Journal
JOURNAL OF FOURIER ANALYSIS AND APPLICATIONS
Volume 19, Issue 2, Pages 256-269Publisher
SPRINGER BIRKHAUSER
DOI: 10.1007/s00041-012-9248-z
Keywords
Kaczmarz method; Randomized Kaczmarz method; Computer tomography; Signal processing
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We present a Projection onto Convex Sets (POCS) type algorithm for solving systems of linear equations. POCS methods have found many applications ranging from computer tomography to digital signal and image processing. The Kaczmarz method is one of the most popular solvers for overdetermined systems of linear equations due to its speed and simplicity. Here we introduce and analyze an extension of the Kaczmarz method that iteratively projects the estimate onto a solution space given by two randomly selected rows. We show that this projection algorithm provides exponential convergence to the solution in expectation. The convergence rate improves upon that of the standard randomized Kaczmarz method when the system has correlated rows. Experimental results confirm that in this case our method significantly outperforms the randomized Kaczmarz method.
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