压缩感知和r-算法

N. Glazunov
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引用次数: 2

摘要

这篇文章是关于作者正在进行的研究。它不是一篇已完成的论文。我们有一个主要的例子,核范数优化问题,这是直观和形式化的描述。我们相信,基于r-算法的问题解决方案的适当公式(和实现)将具有普遍的应用,我们仍在寻求公式(和实现)。它位于r算法的矩阵扩展的邻域内。在该框架中,我们考虑了压缩感知的方法和问题,回顾了该领域的新成果,并研究了r-算法的应用及其修改,以解决从其元素的采样中恢复数据矩阵的问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Compressed sensing and r-algorithms
This paper concerns the author's research in progress. It is not a paper of a completed work. We have a principal example, nuclear norm optimization problem, which is described intuitively and formally. We believe that the proper formulation (and implementation) of r-algorithm based solution of the problem will have general applications and we are still seeking that formulation (and implementation). It lies somewhere in the neighborhood of a matrix extension of r-algorithms. In the framework we consider approaches and problems of compressed sensing, review new results in the field and investigate applications of r-algorithms and their modifications to solution of the problem recovering the data matrix from a sampling of its elements.
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