Abstract: This study introduces a novel matrix determinant feature extraction approach for efficient classification of motor and mental imagery activities from electroencephalography (EEG) signals.
Abstract: As a variant of non-negative matrix factorization (NMF), symmetric NMF (SymNMF) can generate the clustering result without additional post-processing, by decomposing a similarity matrix into ...
Health inequalities in the UK continue from one generation to the next, with those in the most deprived areas experiencing significantly shorter and poorer life years than those in affluent ...
The main goal of this manuscript is to introduce a discrete dynamical system defined by symmetric matrices and a real parameter. By construction, we rediscovery the Power Iteration Method from the ...
Recently, in order to find the principal moments of inertia of a large number of rigid bodies, it was necessary to compute the eigenvalues of many real, symmetric 3 × 3 matrices. The available ...
In this paper, we obtain a formula for the derivative of a determinant with respect to an eigenvalue in the modified Cholesky decomposition of a symmetric matrix, a characteristic example of a direct ...
Department of Economics, FEARP - Faculty of Economics, Business Administration and Accounting at Ribeirão Preto, University of São Paulo, Ribeirão Preto, Brazil Introduction: Realized volatility ...
Hi, can ELPA only get half of the symmetric matrix and compute the eigenvalue and eigenvector? Just like ScaLAPACK pdsyevd? There is a symmetric matrix that will be transformed before computing its ...
We present a linear-time algorithm that computes in a given real interval the number of eigenvalues of any symmetric matrix whose underlying graph is unicyclic. The algorithm can be applied to ...
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