使用参数信号和信道模型的贝叶斯单通道盲反卷积

Proceedings of the 1999 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics. WASPAA'99 (Cat. No.99TH8452) Pub Date : 1999-10-01 DOI:10.1109/ASPAA.1999.810872

J. Hopgood, P. Rayner

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引用次数: 12

摘要

本文考虑单通道盲反卷积，将退化的观测信号建模为非平稳源信号与平稳失真算子的卷积。通过将源信号建模为时变自回归过程，通过IIR滤波器对失真算子进行建模，然后使用贝叶斯框架估计失真滤波器的参数，该参数可用于对观测信号进行反卷积，从而实现源信号从观测信号中恢复。本文还讨论了源信号的非平稳特性如何允许唯一地确定畸变算子的识别。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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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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Proceedings of the 1999 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics. WASPAA'99 (Cat. No.99TH8452)

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