{"title":"自适应信号表示:多少是太多?","authors":"D. Donoho","doi":"10.1109/WITS.1994.513884","DOIUrl":null,"url":null,"abstract":"Adaptive signal representations in overcomplete libraries of waveforms have been very popular. One naturally expects that in searching through a large number of signal representations for noisy data, one is at risk of identifying apparent structure in the data which turns out to be spurious, noise-induced artifacts. We show how to use penalties based on the logarithm of library complexity to temper the search, preventing such spurious structure, and giving near-ideal behavior.","PeriodicalId":423518,"journal":{"name":"Proceedings of 1994 Workshop on Information Theory and Statistics","volume":"33 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1994-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Adaptive signal representations: How much is too much?\",\"authors\":\"D. Donoho\",\"doi\":\"10.1109/WITS.1994.513884\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Adaptive signal representations in overcomplete libraries of waveforms have been very popular. One naturally expects that in searching through a large number of signal representations for noisy data, one is at risk of identifying apparent structure in the data which turns out to be spurious, noise-induced artifacts. We show how to use penalties based on the logarithm of library complexity to temper the search, preventing such spurious structure, and giving near-ideal behavior.\",\"PeriodicalId\":423518,\"journal\":{\"name\":\"Proceedings of 1994 Workshop on Information Theory and Statistics\",\"volume\":\"33 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1994-10-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of 1994 Workshop on Information Theory and Statistics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/WITS.1994.513884\",\"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 1994 Workshop on Information Theory and Statistics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WITS.1994.513884","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Adaptive signal representations: How much is too much?
Adaptive signal representations in overcomplete libraries of waveforms have been very popular. One naturally expects that in searching through a large number of signal representations for noisy data, one is at risk of identifying apparent structure in the data which turns out to be spurious, noise-induced artifacts. We show how to use penalties based on the logarithm of library complexity to temper the search, preventing such spurious structure, and giving near-ideal behavior.