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首页> 外文会议>International Conference on Renewable Energies for Developing Countries >Algorithms for the Iterative Estimation of Discrete-Valued Sparse Vectors
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Algorithms for the Iterative Estimation of Discrete-Valued Sparse Vectors

机译：离散值稀疏向量的迭代估计算法

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摘要

In Compressed Sensing, a real-valued sparse vector has to be estimated from an underdetermined system of linear equations. In many applications, however, the elements of the sparse vector are drawn from a finite set. For the estimation of these discrete-valued vectors, matched algorithms are required which take the additional knowledge of the discrete nature into account. In this paper, the estimation problem is treated from a communications engineering point of view. A powerful new algorithm incorporating techniques known from digital communications and information theory is derived. For comparison, Turbo Compressed Sensing is adapted to the discrete setup and a simplified and generalized notation is presented. The performance of the algorithms is covered by numerical simulations.
机译：在压缩感测中，必须从欠定的线性方程组中估计实值稀疏矢量。然而，在许多应用中，稀疏向量的元素是从有限集合中得出的。为了估计这些离散值向量，需要匹配算法，该算法考虑了离散性质的附加知识。本文从通信工程的角度处理估计问题。得出了一种强大的新算法，该算法结合了从数字通信和信息理论中获知的技术。为了进行比较，Turbo Compressed Sensing适用于离散设置，并给出了简化和通用的表示法。数值模拟涵盖了算法的性能。

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