Efficient spectral analysis in the missing data case using sparse ML methods. Glentis, G., Karlsson, J., Jakobsson, A., & Li, J. In 2014 22nd European Signal Processing Conference (EUSIPCO), pages 1746-1750, Sep., 2014.
Efficient spectral analysis in the missing data case using sparse ML methods [pdf]Paper  abstract   bibtex   
Given their wide applicability, several sparse high-resolution spectral estimation techniques and their implementation have been examined in the recent literature. In this work, we further the topic by examining a computationally efficient implementation of the recent SMLA algorithms in the missing data case. The work is an extension of our implementation for the uniformly sampled case, and offers a notable computational gain as compared to the alternative implementations in the missing data case.

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