{"title":"生物雷达数据分析的经验模态分解算法","authors":"L. Anishchenko","doi":"10.1109/COMCAS.2015.7360429","DOIUrl":null,"url":null,"abstract":"In present work we discuss the usage of empirical mode decomposition algorithm for bioradar data processing. The algorithm of data processing is considered and the value of the threshold criteria is chosen according to the results of the experimental data processing. It is shown that preprocessing of raw bioradar data, which compensate the difference in amplitude of breathing and heartbeat signals, increases the effectiveness of empirical mode decomposition algorithm in bioradar data processing.","PeriodicalId":431569,"journal":{"name":"2015 IEEE International Conference on Microwaves, Communications, Antennas and Electronic Systems (COMCAS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Empirical mode decomposition algorithm for bioradar data analysis\",\"authors\":\"L. Anishchenko\",\"doi\":\"10.1109/COMCAS.2015.7360429\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In present work we discuss the usage of empirical mode decomposition algorithm for bioradar data processing. The algorithm of data processing is considered and the value of the threshold criteria is chosen according to the results of the experimental data processing. It is shown that preprocessing of raw bioradar data, which compensate the difference in amplitude of breathing and heartbeat signals, increases the effectiveness of empirical mode decomposition algorithm in bioradar data processing.\",\"PeriodicalId\":431569,\"journal\":{\"name\":\"2015 IEEE International Conference on Microwaves, Communications, Antennas and Electronic Systems (COMCAS)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-12-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 IEEE International Conference on Microwaves, Communications, Antennas and Electronic Systems (COMCAS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/COMCAS.2015.7360429\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 IEEE International Conference on Microwaves, Communications, Antennas and Electronic Systems (COMCAS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/COMCAS.2015.7360429","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Empirical mode decomposition algorithm for bioradar data analysis
In present work we discuss the usage of empirical mode decomposition algorithm for bioradar data processing. The algorithm of data processing is considered and the value of the threshold criteria is chosen according to the results of the experimental data processing. It is shown that preprocessing of raw bioradar data, which compensate the difference in amplitude of breathing and heartbeat signals, increases the effectiveness of empirical mode decomposition algorithm in bioradar data processing.
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