Adaptation in active noise control - A simulation case study

Malgorzata Michalczyk; Teresa Glowka; Jaroslaw Figwer

doi:10.1109/MMAR.2016.7575172

Adaptation in active noise control - A simulation case study

Department of Measurements and Control Systems (RAU/RAU2)

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

5 Citations (Scopus)

Abstract

In this paper properties of adaptive algorithms utilising ideas of stochastic gradient search optimisation applied to noise reduction are discussed. A focus on their average rate of convergence as well as on the obtained noise reduction is given. The presented discussion is based on a simulation case study devoted to noise reduction using a feedforward adaptive active noise control system.

Original language	English
Title of host publication	2016 21st International Conference on Methods and Models in Automation and Robotics, MMAR 2016
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	420-425
Number of pages	6
ISBN (Electronic)	9781509018666
DOIs	https://doi.org/10.1109/MMAR.2016.7575172
Publication status	Published - 22 Sept 2016
Event	21st International Conference on Methods and Models in Automation and Robotics, MMAR 2016 - Miedzyzdroje, Poland Duration: 29 Aug 2016 → 1 Sept 2016

Publication series

Name	2016 21st International Conference on Methods and Models in Automation and Robotics, MMAR 2016

Conference

Conference	21st International Conference on Methods and Models in Automation and Robotics, MMAR 2016
Country/Territory	Poland
City	Miedzyzdroje
Period	29/08/16 → 1/09/16

ASJC Scopus subject areas

Control and Optimization
Control and Systems Engineering
Artificial Intelligence

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10.1109/MMAR.2016.7575172

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Michalczyk, M., Glowka, T., & Figwer, J. (2016). Adaptation in active noise control - A simulation case study. In 2016 21st International Conference on Methods and Models in Automation and Robotics, MMAR 2016 (pp. 420-425). Article 7575172 (2016 21st International Conference on Methods and Models in Automation and Robotics, MMAR 2016). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/MMAR.2016.7575172

Michalczyk, Malgorzata ; Glowka, Teresa ; Figwer, Jaroslaw. / Adaptation in active noise control - A simulation case study. 2016 21st International Conference on Methods and Models in Automation and Robotics, MMAR 2016. Institute of Electrical and Electronics Engineers Inc., 2016. pp. 420-425 (2016 21st International Conference on Methods and Models in Automation and Robotics, MMAR 2016).

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abstract = "In this paper properties of adaptive algorithms utilising ideas of stochastic gradient search optimisation applied to noise reduction are discussed. A focus on their average rate of convergence as well as on the obtained noise reduction is given. The presented discussion is based on a simulation case study devoted to noise reduction using a feedforward adaptive active noise control system.",

author = "Malgorzata Michalczyk and Teresa Glowka and Jaroslaw Figwer",

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doi = "10.1109/MMAR.2016.7575172",

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series = "2016 21st International Conference on Methods and Models in Automation and Robotics, MMAR 2016",

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Michalczyk, M , Glowka, T & Figwer, J 2016, Adaptation in active noise control - A simulation case study. in 2016 21st International Conference on Methods and Models in Automation and Robotics, MMAR 2016., 7575172, 2016 21st International Conference on Methods and Models in Automation and Robotics, MMAR 2016, Institute of Electrical and Electronics Engineers Inc., pp. 420-425, 21st International Conference on Methods and Models in Automation and Robotics, MMAR 2016, Miedzyzdroje, Poland, 29/08/16. https://doi.org/10.1109/MMAR.2016.7575172

Adaptation in active noise control - A simulation case study. / Michalczyk, Malgorzata ; Glowka, Teresa ; Figwer, Jaroslaw.
2016 21st International Conference on Methods and Models in Automation and Robotics, MMAR 2016. Institute of Electrical and Electronics Engineers Inc., 2016. p. 420-425 7575172 (2016 21st International Conference on Methods and Models in Automation and Robotics, MMAR 2016).

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

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AU - Glowka, Teresa

AU - Figwer, Jaroslaw

PY - 2016/9/22

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N2 - In this paper properties of adaptive algorithms utilising ideas of stochastic gradient search optimisation applied to noise reduction are discussed. A focus on their average rate of convergence as well as on the obtained noise reduction is given. The presented discussion is based on a simulation case study devoted to noise reduction using a feedforward adaptive active noise control system.

AB - In this paper properties of adaptive algorithms utilising ideas of stochastic gradient search optimisation applied to noise reduction are discussed. A focus on their average rate of convergence as well as on the obtained noise reduction is given. The presented discussion is based on a simulation case study devoted to noise reduction using a feedforward adaptive active noise control system.

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BT - 2016 21st International Conference on Methods and Models in Automation and Robotics, MMAR 2016

PB - Institute of Electrical and Electronics Engineers Inc.

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ER -

Michalczyk M , Glowka T , Figwer J. Adaptation in active noise control - A simulation case study. In 2016 21st International Conference on Methods and Models in Automation and Robotics, MMAR 2016. Institute of Electrical and Electronics Engineers Inc. 2016. p. 420-425. 7575172. (2016 21st International Conference on Methods and Models in Automation and Robotics, MMAR 2016). doi: 10.1109/MMAR.2016.7575172

Adaptation in active noise control - A simulation case study

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