Related papers: Advances in the RXTE Proportional Counter Array Ca…
Principal Component Analysis (PCA) is an efficient tool to optimize the multiparameter tests of general relativity (GR) where one tests for simultaneous deviations in multiple post-Newtonian (PN) phasing coefficients by introducing…
Large Area X-ray Proportional Counter (LAXPC) is one of the major AstroSat payloads. LAXPC instrument will provide high time resolution X-ray observations in 3 to 80 keV energy band with moderate energy resolution. A cluster of three…
Test-time adaptation (TTA) enhances model robustness by enabling adaptation to target distributions that differ from training distributions, improving real-world generalizability. However, most existing TTA approaches focus on adjusting the…
We observed the anomalous X-ray pulsar 4U 0142+61 using the Proportional Counter Array (PCA) aboard the Rossi X-ray Timing Explorer (RXTE) in March 1996. The pulse frequency was measured as f = 0.11510039(3) Hz with an upper limit of df/dt…
We present a principal component analysis method which tracks and compensates for short-timescale variability in pulsar profiles, with a goal of improving pulsar timing precision. We couple this with a fast likelihood technique for…
We propose a robust principal component analysis (RPCA) framework to recover low-rank and sparse matrices from temporal observations. We develop an online version of the batch temporal algorithm in order to process larger datasets or…
One of the three X-ray detectors of the CAST experiment searching for solar axions is a Time Projection Chamber (TPC) with a multi-wire proportional counter (MWPC) as a readout structure. Its design has been optimized to provide high…
Principal Component Analysis (PCA) is a transform for finding the principal components (PCs) that represent features of random data. PCA also provides a reconstruction of the PCs to the original data. We consider an extension of PCA which…
Recently years, the attempts on distilling mobile data into useful knowledge has been led to the deployment of machine learning algorithms at the network edge. Principal component analysis (PCA) is a classic technique for extracting the…
The Advanced X-ray Timing Array (AXTAR) is a mission concept for X-ray timing of compact objects that combines very large collecting area, broadband spectral coverage, high time resolution, highly flexible scheduling, and an ability to…
Sparse principal component analysis (sparse PCA) aims at finding a sparse basis to improve the interpretability over the dense basis of PCA, meanwhile the sparse basis should cover the data subspace as much as possible. In contrast to most…
We report on our analysis of a 300 ks observation of the Vela pulsar with the Rossi X-Ray Timing Explorer (RXTE). The double-peaked, pulsed emission at 2 - 30 keV, which we had previously detected during a 93 ks observation, is confirmed…
In this paper, we discuss a method to find the most influential power system parameters to the probabilistic transient stability assessment problem---finding the probability distribution of the critical clearing time. We perform the…
As a widely used method in machine learning, principal component analysis (PCA) shows excellent properties for dimensionality reduction. It is a serious problem that PCA is sensitive to outliers, which has been improved by numerous Robust…
In large-scale statistical modeling, reducing data size through subsampling is essential for balancing computational efficiency and statistical accuracy. We propose a new method, Principal Component Analysis guided Quantile Sampling…
Context. The detection of Earth-like planets with the radial-velocity (RV) method is extremely challenging today due to the presence of non-Doppler signatures such as stellar activity and instrumental signals that mimic and hide the signals…
Principal component analysis (PCA) is a classical dimension reduction method which projects data onto the principal subspace spanned by the leading eigenvectors of the covariance matrix. However, it behaves poorly when the number of…
We report on X-ray observations of the young, energetic radio pulsar PSR J1105-6107 obtained using the Rossi X-ray Timing Explorer. Our timing analysis of Proportional Counter Array data finds no evidence for X-ray pulsations from this…
Principal component analysis (PCA) is a longstanding and well-studied approach for dimension reduction. It rests upon the assumption that the underlying signal in the data has low rank, and thus can be well-summarized using a small number…
In the course of the last century, Principal Component Analysis (PCA) have become one of the pillars of modern scientific methods. Although PCA is normally addressed as a statistical tool aiming at finding orthogonal directions on which the…