{"title":"呼吸信号的混沌行为","authors":"J. Tranquillo, T. Ning","doi":"10.1109/NEBC.1997.594952","DOIUrl":null,"url":null,"abstract":"This paper reflects a study to explore the chaotic behavior of respiration signals. The correlation dimension is used to identify the presence of strange attractors and estimate dimensions. The Grassberger-Procaccia algorithm and the embedding method of Takens were used for computation of the chaotic measure. Preliminary results show the presence of an attractor at a dimension of approximately 2.0 when the data length exceeds 100 points.","PeriodicalId":393788,"journal":{"name":"Proceedings of the IEEE 23rd Northeast Bioengineering Conference","volume":"76 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1997-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Chaotic behavior of respiration signals\",\"authors\":\"J. Tranquillo, T. Ning\",\"doi\":\"10.1109/NEBC.1997.594952\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper reflects a study to explore the chaotic behavior of respiration signals. The correlation dimension is used to identify the presence of strange attractors and estimate dimensions. The Grassberger-Procaccia algorithm and the embedding method of Takens were used for computation of the chaotic measure. Preliminary results show the presence of an attractor at a dimension of approximately 2.0 when the data length exceeds 100 points.\",\"PeriodicalId\":393788,\"journal\":{\"name\":\"Proceedings of the IEEE 23rd Northeast Bioengineering Conference\",\"volume\":\"76 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1997-05-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the IEEE 23rd Northeast Bioengineering Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/NEBC.1997.594952\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the IEEE 23rd Northeast Bioengineering Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NEBC.1997.594952","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
This paper reflects a study to explore the chaotic behavior of respiration signals. The correlation dimension is used to identify the presence of strange attractors and estimate dimensions. The Grassberger-Procaccia algorithm and the embedding method of Takens were used for computation of the chaotic measure. Preliminary results show the presence of an attractor at a dimension of approximately 2.0 when the data length exceeds 100 points.
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