{"title":"基于特定字典的心电压缩感知结果及其验证","authors":"M. Fira, L. Goras, Nicolae Cleju, C. Barabasa","doi":"10.2498/iti.2012.0362","DOIUrl":null,"url":null,"abstract":"The paper presents a new method and results regarding the compressed sensing (CS) and classification of ECG waveforms using a general dictionary as well as specific dictionaries built using normal and pathological cardiac patterns. The proposed method has been validated by computation of the distortion errors between the original and the reconstructed signals and by the classification ratio of the reconstructed signals obtained with the k-nearest neighbors (KNN) algorithm.","PeriodicalId":135105,"journal":{"name":"Proceedings of the ITI 2012 34th International Conference on Information Technology Interfaces","volume":"221 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":"{\"title\":\"Results on ECG compressed sensing using specific dictionaries and its validation\",\"authors\":\"M. Fira, L. Goras, Nicolae Cleju, C. Barabasa\",\"doi\":\"10.2498/iti.2012.0362\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The paper presents a new method and results regarding the compressed sensing (CS) and classification of ECG waveforms using a general dictionary as well as specific dictionaries built using normal and pathological cardiac patterns. The proposed method has been validated by computation of the distortion errors between the original and the reconstructed signals and by the classification ratio of the reconstructed signals obtained with the k-nearest neighbors (KNN) algorithm.\",\"PeriodicalId\":135105,\"journal\":{\"name\":\"Proceedings of the ITI 2012 34th International Conference on Information Technology Interfaces\",\"volume\":\"221 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-06-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"9\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the ITI 2012 34th International Conference on Information Technology Interfaces\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2498/iti.2012.0362\",\"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 ITI 2012 34th International Conference on Information Technology Interfaces","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2498/iti.2012.0362","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Results on ECG compressed sensing using specific dictionaries and its validation
The paper presents a new method and results regarding the compressed sensing (CS) and classification of ECG waveforms using a general dictionary as well as specific dictionaries built using normal and pathological cardiac patterns. The proposed method has been validated by computation of the distortion errors between the original and the reconstructed signals and by the classification ratio of the reconstructed signals obtained with the k-nearest neighbors (KNN) algorithm.
京公网安备 11010802042870号
京ICP备2023020795号-1
分享
求助内容：
应助结果提醒方式：
扫码关注我们
