Taesu Park, Minsu Kim, Minseon Gwak, Taesung Cho, P. Park
{"title":"主动噪声控制算法对噪声输入和测量脉冲噪声具有鲁棒性","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":"{\"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}","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}
Active noise control algorithm robust to noisy inputs and measurement impulsive noises
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.