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Approximate Least Squares

We present a novel iterative algorithm for approximating the linear least squares solution with low complexity. After a motivation of the algorithm we discuss the algorithm's properties including its complexity, and we present theoretical results as well as simulation based performance results. We describe the analysis of its convergence behavior and show that in the noise free case the algorithm converges to the least squares solution.

preprint2013arXivOpen access
Michael LunglmayrChristoph UnterriederMario Huemer
Data Structures and Algorithms
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Open access3 authors1 topic
Imported metadata coverageMissing code, dataset, citation and institution fields are tracked without dominating the paper.Details
Citations: 0Reviews: 0Saves: 0Code: not linkedDataset: not linkedInstitutions: 0

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Michael LunglmayrChristoph UnterriederMario Huemer

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