{"title":"具有参考点和有界稀疏的贪婪相位检索","authors":"Daniel Franz, V. Kuehn","doi":"10.1109/CAMSAP.2017.8313180","DOIUrl":null,"url":null,"abstract":"The phase retrieval problem of recovering a data vector from the squared magnitude of its Fourier transform in general can not be solved uniquely, since the magnitude of the Fourier transform is invariant to a global phase shift, cyclic spatial shift and the conjugate reversal of the signal. We discuss a method of introducing reference points in the signal to resolve aforementioned ambiguities. After specifying requirements for these reference points we present a modification of the GESPAR algorithm to solve the obtained problem.","PeriodicalId":315977,"journal":{"name":"2017 IEEE 7th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP)","volume":"61 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Greedy phase retrieval with reference points and bounded sparsity\",\"authors\":\"Daniel Franz, V. Kuehn\",\"doi\":\"10.1109/CAMSAP.2017.8313180\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The phase retrieval problem of recovering a data vector from the squared magnitude of its Fourier transform in general can not be solved uniquely, since the magnitude of the Fourier transform is invariant to a global phase shift, cyclic spatial shift and the conjugate reversal of the signal. We discuss a method of introducing reference points in the signal to resolve aforementioned ambiguities. After specifying requirements for these reference points we present a modification of the GESPAR algorithm to solve the obtained problem.\",\"PeriodicalId\":315977,\"journal\":{\"name\":\"2017 IEEE 7th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP)\",\"volume\":\"61 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 IEEE 7th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CAMSAP.2017.8313180\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE 7th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CAMSAP.2017.8313180","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Greedy phase retrieval with reference points and bounded sparsity
The phase retrieval problem of recovering a data vector from the squared magnitude of its Fourier transform in general can not be solved uniquely, since the magnitude of the Fourier transform is invariant to a global phase shift, cyclic spatial shift and the conjugate reversal of the signal. We discuss a method of introducing reference points in the signal to resolve aforementioned ambiguities. After specifying requirements for these reference points we present a modification of the GESPAR algorithm to solve the obtained problem.