Results 61 to 70 of about 38,430 (291)

On the equivalence between Total Least Squares and Maximum Likelihood PCA [PDF]

open access: yes, 2005
The maximum likelihood PCA (MLPCA) method has been devised in chemometrics as a generalization of the well-known PCA method in order to derive consistent estimators in the presence of errors with known error distribution.
Wentzell, P.   +7 more
core  

Signed bicyclic graphs minimizing the least Laplacian eigenvalue [PDF]

open access: yes, 2018
A signed graph is a pair (G,sigma), where G is a graph and sigma is the sign function on the edges of G. For a signed graph we consider the Laplacian matrix defined as L=D-A, where D is the matrix of vertices degrees of G and is the (signed) adjacency ...
Brunetti, Maurizio   +2 more
core   +1 more source

Least Squares Problems with Absolute Quadratic Constraints

open access: yesJournal of Applied Mathematics, 2012
This paper analyzes linear least squares problems with absolute quadratic constraints. We develop a generalized theory following Bookstein's conic-fitting and Fitzgibbon's direct ellipse-specific fitting.
R. Schöne, T. Hanning
doaj   +1 more source

Multiplicity results for p-Laplacian boundary value problem with jumping nonlinearities

open access: yesBoundary Value Problems, 2019
We investigate the multiplicity of solutions for one-dimensional p-Laplacian Dirichlet boundary value problem with jumping nonlinearities. We obtain three theorems: The first states that there exists exactly one solution when nonlinearities cross no ...
Tacksun Jung, Q-Heung Choi
doaj   +1 more source

More on Signed Graphs with at Most Three Eigenvalues

open access: yesDiscussiones Mathematicae Graph Theory, 2022
We consider signed graphs with just 2 or 3 distinct eigenvalues, in particular (i) those with at least one simple eigenvalue, and (ii) those with vertex-deleted subgraphs which themselves have at most 3 distinct eigenvalues.
Ramezani Farzaneh   +2 more
doaj   +1 more source

Phase Diagrams and Piezoelectric Properties of Wurtzite Al1−x−yScxGdyN Heterostructural Alloys

open access: yesAdvanced Science, EarlyView.
This study demonstrates ferroelectricity and piezoelectric properties improvement of quaternary wurtzite Al1−x−yScxGdyN${\rm Al}_{1-x-y}{\rm Sc}_x{\rm Gd}_y{\rm N}$ films, guided by density functional theory calculations. Wurtzite Al1−x−yScxGdyN${\rm Al}_{1-x-y}{\rm Sc}_x{\rm Gd}_y{\rm N}$ films have a high optical bandgap, enhanced piezoelectric ...
Julia L. Martin   +11 more
wiley   +1 more source

The Ordinary Least Eigenvalues Estimator

open access: yes, 2023
We propose a rate optimal estimator for the linear regression model on network data with interacted (unobservable) individual effects. The estimator achieves a faster rate of convergence $N$ compared to the standard estimators' $\sqrt{N}$ rate and is efficient in cases that we discuss.
openaire   +2 more sources

The least eigenvalues of nonhomogeneous degenerated quasilinear eigenvalue problems [PDF]

open access: yesMathematica Bohemica, 1995
Summary: We prove the existence of the least positive eigenvalue with a corresponding nonnegative eigenfunction of the quasilinear eigenvalue problem \[ -\text{div}(a(x, u) |\nabla u|^{p- 2} \nabla u)= \lambda b(x, u)|u|^{p- 2} u\quad\text{in }\Omega,\quad u= 0\quad\text{on }\partial\Omega, \] where \(\Omega\) is a bounded domain, \(p> 1\) is a real ...
openaire   +1 more source

STAID: A Self‐Refining Deep Learning Framework for Spatial Cell‐Type Deconvolution with Biologically Informed Modeling

open access: yesAdvanced Science, EarlyView.
STAID is a unified deep learning framework that couples iterative pseudo‐spot refinement with neural network training through a feedback loop and exploits gene co‐expression information to model higher‐order interactions, achieving accurate and robust cell‐type deconvolution in spatial transcriptomics.
Jixin Liu   +5 more
wiley   +1 more source

The Least Eigenvalue of the Graphs Whose Complements Are Connected and Have Pendent Paths [PDF]

open access: yes, 2018
The adjacency matrix of a graph is a matrix which represents adjacent relation between the vertices of the graph. Its minimum eigenvalue is defined as the least eigenvalue of the graph.
Cao, J.   +7 more
core   +1 more source

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