Taesu Park, Minsu Kim, Minseon Gwak, Taesung Cho, P. Park
{"title":"Active noise control algorithm robust to noisy inputs and measurement impulsive noises","authors":"Taesu Park, Minsu Kim, Minseon Gwak, Taesung Cho, P. Park","doi":"10.23919/ICCAS50221.2020.9268248","DOIUrl":null,"url":null,"abstract":"This paper proposes an algorithm that can effectively remove noise when Gaussian noise is introduced into a reference microphone and impulsive noise is introduced into a target point in an active-noise-cancellation (ANC) system. We applied the normalized-least-mean-square (NLMS) algorithm, the most used in the adaptive filter algorithm, to the ANC environment. In the ANC environment, a compensation vector was calculated to compensate for the bias that occurs when Gaussian noise flows into the NLMS algorithm. In addition, a step-size scaler was proposed to prevent false update of the adaptive filter when impulsive noise occurred at the target point. Simulation results show that the proposed algorithm has better performance in the ANC environment than other algorithms.","PeriodicalId":6732,"journal":{"name":"2020 20th International Conference on Control, Automation and Systems (ICCAS)","volume":"3 1","pages":"622-626"},"PeriodicalIF":0.0000,"publicationDate":"2020-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 20th International Conference on Control, Automation and Systems (ICCAS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.23919/ICCAS50221.2020.9268248","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
This paper proposes an algorithm that can effectively remove noise when Gaussian noise is introduced into a reference microphone and impulsive noise is introduced into a target point in an active-noise-cancellation (ANC) system. We applied the normalized-least-mean-square (NLMS) algorithm, the most used in the adaptive filter algorithm, to the ANC environment. In the ANC environment, a compensation vector was calculated to compensate for the bias that occurs when Gaussian noise flows into the NLMS algorithm. In addition, a step-size scaler was proposed to prevent false update of the adaptive filter when impulsive noise occurred at the target point. Simulation results show that the proposed algorithm has better performance in the ANC environment than other algorithms.