压缩感知重构的综合软件工具

Sanja Zuković, Milica Medenica, I. Orović, S. Stankovic
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引用次数: 0

摘要

提出了一种用于压缩感知信号重建的综合软件工具。压缩感知是一种新的信号感知方法,旨在减少实际数字系统对资源的需求。使用非常复杂的数学算法,仅使用少量随机选择的样本就可以重建压缩感知信号。因此,所提出的软件包含并实现了不同的信号重构算法,提供了不同的重构性能。在软件中包含其他方法也是一种开放的可能性。在这里,我们将介绍建议的工具提供的一些最重要的算法和功能。软件的选择和效率将在合成信号和实际信号上进行演示。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Synthetic software tool for compressive sensing reconstruction
A synthetic software tool for the reconstruction of Compressive Sensed signals is proposed. Compressive Sensing is a new signal sensing approach aiming to decrease the requirements for resources in real digital systems. Using very complex mathematical algorithms, it is possible to reconstruct the Compressive Sensed signals using just a small number of randomly chosen samples. Accordingly, the proposed software comprises and implements different signal reconstruction algorithms, providing different reconstruction performances. There is also an open possibility to include other methods within the software. Here, we will present just some of the most important algorithms and functionalities provided by the proposed tool. The software options and efficiency will be demonstrated on synthetic and real-world signals.
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