D. Pokrajac, Nataša Reljin, Michael Reiter, Stephanie Stotts, Robert Scarborough, Jelena Nikoli
{"title":"水位数据处理的自适应滤波器","authors":"D. Pokrajac, Nataša Reljin, Michael Reiter, Stephanie Stotts, Robert Scarborough, Jelena Nikoli","doi":"10.1109/TELSKS.2007.4376002","DOIUrl":null,"url":null,"abstract":"We describe application of adaptive filters on water level data. The original dataset is a time series of 57,127 measurements and consists of water levels measured at two locations along the St. Jones River, Delaware. After data cleansing to recover for missing data and reduce periodic components in the dataset, adaptive filters are applied to remove the influence of upstream water level on the levels measured downstream.","PeriodicalId":350740,"journal":{"name":"2007 8th International Conference on Telecommunications in Modern Satellite, Cable and Broadcasting Services","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Adaptive Filters for Water Level Data Processing\",\"authors\":\"D. Pokrajac, Nataša Reljin, Michael Reiter, Stephanie Stotts, Robert Scarborough, Jelena Nikoli\",\"doi\":\"10.1109/TELSKS.2007.4376002\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We describe application of adaptive filters on water level data. The original dataset is a time series of 57,127 measurements and consists of water levels measured at two locations along the St. Jones River, Delaware. After data cleansing to recover for missing data and reduce periodic components in the dataset, adaptive filters are applied to remove the influence of upstream water level on the levels measured downstream.\",\"PeriodicalId\":350740,\"journal\":{\"name\":\"2007 8th International Conference on Telecommunications in Modern Satellite, Cable and Broadcasting Services\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2007-11-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2007 8th International Conference on Telecommunications in Modern Satellite, Cable and Broadcasting Services\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/TELSKS.2007.4376002\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2007 8th International Conference on Telecommunications in Modern Satellite, Cable and Broadcasting Services","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/TELSKS.2007.4376002","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
We describe application of adaptive filters on water level data. The original dataset is a time series of 57,127 measurements and consists of water levels measured at two locations along the St. Jones River, Delaware. After data cleansing to recover for missing data and reduce periodic components in the dataset, adaptive filters are applied to remove the influence of upstream water level on the levels measured downstream.
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