Sparse Sampling of Signal Innovations [Theory, algorithms, and performance bounds]

Blu T.; Dragotti P.-L.; Vetterli M.; Marziliano P.; Coulot L.

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Sparse Sampling of Signal Innovations [Theory, algorithms, and performance bounds]

机译：信号创新的稀疏采样[理论，算法和性能界限]

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Sparse sampling of continuous-time sparse signals is addressed. In particular, it is shown that sampling at the rate of innovation is possible, in some sense applying Occam''s razor to the sampling of sparse signals. The noisy case is analyzed and solved,

机译：解决了连续时间稀疏信号的稀疏采样问题。特别是，它表明以创新的速度进行采样是可能的，在某种意义上，将Occam剃刀应用于稀疏信号的采样。分析嘈杂的情况，

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来源
《IEEE Signal Processing Magazine》 |2008年第2期|p.31-40|共10页
作者
Blu T.; Dragotti P.-L.; Vetterli M.; Marziliano P.; Coulot L.;
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正文语种 eng
中图分类通信理论;
关键词
continuous time systems; covariance matrices; signal sampling; sparse matrices; ultra wideband communication; Cramer-Rao bounds; Occam razor; continuous-time sparse signal sampling; covariance matrix; ultra-wide band communications;

机译：连续时间系统;协方差矩阵;信号采样;稀疏矩阵;超宽带通信;Cramer-Rao边界;Occam剃刀;连续时间稀疏信号采样;协方差矩阵;超宽带通信;

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Sparse Sampling of Signal Innovations [Theory, algorithms, and performance bounds]

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