{"title":"双复值自适应滤波在风廓线预测中的应用","authors":"Xiaoming Gou, Zhiwen Liu, Zheyi Fan, Yougen Xu","doi":"10.1109/ICDSP.2014.6900695","DOIUrl":null,"url":null,"abstract":"A variant of the least mean squares (LMS) filtering algorithm is proposed based on bicomplex numbers. Experiments on recorded data for wind profile prediction show its comparable or accelerated convergence rate compared with quaternion-based approaches. The benefits of further exploitation of bicomplex numbers can be projected, including frequency-domain methods and augmented model-based methods.","PeriodicalId":301856,"journal":{"name":"2014 19th International Conference on Digital Signal Processing","volume":"93 3","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Bicomplex-valued adaptive filtering with application to wind profile prediction\",\"authors\":\"Xiaoming Gou, Zhiwen Liu, Zheyi Fan, Yougen Xu\",\"doi\":\"10.1109/ICDSP.2014.6900695\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A variant of the least mean squares (LMS) filtering algorithm is proposed based on bicomplex numbers. Experiments on recorded data for wind profile prediction show its comparable or accelerated convergence rate compared with quaternion-based approaches. The benefits of further exploitation of bicomplex numbers can be projected, including frequency-domain methods and augmented model-based methods.\",\"PeriodicalId\":301856,\"journal\":{\"name\":\"2014 19th International Conference on Digital Signal Processing\",\"volume\":\"93 3\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-09-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 19th International Conference on Digital Signal Processing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICDSP.2014.6900695\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 19th International Conference on Digital Signal Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICDSP.2014.6900695","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Bicomplex-valued adaptive filtering with application to wind profile prediction
A variant of the least mean squares (LMS) filtering algorithm is proposed based on bicomplex numbers. Experiments on recorded data for wind profile prediction show its comparable or accelerated convergence rate compared with quaternion-based approaches. The benefits of further exploitation of bicomplex numbers can be projected, including frequency-domain methods and augmented model-based methods.