Results 111 to 120 of about 2,949,927 (358)
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective To delineate specific in vivo white matter pathology in neuronal intranuclear inclusion disease (NIID) using diffusion spectrum imaging (DSI) and define its clinical relevance. Methods DSI was performed on 42 NIID patients and 38 matched controls.
Kaiyan Jiang +10 more
wiley +1 more source
γ-Inverse graph of some mixed graphs
Special MatricesLet GG be a graph. Then, the inverse graph G−1{G}^{-1} of GG is defined to be a graph that has adjacency matrix similar to the inverse of the adjacency matrix of GG, where the similarity matrix is ±1\pm 1 diagonal matrix. In this article, we introduced a
Boulahmar Wafa +2 more
doaj +1 more source
The adjacency spectrum of two new operations of graphs
AKCE International Journal of Graphs and Combinatorics, 2018 Let be a graph and be its adjacency matrix. The eigenvalues of are the eigenvalues of and form the adjacency spectrum, denoted by . In this paper, we introduce two new operations and , and describe the adjacency spectra of and of regular graphs , and ...
Dijian Wang, Yaoping Hou, Zikai Tang
doaj +1 more source
Evaluating adjacency matrix for network visualization
, 2021 Adjacency Matrix (AM) is one of the commonly used techniques to visualize networks. While an AM provides a clean and compact representation for dense networks, several studies have shown that it is not suitable for path-related tasks. Several visualization techniques have been proposed to address this limitation.
openaire +2 more sources
Data‐Driven Distributed Safe Control Design for Multi‐Agent Systems
International Journal of Adaptive Control and Signal Processing, EarlyView.This paper presents a data‐driven control barrier function (CBF) technique for ensuring safe control of multi‐agent systems (MASs) with uncertain linear dynamics. A data‐driven quadratic programming (QP) optimization is first developed for CBF‐based safe control of single‐agent systems using a nonlinear controller. This approach is then extended to the
Marjan Khaledi, Bahare Kiumarsi
wiley +1 more source
Dynamic Correlation Adjacency-Matrix-Based Graph Neural Networks for Traffic Flow Prediction. [PDF]
Sensors (Basel), 2023 Gu J, Jia Z, Cai T, Song X, Mahmood A.
europepmc +1 more source
, 2006 There are several common ways to encode a tree as a matrix, such as the adjacency matrix, the Laplacian matrix (that is, the infinitesimal generator of the natural random walk), and the matrix of pairwise distances between leaves.
Evans, Steven N., Matsen, Frederick A.
core +3 more sources
Advanced Engineering Materials, EarlyView.This study explores the mechanical performance of three auxetic structures, identifying a re‐entrant‐star hybrid as the most effective for impact absorption. Finite element simulations and experiments demonstrate significant gains in energy absorption and flexural strength after geometric optimization. This study investigates the mechanical performance
Malik Hassan +4 more
wiley +1 more source
Node Importance Identification for Temporal Networks Based on Optimized Supra-Adjacency Matrix. [PDF]
Entropy (Basel), 2022 Liu R, Zhang S, Zhang D, Zhang X, Bao X.
europepmc +1 more source
A New Perspective on the Average Mixing Matrix
, 2017 We consider the continuous-time quantum walk defined on the adjacency matrix of a graph. At each instant, the walk defines a mixing matrix which is doubly-stochastic. The average of the mixing matrices contains relevant information about the quantum walk
Coutinho, Gabriel +3 more
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