{"title":"使用参数信号和信道模型的贝叶斯单通道盲反卷积","authors":"J. Hopgood, P. Rayner","doi":"10.1109/ASPAA.1999.810872","DOIUrl":null,"url":null,"abstract":"This paper considers single channel blind deconvolution, in which a degraded observed signal is modelled as the convolution of a non-stationary source signal with a stationary distortion operator. Recovery of the source signal from the observed signal is achieved by modelling the source signal as a time-varying autoregressive process, the distortion operator by a IIR filter, and then using a Bayesian framework to estimate the parameters of the distorting filter, which can be used to deconvolve the observed signal. The paper also discusses how the non-stationary properties of the source signal allow the identification of the distortion operator to be uniquely determined.","PeriodicalId":229733,"journal":{"name":"Proceedings of the 1999 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics. WASPAA'99 (Cat. No.99TH8452)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1999-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":"{\"title\":\"Bayesian single channel blind deconvolution using parametric signal and channel models\",\"authors\":\"J. Hopgood, P. Rayner\",\"doi\":\"10.1109/ASPAA.1999.810872\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper considers single channel blind deconvolution, in which a degraded observed signal is modelled as the convolution of a non-stationary source signal with a stationary distortion operator. Recovery of the source signal from the observed signal is achieved by modelling the source signal as a time-varying autoregressive process, the distortion operator by a IIR filter, and then using a Bayesian framework to estimate the parameters of the distorting filter, which can be used to deconvolve the observed signal. The paper also discusses how the non-stationary properties of the source signal allow the identification of the distortion operator to be uniquely determined.\",\"PeriodicalId\":229733,\"journal\":{\"name\":\"Proceedings of the 1999 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics. WASPAA'99 (Cat. No.99TH8452)\",\"volume\":\"30 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1999-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"12\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 1999 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics. WASPAA'99 (Cat. No.99TH8452)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ASPAA.1999.810872\",\"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 1999 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics. WASPAA'99 (Cat. No.99TH8452)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ASPAA.1999.810872","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Bayesian single channel blind deconvolution using parametric signal and channel models
This paper considers single channel blind deconvolution, in which a degraded observed signal is modelled as the convolution of a non-stationary source signal with a stationary distortion operator. Recovery of the source signal from the observed signal is achieved by modelling the source signal as a time-varying autoregressive process, the distortion operator by a IIR filter, and then using a Bayesian framework to estimate the parameters of the distorting filter, which can be used to deconvolve the observed signal. The paper also discusses how the non-stationary properties of the source signal allow the identification of the distortion operator to be uniquely determined.
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