超分辨显微镜的随机多元矩阵铅笔法

M. Ehler, Stefan Kunis, T. Peter, C. Richter
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引用次数: 11

摘要

矩阵铅笔法是一种基于特征值的稀疏指数和参数辨识方法。给出了一种基于同时对角化的多元指数和重构算法。随机化被用于将同时对角化简化为单个随机矩阵的特征分解。为了验证该算法的可行性,将该算法应用于合成和实验荧光显微数据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A randomized multivariate matrix pencil method for superresolution microscopy
The matrix pencil method is an eigenvalue based approach for the parameter identification of sparse exponential sums. We derive a reconstruction algorithm for multivariate exponential sums that is based on simultaneous diagonalization. Randomization is used and quantified to reduce the simultaneous diagonalization to the eigendecomposition of a single random matrix. To verify feasibility, the algorithm is applied to synthetic and experimental fluorescence microscopy data.
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