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It is already known that both auditory and visual stimulus is able to convey emotions in human mind to different extent. The strength or intensity of the emotional arousal vary depending on the type of stimulus chosen. In this study, we try…

How does one find dimensions in multivariate data that are reliably expressed across repetitions? For example, in a brain imaging study one may want to identify combinations of neural signals that are reliably expressed across multiple…

Machine Learning · Statistics 2022-12-05 Lucas C. Parra , Stefan Haufe , Jacek P. Dmochowski

In this paper we discuss various possibilities of using X-ray observations to gain information about the large-scale structure of the Universe. After reviewing briefly the current status of these investigations we explore different ways of…

Astrophysics · Physics 2007-05-23 X. Barcons , F. J. Carrera , M. T. Ceballos , S. Mateos

We present a new and efficient optimization method to determine the structure of disordered systems in agreement with available experimental data. Our approach permits the application of accurate electronic structure calculations within the…

Materials Science · Physics 2014-06-23 Jan H. Los , Thomas D. Kühne

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 study the dynamics of a single Frenkel exciton in a disordered molecular chain. The coherent-potential approximation (CPA) is applied to the situation when the single-molecule excitation energies as well as the transition dipole moments,…

Disordered Systems and Neural Networks · Physics 2011-05-11 D. B. Balagurov , G. C. La Rocca , V. M. Agranovich

Multiexponential modeling of relaxation or diffusion MR signal decays is a popular approach for estimating and spatially mapping different microstructural tissue compartments. While this approach can be quite powerful, it is also limited by…

Image and Video Processing · Electrical Eng. & Systems 2019-05-10 Daeun Kim , Jessica L. Wisnowski , Christopher T. Nguyen , Justin P. Haldar

We applied the analysis of x-ray intensity angular correlation function to dilute ensembles of identical spinel crystals. Firstly, we show that the angular correlation from measured diffraction patterns with many crystals per shot converges…

Materials Science · Physics 2017-01-27 Yun Zhao

To obtain spatial information about an arbitrary object in x-ray structure analysis, the standard method is to measure the intensity in the far field, i.e., the first-order photon correlation function of the coherently scattered x-ray…

Quantum Physics · Physics 2023-12-20 M. Bojer , J. Eckert , S. Karl , S. Richter , J. von Zanthier

This paper proposes a robust high-dimensional sparse canonical correlation analysis (CCA) method for investigating linear relationships between two high-dimensional random vectors, focusing on elliptical symmetric distributions. Traditional…

Methodology · Statistics 2025-04-18 Chengde Qian , Yanhong Liu , Long Feng

For the theoretical prediction of cross-section fluctuations in chaotic scattering, the cross-section autocorrelation function is needed. That function is not known analytically. Using experimental data and numerical simulations, we show…

Chaotic Dynamics · Physics 2015-05-14 B. Dietz , H. L. Harney , A. Richter , F. Schaefer , H. A. Weidenmueller

We introduce a new method for detection of long-range cross-correlations and multifractality - multifractal height cross-correlation analysis (MF-HXA) - based on scaling of qth order covariances. MF-HXA is a bivariate generalization of the…

Statistical Finance · Quantitative Finance 2012-05-24 Ladislav Kristoufek

Spin correlation functions (up to the 3-site one) of disordered Ising model with the nearest neighbour interaction are calculated and investigated within a two-site cluster approximation for both quenched and annealed cases. The approach…

Condensed Matter · Physics 2007-05-23 R. R. Levitskii , S. I. Sorokov

The Fourier inversion of phased coherent diffraction patterns offers images without the resolution and depth-of-focus limitations of lens-based tomographic systems. We report on our recent experimental images inverted using recent…

Canonical correlation analysis (CCA) is a multivariate statistical technique for finding the linear relationship between two sets of variables. The kernel generalization of CCA named kernel CCA has been proposed to find nonlinear relations…

Machine Learning · Statistics 2017-01-17 Xiaowei Zhang , Delin Chu , Li-Zhi Liao , Michael K. Ng

It is shown that the errors of present-day exchange-correlation (xc) functionals are rather short ranged. For extended systems the correction can therefore be evaluated by analyzing properly chosen clusters and employing highest-quality…

Materials Science · Physics 2009-11-13 Qing-Miao Hu , Karsten Reuter , Matthias Scheffler

An application of resonant inelastic x-ray scattering technique for studying of optical scale excitations in electron-correlated materials is discussed. Examples are given including data obtained for 3d transition metal, lanthanide, and…

Strongly Correlated Electrons · Physics 2007-05-23 Sergei M. Butorin

We perform combined X-ray tomography and shear force measurements on a cyclically sheared granular system with highly transient behaviors, and obtain the evolution of microscopic structures and the macroscopic shear force during the shear…

Soft Condensed Matter · Physics 2021-02-03 Yi Xing , Jie Zheng , Jindong Li , Yixin Cao , Wei Pan , Jie Zhang , Yujie Wang

We present a theoretical study of frequency correlations of light backscattered from a random scattering medium. This statistical quantity provides insight into the dynamics of multiple scattering processes accessible both, in theoretical…

Optics · Physics 2015-06-23 Angelika Knothe , Thomas Wellens

Generalized Canonical Correlation Analysis (GCCA) is an important tool that finds numerous applications in data mining, machine learning, and artificial intelligence. It aims at finding `common' random variables that are strongly correlated…

Machine Learning · Computer Science 2021-05-19 Mikael Sørensen , Charilaos I. Kanatsoulis , Nicholas D. Sidiropoulos