相关论文: Principal Component Analysis to correct data syste…

Understanding the inverse equivalent width - luminosity relationship (Baldwin Effect), the topic of this meeting, requires extracting information on continuum and emission line parameters from samples of AGN. We wish to discover whether,…

Exoplanetary atmospheric observations require an exquisite precision in the measurement of the relative flux among wavelengths. In this paper, we aim to provide a new adaptive method to treat light curves before fitting transit parameters…

We present the first results of the application of supervised classification methods to the Kepler Q1 long-cadence light curves of a subsample of 2288 stars measured in the asteroseismology program of the mission. The methods, originally…

We explore how finite integration times or equivalently temporal binning induces morphological distortions to the transit light-curve. These distortions, if uncorrected for, lead to the retrieval of erroneous system parameters and may even…

Calibration issues associated to scrambled collateral smear affecting the Kepler short-cadence data were discovered in the Data Release 24 and were found to be present in all the previous data releases since launch. In consequence, a new…

We present a new method to discriminate periodic from non-periodic irregularly sampled lightcurves. We introduce a periodic kernel and maximize a similarity measure derived from information theory to estimate the periods and a discriminator…

Astronomical observations are affected by several kinds of noise, each with its own causal source; there is photon noise, stochastic source variability, and residuals coming from imperfect calibration of the detector or telescope. The…

Exposure correction methods aim to adjust the luminance while maintaining other luminance-unrelated information. However, current exposure correction methods have difficulty in fully separating luminance-related and luminance-unrelated…

In this work we apply the principal component analysis (PCA) method with kernel trick to study classification of phases and phase transition in classical XY models in frustrated lattices. Comparing to our previous work with linear PCA…

In areas of application, including actuarial science and demography, it is increasingly common to consider a time series of curves; an example of this is age-specific mortality rates observed over a period of years. Given that age can be…

Classical Principal Component Analysis (PCA) approximates data in terms of projections on a small number of orthogonal vectors. There are simple procedures to efficiently compute various functions of the data from the PCA approximation. The…

High-precision photometry from space-based missions such as K2 and TESS enables detailed studies of young star variability. However, because space-based observing campaigns are often short (e.g., 80 days for K2), complementary long-baseline…

Cellular Automata are discrete dynamical systems that evolve following simple and local rules. Despite of its local simplicity, knowledge discovery in CA is a NP problem. This is the main motivation for using data mining techniques for CA…

The nearly continuous light curves with micromagnitude precision provided by the space mission Kepler are revolutionising our view of pulsating stars. They have revealed a vast sea of low-amplitude pulsation modes that were undetectable…

We have modified the graphical user interfaced close binary system analysis program CurveFit to the form WinKepler and applied it to 16 representative planetary candidate light curves found in the NASA Exoplanet Archive (NEA) at the Caltech…

Principal component analysis is commonly used for dimensionality reduction, feature extraction, denoising, and visualization. The most commonly used principal component analysis method is based upon optimization of the L2-norm, however, the…

Proper photometric data are challenging to obtain in the K2 mission of the Kepler space telescope due to strong systematics caused by the two-wheel-mode operation. It is especially true for variable stars wherein physical phenomena occur on…

Eclipsing binary systems with a Delta (${\delta}$) Scuti component serve a vital role in deriving precise fundamental stellar parameters and testing stellar evolution models. This study mainly focuses on the Kepler target KIC 8569819, a…

The Principal Component Analysis (PCA) is a data dimensionality reduction technique well-suited for processing data from sensor networks. It can be applied to tasks like compression, event detection, and event recognition. This technique is…

This paper describes an improved mapmaking approach with respect to the one used for the Planck High Frequency Instrument 2018 Legacy release. The algorithm SRoll2 better corrects the known instrumental effects that still affected mostly…