Results 121 to 130 of about 1,101,519 (253)

Algorithm to extract direction in 2D discrete distributions and a continuous Frobenius norm [PDF]

AIP Advances
In this study, we present a novel algorithm for determining directionality in 2D distributions of discrete data. We compare a reference dataset with a known direction to a measured dataset with an unknown direction by the Frobenius norm of the difference
Jeffrey G. Yepez, Jackson D. Seligman, Max A. A. Dornfest, Brian C. Crow, John G. Learned, Viacheslav A. Li   +5 more
doaj   +1 more source

On generating correlated random variables with a given valid or invalid Correlation matrix [PDF]

In simulation we often have to generate correlated random variables by giving a reference intercorrelation matrix, R or Q. The matrix R is positive definite and a valid correlation matrix.
Mishra, SK
core   +1 more source

scMOG: A graph neural network method for regulatory relationship‐preserving single‐cell multi‐omics integration

Quantitative Biology, Volume 14, Issue 3, September 2026.
Abstract Single‐cell multi‐omics sequencing technology provides a powerful tool for studying cellular heterogeneity. However, beyond the challenges of sparsity, heterogeneity, and dimensionality differences, a critical challenge in multi‐omics data integration lies in preserving the true regulatory relationships among molecular features.
Yucheng Lu, Xun Zhang, Hongwei Li
wiley   +1 more source

Quaternion Nuclear Norms Over Frobenius Norms Minimization for Robust Matrix Completion

CoRR
Recovering hidden structures from incomplete or noisy data remains a pervasive challenge across many fields, particularly where multi-dimensional data representation is essential. Quaternion matrices, with their ability to naturally model multi-dimensional data, offer a promising framework for this problem.
Yu Guo 0008, Guoqing Chen, Tieyong Zeng, Qiyu Jin, Michael Kwok-Po Ng   +4 more
openaire   +2 more sources

Self‐Similar Blowup for the Cubic Schrödinger Equation

Communications on Pure and Applied Mathematics, Volume 79, Issue 8, Page 1831-1918, August 2026.
ABSTRACT We give a rigorous proof for the existence of a finite‐energy, self‐similar solution to the focusing cubic Schrödinger equation in three spatial dimensions. The proof is computer‐assisted and relies on a fixed point argument that shows the existence of a solution in the vicinity of a numerically constructed approximation.
Roland Donninger, Birgit Schörkhuber
wiley   +1 more source

Graph regularised sparse NMF factorisation for imagery de‐noising

IET Computer Vision, 2018
When utilising non‐negative matrix factorisation (NMF) to decompose a data matrix into the product of two low‐rank matrices with non‐negative entries, the noisy components of data may be introduced into the matrix.
Yixian Fang, Huaxiang Zhang, Yuwei Ren
doaj   +1 more source

Synthesizing Interacting Model‐Based Optimal Control and Model‐Free Learning Approaches for Nonlinear Systems

International Journal of Robust and Nonlinear Control, Volume 36, Issue 10, Page 5619-5634, 10 July 2026.
ABSTRACT In this paper, we consider the optimal control problem for an unknown continuous‐time nonlinear system, and present a framework that integrates model‐based and model‐free methods to solve it. Each approach offers distinct advantages: model‐based techniques provide offline synthesis and data efficiency, while model‐free procedures excel at ...
Surabhi Athalye, Kyriakos G. Vamvoudakis, Panos J. Antsaklis   +2 more
wiley   +1 more source

Offline Reconstruction of Diffusion MRI Acquisitions for Comparison Between Complex PCA‐Based and AI‐Based Denoising

Magnetic Resonance in Medicine, Volume 96, Issue 1, Page 435-447, July 2026.
ABSTRACT Purpose Optimal diffusion MRI (dMRI) data for image denoising is often unavailable from scanner reconstruction. In this work, we make available an offline reconstruction pipeline for GE dMRI acquisitions, giving access to complex dMRI data. Furthermore, we compare the efficacy of GE HealthCare's AIR‐Recon DL (ARDL), a proprietary convolutional
Francesco D'Antonio, Shaun Warrington, Jose‐Pedro Manzano‐Patron, Paul S. Morgan, Stamatios N. Sotiropoulos   +4 more
wiley   +1 more source

Neutral-Type CGNNs With Multiple Delays: A Frobenius Norm Approach to Stability

IEEE Access
For neutral Cohen-Grossberg neural networks incorporating multiple time delays, we construct a tailored Lyapunov function to derive stability criteria independent of delay magnitudes.
Lin Wang, Binbin Gan, Hao Chen
doaj   +1 more source

Optimal solution of the nearest correlation matrix problem by minimization of the maximum norm [PDF]

The nearest correlation matrix problem is to find a valid (positive semidefinite) correlation matrix, R(m,m), that is nearest to a given invalid (negative semidefinite) or pseudo-correlation matrix, Q(m,m); m larger than 2.
Mishra, SK
core   +1 more source