低功耗无线传感器的自适应压缩感知

Adam Watkins, Venkata Naresh Mudhireddy, Haibo Wang, S. Tragoudas
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引用次数: 9

摘要

压缩感知已被证明是一种有吸引力的技术在低功耗传感器的实现。本文研究了在压缩感知操作中自适应调整采样率的可行性和潜在的节能性,本文将其称为自适应压缩感知。结果表明,许多生物医学传感器信号的稀疏度随时间而变化,因此可以执行这种自适应操作。研究还表明,自适应操作可以显著降低传感器节点功耗
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Adaptive compressive sensing for low power wireless sensors
Compressive sensing has been demonstrated as an appealing technique in the implementation of low-power sensors. This work studies the feasibility and potential power savings by adaptively adjusting the sampling rates in compressive sensing operations, which is referred to as adaptive compressive sensing in this paper. The results reveal that the sparsity of many biomedical sensor signals varies over time and hence it is possible to perform such adaptive operations. The study also shows that the adaptive operation can lead to significant reduction on sensor node power consumption
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