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SEQUENTIAL LOCAL FRI SAMPLING OF INFINITE STREAMS OF DIRACS

机译:序列局部临时狄料狄拉克斯流液

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The theory of sampling signals with finite rate of innovation (FRI) has shown that it is possible to perfectly recover classes of non-bandlimited signals such as streams of Diracs from uniform samples. Most of previous papers, however, have to some extent only focused on the sampling of periodic or finite duration signals. In this paper we propose a novel method that is able to reconstruct infinite streams of Diracs, even in high noise scenarios. We sequentially process the discrete samples and output locations and amplitudes of the Diracs in real-time. We first establish conditions for perfect reconstruction in the noiseless case and then present the sequential algorithm for the noisy scenario. We also show that we can achieve a high reconstruction accuracy of 1000 Diracs for SNRs as low as 5dB.
机译:具有有限速率的采样信号(FRI)的采样信号表明,可以完全恢复来自均匀样品的狄拉克斯的非带状信号等类别。然而,之前的大多数论文必须在某种程度上仅关注周期性或有限持续时间信号的采样。在本文中,我们提出了一种新的方法,即使在高噪声场景中,也能够重建无限的DIRAC流。我们在实时顺序地处理离散的样本和输出位置和狄拉克的幅度。我们首先在无噪声案例中建立完美重建的条件,然后介绍嘈杂场景的顺序算法。我们还表明,我们可以实现高达5dB的SNR的高重建精度为1000个DIACS。

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