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Compressed sensing and r-algorithms

机译:压缩感测和r算法

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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.
机译:本文涉及作者的研究进展。这不是完成的工作的论文。我们有一个主要的例子,核规范优化问题,可以直观而正式地进行描述。我们相信基于r算法的问题解决方案的正确表述(和实现)将具有普遍应用,并且我们仍在寻求这种表述(和实现)。它位于r算法的矩阵扩展的附近。在该框架中,我们考虑了压缩感知的方法和问题,审查了该领域的新结果,并研究了r算法的应用及其对解决问题的解决方案的改进,从而从其元素的采样中恢复了数据矩阵。

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