Signal Recovery From 1-Bit Quantized Noisy Samples via Adaptive Thresholding
Signal Recovery From 1-Bit Quantized Noisy Samples via Adaptive Thresholding
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DOI：
10.1109/acssc.2018.8645383
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发表时间：
2018-10
期刊：
影响因子：
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通讯作者：
Shahin Khobahi;M. Soltanalian
中科院分区：
文献类型：
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作者：
Shahin Khobahi;M. Soltanalian
在本文中，我们考虑从1位噪声测量信号恢复的问题。我们提出了一种有效的方法来获得感兴趣的信号的估计时，测量被损坏的白色或有色噪声。据我们所知，所提出的框架是在1位采样和信号恢复领域的先驱努力，提供了一个统一的框架来处理噪声的存在与任意协方差矩阵，包括有色噪声。所提出的方法是基于约束二次规划（CQP）制定利用自适应量化阈值的方法，进一步使我们能够准确地恢复其1位噪声测量的信号的兴趣。此外，由于所提出的方法的自适应性质，它可以恢复固定和时变参数从他们的量化1位样本。
In this paper, we consider the problem of signal recovery from 1-bit noisy measurements. We present an efficient method to obtain an estimation of the signal of interest when the measurements are corrupted by white or colored noise. To the best of our knowledge, the proposed framework is the pioneer effort in the area of 1-bit sampling and signal recovery in providing a unified framework to deal with the presence of noise with an arbitrary covariance matrix including that of the colored noise. The proposed method is based on a constrained quadratic program (CQP) formulation utilizing an adaptive quantization thresholding approach, that further enables us to accurately recover the signal of interest from its 1-bit noisy measurements. In addition, due to the adaptive nature of the proposed method, it can recover both fixed and time-varying parameters from their quantized 1-bit samples.