Results 41 to 50 of about 179,952 (279)
Ekológia (Bratislava), 2016 In this study, we used bootstrap simulation of a real data set to investigate the impact of sample size (N = 20, 30, 40 and 50) on the eigenvalues and eigenvectors resulting from principal component analysis (PCA).
Shaukat S. Shahid +2 more
doaj +1 more source
Estimating Angle of Arrival and Output Signals to Noise Ratio for Wideband Signals [PDF]
Engineering and Technology Journal, 2016 Multiple Signal Classification (MUSIC) algorithm is the most popular algorithm to estimate angle of arrival (AOA) for narrowband signals. This algorithm is based on the use of subspace noise Eigenvectors (Q_n) matrix related to the smallest set of Eigen ...
Bassim Sayed Mohammed
doaj +1 more source
Twisting singular solutions of Bethe's equations
, 2014 The Bethe equations for the periodic XXX and XXZ spin chains admit singular solutions, for which the corresponding eigenvalues and eigenvectors are ill-defined. We use a twist regularization to derive conditions for such singular solutions to be physical,
Nepomechie, Rafael I., Wang, Chunguang
core +1 more source
Novel Modifications of Parallel Jacobi Algorithms [PDF]
, 2011 We describe two main classes of one-sided trigonometric and hyperbolic Jacobi-type algorithms for computing eigenvalues and eigenvectors of Hermitian matrices. These types of algorithms exhibit significant advantages over many other eigenvalue algorithms.
A Sluis van der +27 more
core +2 more sources
Exceptional Antimodes in Multi‐Drive Cavity Magnonics
Advanced Electronic Materials, EarlyView.Driven‐dissipative cavity‐magnonics provides a flexible platform for engineering non‐Hermitian physics such as exceptional points. Here, using a four‐port, three‐mode system with controllable microwave interference, antimodes and coherent perfect extinction (CPE) are realized, enabling active tuning to antimode exceptional points.
Mawgan A. Smith +4 more
wiley +1 more source
A Globally Convergent MCA Algorithm by Generalized Eigen-Decomposition [PDF]
International Journal of Computational Intelligence Systems, 2011 Minor component analysis (MCA) are used in many applications such as curve and surface fitting, robust beam forming, and blind signal separation. Based on the generalized eigen-decomposition, we present a completely different approach that leads to ...
Jianbin Gao, Mao Ye, Jianping Li, Qi Xia
doaj +1 more source
Advanced Energy Materials, EarlyView.Machine learning interatomic potentials bridge quantum accuracy and computational efficiency for materials discovery. Architectures from Gaussian process regression to equivariant graph neural networks, training strategies including active learning and foundation models, and applications in solid‐state electrolytes, batteries, electrocatalysts ...
In Kee Park +19 more
wiley +1 more source
New approach to finding eigenvectors for repeated eigenvalues of a matrix
Sistemnì Doslìdženâ ta Informacìjnì TehnologìïAn efficient method of calculating eigenvectors for multiple eigenvalues of a matrix is proposed. This method is based on a formalized transformation of the problem of solving degenerate systems of equations into a regular problem by “repairing” their ...
Anatolii Petrenko
doaj +1 more source
Algebraic Bethe Ansatz for spinor R-matrices
SciPost Physics, 2022 We present a supermatrix realisation of $q$-deformed spinor-spinor and spinor-vector $R$-matrices. These $R$-matrices are then used to construct transfer matrices for $U_{q^2}(\mathfrak{so}_{2n+1})$- and $U_{q}(\mathfrak{so}_{2n+2})$-symmetric closed ...
Vidas Regelskis
doaj +1 more source
Advanced Intelligent Discovery, EarlyView.This study integrates random matrix theory (RMT) and principal component analysis (PCA) to improve the identification of correlated regions in HIV protein sequences for vaccine design. PCA validation enhances the reliability of RMT‐derived correlations, particularly in small‐sample, high‐dimensional datasets, enabling more accurate detection of ...
Mariyam Siddiqah +3 more
wiley +1 more source