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首页> 外文会议>Proceedings of the 2009 IEEE Dallas Circuits and Systems Workshop >Digitally assisted Analog Compressive Sensing
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Digitally assisted Analog Compressive Sensing

机译：数字辅助模拟压缩传感

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摘要

Analog Compressive Sensing (CS) provides a novel strategy to sample and process wideband sparse signals at sub-Nyquist rate. This scheme exploits the signal sparsity to reduce the sampling rate requirements. The analog compressive sensing system performance is greatly impacted by the accuracy of analog circuit components, especially with the scaling of CMOS technology. In this paper, the effect of the circuit imperfections in the analog compressive sensing architecture based on Parallel Segmented Compressive Sensing (PSCS) is discussed, such as the finite settling time, the timing uncertainty and so on. An iterative background calibration algorithm based on LMS (Least Mean Square) is proposed, which is shown to be able to effectively calibrate the error due to the circuit nonideal factors.
机译：模拟压缩感测（CS）提供了一种新颖的策略来以亚奈奎斯特速率采样和处理宽带稀疏信号。该方案利用信号稀疏性来降低采样率要求。模拟压缩传感系统的性能受模拟电路组件的精度影响很大，尤其是随着CMOS技术的扩展。本文讨论了电路缺陷在基于并行分段压缩传感（PSCS）的模拟压缩传感体系结构中的影响，例如有限的建立时间，时序不确定性等。提出了一种基于LMS（最小均方）的迭代背景校正算法，该算法能够有效校正由于电路非理想因素引起的误差。

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