Improving ANC computational efficiency: a novel Fx LMS algorithm with dynamic response control

Iman Ardekani; Soheil Varastehpour; Hamid Sharifzadeh; Waleed Abdulla

doi:10.1109/M2VIP58386.2023.10413383

Improving ANC computational efficiency: a novel Fx LMS algorithm with dynamic response control

Iman Ardekani^*, Soheil Varastehpour, Hamid Sharifzadeh, Waleed Abdulla

^*Corresponding author for this work

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

Abstract

This paper presents a novel variant of the Fx LMS algorithm. This variant optimizes computational efficiency by utilizing a calculated imperfect secondary path model with a pure-delay impulse response, simplifying the filtered reference signal calculation and enhancing the convergence rate. Additionally, the algorithm includes a control parameter to adjust its dynamic response, further improving its convergence behaviour. We provide a theoretical framework based on root locus theory to optimize this parameter and the algorithm's performance. The theoretical contributions are substantiated through computer simulations, validating the enhanced effectiveness of the proposed approach in ANC applications.

Original language	English
Title of host publication	2023 29th International Conference on Mechatronics and Machine Vision in Practice (M2VIP)
Place of Publication	Piscataway, NJ
Publisher	Institute of Electrical and Electronics Engineers (IEEE)
Number of pages	6
ISBN (Electronic)	9798350325621
ISBN (Print)	9798350325638
DOIs	https://doi.org/10.1109/M2VIP58386.2023.10413383
Publication status	Published - 2023
Externally published	Yes
Event	29th International Conference on Mechatronics and Machine Vision in Practice, M2VIP 2023 - Queenstown, New Zealand Duration: 21 Nov 2023 → 24 Nov 2023

Conference

Conference	29th International Conference on Mechatronics and Machine Vision in Practice, M2VIP 2023
Country/Territory	New Zealand
City	Queenstown
Period	21/11/23 → 24/11/23

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10.1109/M2VIP58386.2023.10413383

Cite this

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title = "Improving ANC computational efficiency: a novel Fx LMS algorithm with dynamic response control",

abstract = "This paper presents a novel variant of the Fx LMS algorithm. This variant optimizes computational efficiency by utilizing a calculated imperfect secondary path model with a pure-delay impulse response, simplifying the filtered reference signal calculation and enhancing the convergence rate. Additionally, the algorithm includes a control parameter to adjust its dynamic response, further improving its convergence behaviour. We provide a theoretical framework based on root locus theory to optimize this parameter and the algorithm's performance. The theoretical contributions are substantiated through computer simulations, validating the enhanced effectiveness of the proposed approach in ANC applications.",

author = "Iman Ardekani and Soheil Varastehpour and Hamid Sharifzadeh and Waleed Abdulla",

year = "2023",

doi = "10.1109/M2VIP58386.2023.10413383",

language = "English",

isbn = "9798350325638",

booktitle = "2023 29th International Conference on Mechatronics and Machine Vision in Practice (M2VIP)",

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

address = "United States",

note = "29th International Conference on Mechatronics and Machine Vision in Practice, M2VIP 2023 ; Conference date: 21-11-2023 Through 24-11-2023",

}

Ardekani, I, Varastehpour, S, Sharifzadeh, H & Abdulla, W 2023, Improving ANC computational efficiency: a novel Fx LMS algorithm with dynamic response control. in 2023 29th International Conference on Mechatronics and Machine Vision in Practice (M2VIP). Institute of Electrical and Electronics Engineers (IEEE), Piscataway, NJ, 29th International Conference on Mechatronics and Machine Vision in Practice, M2VIP 2023, Queenstown, New Zealand, 21/11/23. https://doi.org/10.1109/M2VIP58386.2023.10413383

Improving ANC computational efficiency: a novel Fx LMS algorithm with dynamic response control. / Ardekani, Iman; Varastehpour, Soheil; Sharifzadeh, Hamid et al.
2023 29th International Conference on Mechatronics and Machine Vision in Practice (M2VIP). Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE), 2023.

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

TY - GEN

T1 - Improving ANC computational efficiency

T2 - 29th International Conference on Mechatronics and Machine Vision in Practice, M2VIP 2023

AU - Ardekani, Iman

AU - Varastehpour, Soheil

AU - Sharifzadeh, Hamid

AU - Abdulla, Waleed

PY - 2023

Y1 - 2023

N2 - This paper presents a novel variant of the Fx LMS algorithm. This variant optimizes computational efficiency by utilizing a calculated imperfect secondary path model with a pure-delay impulse response, simplifying the filtered reference signal calculation and enhancing the convergence rate. Additionally, the algorithm includes a control parameter to adjust its dynamic response, further improving its convergence behaviour. We provide a theoretical framework based on root locus theory to optimize this parameter and the algorithm's performance. The theoretical contributions are substantiated through computer simulations, validating the enhanced effectiveness of the proposed approach in ANC applications.

AB - This paper presents a novel variant of the Fx LMS algorithm. This variant optimizes computational efficiency by utilizing a calculated imperfect secondary path model with a pure-delay impulse response, simplifying the filtered reference signal calculation and enhancing the convergence rate. Additionally, the algorithm includes a control parameter to adjust its dynamic response, further improving its convergence behaviour. We provide a theoretical framework based on root locus theory to optimize this parameter and the algorithm's performance. The theoretical contributions are substantiated through computer simulations, validating the enhanced effectiveness of the proposed approach in ANC applications.

UR - https://www.scopus.com/pages/publications/85186113678

U2 - 10.1109/M2VIP58386.2023.10413383

DO - 10.1109/M2VIP58386.2023.10413383

M3 - Conference proceeding contribution

SN - 9798350325638

BT - 2023 29th International Conference on Mechatronics and Machine Vision in Practice (M2VIP)

PB - Institute of Electrical and Electronics Engineers (IEEE)

CY - Piscataway, NJ

Y2 - 21 November 2023 through 24 November 2023

ER -

Improving ANC computational efficiency: a novel Fx LMS algorithm with dynamic response control

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