Practical active noise control algorithms in bayesian inversion framework

Iman Ardekani, Hamid Sharifzadeh, Soheil Pour

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contributionpeer-review

Abstract

This paper approaches the problem of adaptive active noise control (ANC) as a Bayesian inverse problem. Initially, a forward model for the ANC system in the generic form usually used in the theory of inverse problems is derived. A vector of control system parameters is considered the problem's unknown variable. The unknown is assumed to be a multivariate random variable with a Gaussian prior probability density function. A data vector is formed using samples of the residual noise signal collected by a feedback microphone. Then, the standard Bayesian inversion method is applied to the forward model, resulting in a posterior probability density function for the unknown variable. We use the maximizer of this function to adjust the ANC system parameters. Both numerical results using computer simulation and empirical results using an experimental ANC setup confirm the efficiency of the proposed algorithm in practice.

Original languageEnglish
Title of host publicationInternational Conference on Electrical, Computer, Communications and Mechatronics Engineering (ICECCME 2022)
Place of PublicationPiscataway, NJ
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Number of pages6
ISBN (Electronic)9781665470957
ISBN (Print)9781665470964
DOIs
Publication statusPublished - 2022
Externally publishedYes
Event2022 International Conference on Electrical, Computer, Communications and Mechatronics Engineering, ICECCME 2022 - Male, Maldives
Duration: 16 Nov 202218 Nov 2022

Conference

Conference2022 International Conference on Electrical, Computer, Communications and Mechatronics Engineering, ICECCME 2022
Country/TerritoryMaldives
CityMale
Period16/11/2218/11/22

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