{"title":"高阶统计量和极端波","authors":"E. Powers, In-Seung Park, S. Im, S. Mehta, E. Yi","doi":"10.1109/HOST.1997.613495","DOIUrl":null,"url":null,"abstract":"A sparse second-order time-domain Volterra model is used to decompose a random (sea) wave train into its first- and second-order components. Extreme waves are shown to result from short-term phase locking of the first- and second-order components. The feasibility of using a wavelet-based bicoherence \"spectrum\" to detect the strong, but short lived, phase coupling is investigated. The results are encouraging and suggest the wavelet-based bicoherence is a topic worth considering further.","PeriodicalId":305928,"journal":{"name":"Proceedings of the IEEE Signal Processing Workshop on Higher-Order Statistics","volume":"101 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1997-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Higher-order statistics and extreme waves\",\"authors\":\"E. Powers, In-Seung Park, S. Im, S. Mehta, E. Yi\",\"doi\":\"10.1109/HOST.1997.613495\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A sparse second-order time-domain Volterra model is used to decompose a random (sea) wave train into its first- and second-order components. Extreme waves are shown to result from short-term phase locking of the first- and second-order components. The feasibility of using a wavelet-based bicoherence \\\"spectrum\\\" to detect the strong, but short lived, phase coupling is investigated. The results are encouraging and suggest the wavelet-based bicoherence is a topic worth considering further.\",\"PeriodicalId\":305928,\"journal\":{\"name\":\"Proceedings of the IEEE Signal Processing Workshop on Higher-Order Statistics\",\"volume\":\"101 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1997-07-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the IEEE Signal Processing Workshop on Higher-Order Statistics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/HOST.1997.613495\",\"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 Signal Processing Workshop on Higher-Order Statistics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/HOST.1997.613495","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A sparse second-order time-domain Volterra model is used to decompose a random (sea) wave train into its first- and second-order components. Extreme waves are shown to result from short-term phase locking of the first- and second-order components. The feasibility of using a wavelet-based bicoherence "spectrum" to detect the strong, but short lived, phase coupling is investigated. The results are encouraging and suggest the wavelet-based bicoherence is a topic worth considering further.
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