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Sparse Principal Component Analysis (SPCA) is an important technique for high-dimensional data analysis, improving interpretability by imposing sparsity on principal components. However, existing methods often fail to simultaneously…

Machine Learning · Computer Science 2026-03-03 Difei Cheng , Qiao Hu

Principal Component Analysis (PCA) is a well-known technique used to decorrelate a set of vectors. It has been applied to explore the star formation history of galaxies or to determine distances of mass-lossing stars. Here we apply PCA to…

Astrophysics · Physics 2007-10-23 Stavros Akras , Panayotis Boumis

Speckle noise is an inherent disturbance in coherent imaging systems such as digital holography, synthetic aperture radar, optical coherence tomography, or ultrasound systems. These systems usually produce only single observation per view…

Image and Video Processing · Electrical Eng. & Systems 2022-05-19 Tsung-Ming Tai , Yun-Jie Jhang , Wen-Jyi Hwang , Chau-Jern Cheng

Performance of nuclear threat detection systems based on gamma-ray spectrometry often strongly depends on the ability to identify the part of measured signal that can be attributed to background radiation. We have successfully applied a…

Machine Learning · Computer Science 2016-05-30 P. Tandon , P. Huggins , A. Dubrawski , S. Labov , K. Nelson

In this paper, we study the problem of sparse Principal Component Analysis (PCA) in the high-dimensional setting with missing observations. Our goal is to estimate the first principal component when we only have access to partial…

Statistics Theory · Mathematics 2012-06-04 Karim Lounici

This letter introduces a physics-informed self-supervised framework for sonar image despeckling that reformulates despeckling as residual consistency in the homomorphic log domain. By constraining the log-ratio residual to obey…

Computer Vision and Pattern Recognition · Computer Science 2026-05-26 Swapna Pillai , Siddharth Singh Savner , Sujit Kumar Sahoo

Suppose we observe data of the form $Y_i = D_i (S_i + \varepsilon_i) \in \mathbb{R}^p$ or $Y_i = D_i S_i + \varepsilon_i \in \mathbb{R}^p$, $i=1,\ldots,n$, where $D_i \in \mathbb{R}^{p\times p}$ are known diagonal matrices, $\varepsilon_i$…

Statistics Theory · Mathematics 2018-11-05 Edgar Dobriban , William Leeb , Amit Singer

Principal Component Analysis (PCA) is applied to a variety of blazars to examine X-ray spectral variability. Data from nine different objects are analysed in two ways: long-term, which examines variability trends across years or decades,…

High Energy Astrophysical Phenomena · Physics 2018-08-08 Dennis Gallant , Luigi C. Gallo , Michael L. Parker

We have conducted an angular differential imaging survey with NIRC2 at Keck in search of close-in substellar companions to a sample of seven systems with confirmed planetary-mass companions (PMCs) on wide orbits (>50 AU). These…

Earth and Planetary Astrophysics · Physics 2016-08-17 Marta L. Bryan , Brendan P. Bowler , Heather A. Knutson , Adam L. Kraus , Sasha Hinkley , Dimitri Mawet , Eric L. Nielsen , Sarah C. Blunt

Residual speckles in adaptive optics (AO) images represent a well-known limitation on the achievement of the contrast needed for faint source detection. Speckles in AO imagery can be the result of either residual atmospheric aberrations,…

Object-motion-based speckle correlation can recover hidden objects from any inhomogeneous medium, which takes advantage of the inherent connection that the cross-correlation between speckle patterns can reflect the autocorrelation of…

Optics · Physics 2023-12-01 Zhao Wang , Rui Ma , Mingzhu She , Anda Shi , Weili Zhang

Infrared (IR) spectroscopy is an indispensable tool for many practical applications including material analysis and sensing. Existing IR spectroscopy techniques face challenges related to the inferior performance and the high cost of…

Optics · Physics 2017-03-13 Anna Paterova , Shaun Lung , Dmitry Kalashnikov , Leonid Krivitsky

Optical imperfections, misalignments, aberrations, and even dust can significantly limit sensitivity in high-contrast imaging systems such as coronagraphs. An upstream deformable mirror (DM) in the pupil can be used to correct or compensate…

Instrumentation and Methods for Astrophysics · Physics 2015-06-15 Johanan L. Codona , Matthew Kenworthy

Optical imaging through scattering media is a long-standing challenge. Although many approaches have been developed to focus light or image objects through scattering media, they are either invasive, restricted to stationary or…

Optics · Physics 2022-10-11 Xingchen Zhao , Xiaoyu Nie , Zhenhuan Yi , Tao Peng , Marlan O. Scully

Substellar companions such as exoplanets and brown dwarfs exhibit changes in brightness arising from top-of-atmosphere inhomogeneities, providing insights into their atmospheric structure and dynamics. This variability can be measured in…

We study semiparametric factor models in high-dimensional panels where the factor loadings consist of a nonparametric component explained by observed covariates and an idiosyncratic component capturing unobserved heterogeneity. A key…

Methodology · Statistics 2025-12-09 Sijie Zheng

We study sparse principal component analysis in the high-dimensional, sample-limited regime, aiming to recover a leading component supported on a few coordinates. Despite extensive progress, most methods and analyses are tailored to the…

Information Theory · Computer Science 2025-12-18 Mengchu Xu , Jian Wang , Yonina C. Eldar

(Abbreviated) Kepler planet candidates require both spectroscopic and imaging follow-up observations to rule out false positives and detect blended stars. [...] In this paper, we examine a sample of 11 Kepler host stars with companions…

The coded-mask spectrometer-telescope SPI on board the INTEGRAL observatory records photons in the energy range between 20 and 8000 keV. A robust and versatile method to model the dominating instrumental background (BG) radiation is…

High Energy Astrophysical Phenomena · Physics 2019-06-19 Thomas Siegert , Roland Diehl , Christoph Weinberger , Moritz M. M. Pleintinger , Jochen Greiner , Xiaoling Zhang

We present the first tests of a new method, the Correlated Component Analysis (CCA) based on second-order statistics, to estimate the mixing matrix, a key ingredient to separate astrophysical foregrounds superimposed to the Cosmic Microwave…

Astrophysics · Physics 2016-04-26 A. Bonaldi , L. Bedini , E. Salerno , C. Baccigalupi , G. De Zotti