Skillful Coupled Atmosphere‐Ocean Forecasts on Interannual to Decadal Timescales Using a Linear Inverse Model
Sign Up to like & getrecommendations! Published in 2023 at "Earth and Space Science"
DOI: 10.1029/2022ea002679
Abstract: There are two major challenges to improving interannual to decadal forecasts: (a) consistently initializing the coupled system so that variability is not dominated by initial imbalances, and (b) having a large sample of different initial… read more here.
Keywords: using linear; linear inverse; model; interannual decadal ... See more keywords
Eigenvalue-free iterative shrinkage-thresholding algorithm for solving the linear inverse problems
Sign Up to like & getrecommendations! Published in 2021 at "Inverse Problems"
DOI: 10.1088/1361-6420/abf9e8
Abstract: The iterative shrinkage threshold algorithm (ISTA) is widely used in solving linear inverse problems due to its simplicity. However, it depends on the calculation of eigenvalues during the iterative process, which will cost a lot… read more here.
Keywords: linear inverse; iterative shrinkage; inverse problems; solving linear ... See more keywords
Solving Sparse Linear Inverse Problems in Communication Systems: A Deep Learning Approach With Adaptive Depth
Sign Up to like & getrecommendations! Published in 2021 at "IEEE Journal on Selected Areas in Communications"
DOI: 10.1109/jsac.2020.3036959
Abstract: Sparse signal recovery problems from noisy linear measurements appear in many areas of wireless communications. In recent years, deep learning (DL) based approaches have attracted interests of researchers to solve the sparse linear inverse problem… read more here.
Keywords: sparse linear; depth; approach; linear inverse ... See more keywords
A Hybrid Iterative Thresholding Method for Solving Sparsity-Regularized Linear Inverse Problems and Its Application in Seismic Sparse-Spike Deconvolution
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Geoscience and Remote Sensing Letters"
DOI: 10.1109/lgrs.2023.3278026
Abstract: Sparsity-regularized linear inverse problem has served as the base in many disciplines, such as remote sensing imaging, image processing and analysis, seismic deconvolution, compressed sensing, medical imaging, and so forth. The iterative hard thresholding algorithm… read more here.
Keywords: linear inverse; sparsity regularized; regularized linear; method ... See more keywords
Deep Coupled-Representation Learning for Sparse Linear Inverse Problems With Side Information
Sign Up to like & getrecommendations! Published in 2019 at "IEEE Signal Processing Letters"
DOI: 10.1109/lsp.2019.2929869
Abstract: In linear inverse problems, the goal is to recover a target signal from undersampled, incomplete or noisy linear measurements. Typically, the recovery relies on complex numerical optimization methods; recent approaches perform an unfolding of a… read more here.
Keywords: side information; deep coupled; linear inverse; inverse problems ... See more keywords
On Ambiguity in Linear Inverse Problems: Entrywise Bounds on Nearly Data-Consistent Solutions and Entrywise Condition Numbers
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Signal Processing"
DOI: 10.1109/tsp.2023.3257989
Abstract: Ill-posed linear inverse problems appear frequently in various signal processing applications. It can be very useful to have theoretical characterizations that quantify the level of ill-posedness for a given inverse problem and the degree of… read more here.
Keywords: inverse problems; nearly data; inverse; condition ... See more keywords
Predictability of Marine Heatwaves off Western Australia using a Linear Inverse Model
Sign Up to like & getrecommendations! Published in 2023 at "Journal of Climate"
DOI: 10.1175/jcli-d-22-0692.1
Abstract: Marine heatwaves (MHWs) off Western Australia (110°E–116°E, 22°S–32°S; hereafter, WA MHWs) can cause devastating ecological impacts, as was evidenced by the 2011 extreme event. Previous studies suggest that La Niña is the major large-scale driver… read more here.
Keywords: mhws; marine heatwaves; linear inverse; model ... See more keywords
Principal Component Wavelet Networks for Solving Linear Inverse Problems
Sign Up to like & getrecommendations! Published in 2021 at "Symmetry"
DOI: 10.3390/sym13061083
Abstract: In this paper we propose a novel learning-based wavelet transform and demonstrate its utility as a representation in solving a number of linear inverse problems—these are asymmetric problems, where the forward problem is easy to… read more here.
Keywords: component wavelet; principal component; inverse problems; linear inverse ... See more keywords