{"title":"具有降噪功能的盲均衡器","authors":"Mitsuru Mashimo, Minoru Komatsu, H. Matsumoto","doi":"10.1109/ISPACS48206.2019.8986252","DOIUrl":null,"url":null,"abstract":"Recently, in order to compensate for distortion of the received signals, the blind equalization method has been studied. The blind equalizer is designed by using only received signals. However, equalization precision is lower when noise is included in the received signals [1]. Therefore, in order to solve the problem, we propose a method to equalize accurately even in the noisy environment by using Total Least Squares (TLS). Specifically, the procedures of equalization with noise reduction function are as follows:","PeriodicalId":6765,"journal":{"name":"2019 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS)","volume":"19 1","pages":"1-2"},"PeriodicalIF":0.0000,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Blind Equalizer with Noise Reduction Function\",\"authors\":\"Mitsuru Mashimo, Minoru Komatsu, H. Matsumoto\",\"doi\":\"10.1109/ISPACS48206.2019.8986252\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Recently, in order to compensate for distortion of the received signals, the blind equalization method has been studied. The blind equalizer is designed by using only received signals. However, equalization precision is lower when noise is included in the received signals [1]. Therefore, in order to solve the problem, we propose a method to equalize accurately even in the noisy environment by using Total Least Squares (TLS). Specifically, the procedures of equalization with noise reduction function are as follows:\",\"PeriodicalId\":6765,\"journal\":{\"name\":\"2019 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS)\",\"volume\":\"19 1\",\"pages\":\"1-2\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISPACS48206.2019.8986252\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISPACS48206.2019.8986252","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Recently, in order to compensate for distortion of the received signals, the blind equalization method has been studied. The blind equalizer is designed by using only received signals. However, equalization precision is lower when noise is included in the received signals [1]. Therefore, in order to solve the problem, we propose a method to equalize accurately even in the noisy environment by using Total Least Squares (TLS). Specifically, the procedures of equalization with noise reduction function are as follows: