{"title":"基于神经网络的体感诱发电位检测生物噪声美白方法","authors":"D.B. Smith, D. Lovely","doi":"10.1109/IEMBS.1995.575371","DOIUrl":null,"url":null,"abstract":"A matched filter is the optimal technique for detecting a known signal buried in additive white noise. Surface recorded somatosensory evoked potentials are corrupted with non-white noise, and so must be whitened before being passed to a matched filter. The authors evaluated the viability of selected artificial neural networks in whitening the noise of recorded evoked potentials.","PeriodicalId":20509,"journal":{"name":"Proceedings of 17th International Conference of the Engineering in Medicine and Biology Society","volume":"38 1","pages":"803-804 vol.1"},"PeriodicalIF":0.0000,"publicationDate":"1995-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"A neural network based approach to whitening biological noise for somatosensory evoked potential detection\",\"authors\":\"D.B. Smith, D. Lovely\",\"doi\":\"10.1109/IEMBS.1995.575371\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A matched filter is the optimal technique for detecting a known signal buried in additive white noise. Surface recorded somatosensory evoked potentials are corrupted with non-white noise, and so must be whitened before being passed to a matched filter. The authors evaluated the viability of selected artificial neural networks in whitening the noise of recorded evoked potentials.\",\"PeriodicalId\":20509,\"journal\":{\"name\":\"Proceedings of 17th International Conference of the Engineering in Medicine and Biology Society\",\"volume\":\"38 1\",\"pages\":\"803-804 vol.1\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1995-09-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of 17th International Conference of the Engineering in Medicine and Biology Society\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IEMBS.1995.575371\",\"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 17th International Conference of the Engineering in Medicine and Biology Society","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IEMBS.1995.575371","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A neural network based approach to whitening biological noise for somatosensory evoked potential detection
A matched filter is the optimal technique for detecting a known signal buried in additive white noise. Surface recorded somatosensory evoked potentials are corrupted with non-white noise, and so must be whitened before being passed to a matched filter. The authors evaluated the viability of selected artificial neural networks in whitening the noise of recorded evoked potentials.
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