An iteratively reweighted least-squares approach to adaptive robust adjustment of parameters in linear regression models with autoregressive and t-distributed deviations
Sign Up to like & getrecommendations! Published in 2017 at "Journal of Geodesy"
DOI: 10.1007/s00190-017-1062-6
Abstract: In this paper, we investigate a linear regression time series model of possibly outlier-afflicted observations and autocorrelated random deviations. This colored noise is represented by a covariance-stationary autoregressive (AR) process, in which the independent error… read more here.
Keywords: reweighted least; regression; linear regression; iteratively reweighted ... See more keywords
PRIM: An Efficient Preconditioning Iterative Reweighted Least Squares Method for Parallel Brain MRI Reconstruction
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DOI: 10.1007/s12021-017-9354-9
Abstract: The most recent history of parallel Magnetic Resonance Imaging (pMRI) has in large part been devoted to finding ways to reduce acquisition time. While joint total variation (JTV) regularized model has been demonstrated as a… read more here.
Keywords: reweighted least; iterative reweighted; least squares; preconditioning iterative ... See more keywords
Image Denoising and Refinement Based on an Iteratively Reweighted Least Squares Filter
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DOI: 10.1007/s12205-020-2103-x
Abstract: This paper presents a method to reduce noise and refine detail features of a scene based on an iteratively reweighted least squares method. The performance of the proposed filter, called the iteratively reweighted least squares… read more here.
Keywords: reweighted least; least squares; based iteratively; iteratively reweighted ... See more keywords
Convergence and stability of iteratively reweighted least squares for low-rank matrix recovery
Sign Up to like & getrecommendations! Published in 2017 at "Inverse Problems and Imaging"
DOI: 10.3934/ipi.2017030
Abstract: In this paper, we study the theoretical properties of iteratively reweighted least squares algorithm for recovering a matrix (IRLS-M for short) from noisy linear measurements. The IRLS-M was proposed by Fornasier et al. (2011) [… read more here.
Keywords: begin document; reweighted least; least squares; iteratively reweighted ... See more keywords