Results 121 to 130 of about 1,705,971 (292)

Applications of combinatorial matrix theory to Laplacian matrices of graphs

open access: yes, 2012
On the surface, matrix theory and graph theory seem like very different branches of mathematics. However, adjacency, Laplacian, and incidence matrices are commonly used to represent graphs, and many properties of matrices can give us useful information ...
Molitierno, Jason J.   +1 more
core  

Matrix Tree Theorem for the Net Laplacian Matrix of a Signed Graph

open access: yes, 2022
For a simple signed graph G with the adjacency matrix A and net degree matrix D±, the net Laplacian matrix is L± = D±−A. We introduce a new oriented incidence matrix N± which can keep track of the sign as well as the orientation of each edge of G. Also L±
Mallik, Sudipta
core  

Supervised Protein Structure Classification Using Topological Persistence With DeltaFold

open access: yesProteins: Structure, Function, and Bioinformatics, EarlyView.
ABSTRACT Recent advances in protein structure prediction have considerably increased the number of available structures, underscoring the need for scalable and accurate methods to compare and classify this huge amount of data. Current approaches based on sequence alignment or structural superposition often lack sensitivity and/or are computationally ...
Joseph Nardin‐Gennequin   +3 more
wiley   +1 more source

Propagation of internal gravity waves: Optimal vertical discretisation and grid design based on numerical error analysis

open access: yesQuarterly Journal of the Royal Meteorological Society, EarlyView.
An energy‐conserving discrete framework for the vertical discretisation of stratified ocean models is developed using internal gravity‐wave theory. A β$$ \beta $$‐indexed family of schemes is analysed through perturbation theory, revealing optimal parameter choices and grid designs that reduce truncation errors significantly.
Gabriel Derrida   +3 more
wiley   +1 more source

On spectrum and energies of enhanced power graphs

open access: yesMathematics Open
The enhanced power graph [Formula: see text] of a group G is a simple graph with vertex set G and two distinct vertex are adjacent if and only if they belong to the same cyclic subgroup.
Pankaj Kalita, Prohelika Das
doaj   +1 more source

Laplacian Invariant Operator in the Matrix Ball

open access: yes, 2012
В статье найден инвариантный оператор Лапласа в матричном шаре и решена задача Дирихле.In article it is considered Laplacian invariant operator in a matrix ball and it is solved the problem of ...
Khudayberganov, Gulmirza Kh.   +3 more
core  

Privacy‐Preserving Data‐Driven Distributed MPC for Heterogeneous Nonlinear Multi‐Agent Systems

open access: yesInternational Journal of Robust and Nonlinear Control, EarlyView.
ABSTRACT Distributed model predictive control (DMPC) is a cornerstone for coordinating multi‐agent systems, yet simultaneously ensuring data privacy, handling unknown nonlinear dynamics, and managing heterogeneous constraints remains an open challenge.
Mahmood Mazare, Hossein Ramezani
wiley   +1 more source

Cramer-Rao Bounds for Laplacian Matrix Estimation

open access: yesCoRR
In this paper, we analyze the performance of the estimation of Laplacian matrices under general observation models. Laplacian matrix estimation involves structural constraints, including symmetry and null-space properties, along with matrix sparsity.
Morad Halihal   +2 more
openaire   +2 more sources

Frequency Shaping for Improving a Trade‐Off Between Control and Privacy Performance: Beyond Differential Privacy

open access: yesInternational Journal of Robust and Nonlinear Control, EarlyView.
ABSTRACT In privacy protection of control systems, a trade‐off between control performance and privacy level is often pointed out. Our goal in this paper is to improve this trade‐off by shaping the frequency of noise added for privacy protection when the control objective is to track a reference signal, which is taken as a piece of information whose ...
Rintaro Watanabe   +3 more
wiley   +1 more source

The spectrum of the Laplacian matrix of a balanced binary tree

open access: yesLinear Algebra and its Applications, 2002
Let \(L({\mathcal B}_k)\) be the Laplacian matrix of an unweighted balanced binary tree \({\mathcal B}_k\) of \(k\) levels. The author completely characterizes the eigenvalues of \(L({\mathcal B}_k)\) by labelling vertices of \({\mathcal B}_k\) in such a way that \(L({\mathcal B}_k)\) becomes a symmetric persymmetric matrix.
openaire   +4 more sources

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