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Theory and applications of compressed sensing

机译:压缩传感理论与应用

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摘要

Compressed sensing is a novel research area, which was introduced in 2006, and since then has already become a key concept in various areas of applied mathematics, computer science, and electrical engineering. It surprisingly predicts that high-dimensional signals, which allow a sparse representation by a suitable basis or, more generally, a frame, can be recovered from what was previously considered highly incomplete linear measurements by using efficient algorithms. This article shall serve as an introduction to and a survey about compressed sensing.
机译:压缩感测是一个新兴的研究领域,于2006年引入,从那时起,它已成为应用数学,计算机科学和电气工程各个领域的关键概念。令人惊讶地预测,可以通过使用高效算法从以前认为高度不完整的线性测量中恢复高维信号,该高维信号允许以适当的基础或更普遍地以帧进行稀疏表示。本文将作为压缩感知的简介和调查。

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