-0637-6_25

Cite this

Sadiq, A., Usman, M., Khan, S., Naseem, I., Moinuddin, M., & Al-Saggaf, U. M. (2020). Q-lmf: Quantum calculus-based least mean fourth algorithm. In X.-S. Yang, S. Sherratt, N. Dey, & A. Joshi (Eds.), 4th International Congress on Information and Communication Technology, ICICT 2019, Volume 1 (pp. 303-311). (Advances in Intelligent Systems and Computing; Vol. 1041). Springer. https://doi.org/10.1007/978-981-15-0637-6_25

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title = "Q-lmf: Quantum calculus-based least mean fourth algorithm",

abstract = "Herein, we propose a new class of stochastic gradient algorithm for channel identification. The proposed q-least mean fourth (q-LMF) is an extension of the least mean fourth (LMF) algorithm and it is based on the q-calculus which is also known as Jackson{\textquoteright}s derivative. The proposed algorithm utilizes a novel concept of error correlation energy and normalization of signal to ensure a high convergence rate, better stability, and low steady-state error. Contrary to conventional LMF, the proposed method has more freedom for large step sizes. Extensive experiments show significant gain in the performance of the proposed q-LMF algorithm in comparison to the contemporary techniques.",

keywords = "Q-Calculus, Q-LMF, System identification",

author = "Alishba Sadiq and Muhammad Usman and Shujaat Khan and Imran Naseem and Muhammad Moinuddin and Al-Saggaf, \{Ubaid M.\}",

note = "Publisher Copyright: {\textcopyright} Springer Nature Singapore Pte Ltd. 2020.",

year = "2020",

doi = "10.1007/978-981-15-0637-6\_25",

language = "English",

isbn = "9789811506369",

series = "Advances in Intelligent Systems and Computing",

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}

Sadiq, A, Usman, M, Khan, S, Naseem, I, Moinuddin, M & Al-Saggaf, UM 2020, Q-lmf: Quantum calculus-based least mean fourth algorithm. in X-S Yang, S Sherratt, N Dey & A Joshi (eds), 4th International Congress on Information and Communication Technology, ICICT 2019, Volume 1. Advances in Intelligent Systems and Computing, vol. 1041, Springer, pp. 303-311. https://doi.org/10.1007/978-981-15-0637-6_25

Q-lmf: Quantum calculus-based least mean fourth algorithm. / Sadiq, Alishba; Usman, Muhammad; Khan, Shujaat et al.
4th International Congress on Information and Communication Technology, ICICT 2019, Volume 1. ed. / Xin-She Yang; Simon Sherratt; Nilanjan Dey; Amit Joshi. Springer, 2020. p. 303-311 (Advances in Intelligent Systems and Computing; Vol. 1041).

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

TY - GEN

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AU - Sadiq, Alishba

AU - Usman, Muhammad

AU - Khan, Shujaat

AU - Naseem, Imran

AU - Moinuddin, Muhammad

AU - Al-Saggaf, Ubaid M.

N1 - Publisher Copyright: © Springer Nature Singapore Pte Ltd. 2020.

PY - 2020

Y1 - 2020

N2 - Herein, we propose a new class of stochastic gradient algorithm for channel identification. The proposed q-least mean fourth (q-LMF) is an extension of the least mean fourth (LMF) algorithm and it is based on the q-calculus which is also known as Jackson’s derivative. The proposed algorithm utilizes a novel concept of error correlation energy and normalization of signal to ensure a high convergence rate, better stability, and low steady-state error. Contrary to conventional LMF, the proposed method has more freedom for large step sizes. Extensive experiments show significant gain in the performance of the proposed q-LMF algorithm in comparison to the contemporary techniques.

AB - Herein, we propose a new class of stochastic gradient algorithm for channel identification. The proposed q-least mean fourth (q-LMF) is an extension of the least mean fourth (LMF) algorithm and it is based on the q-calculus which is also known as Jackson’s derivative. The proposed algorithm utilizes a novel concept of error correlation energy and normalization of signal to ensure a high convergence rate, better stability, and low steady-state error. Contrary to conventional LMF, the proposed method has more freedom for large step sizes. Extensive experiments show significant gain in the performance of the proposed q-LMF algorithm in comparison to the contemporary techniques.

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Sadiq A, Usman M, Khan S, Naseem I, Moinuddin M, Al-Saggaf UM. Q-lmf: Quantum calculus-based least mean fourth algorithm. In Yang XS, Sherratt S, Dey N, Joshi A, editors, 4th International Congress on Information and Communication Technology, ICICT 2019, Volume 1. Springer. 2020. p. 303-311. (Advances in Intelligent Systems and Computing). doi: 10.1007/978-981-15-0637-6_25

Q-lmf: Quantum calculus-based least mean fourth algorithm

Abstract

Publication series

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

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Cite this