22 citations · 78 across the 20 of their papers we have counts for
23 papers
Sensitivity of Perron and Fiedler eigenpairs to structural perturbations of a network
Silvia Noschese, Lothar Reichel
One can estimate the change of the Perron and Fiedler values for a connected network when the weight of an edge is perturbed by analyzing relevant entries of the Perron and Fiedler…
Network connectivity analysis via shortest paths
Silvia Noschese, Lothar Reichel
Complex systems of interacting components often can be modeled by a simple graph that consists of a set of nodes and a set of edges. Such a graph can be repre…
Communication in Multiplex Transportation Networks
Silvia Noschese, Lothar Reichel
Complex networks are made up of vertices and edges. The edges, which may be directed or undirected, are equipped with positive weights. Modeling complex systems that consist of dif…
Enhancing multiplex global efficiency
Silvia Noschese, Lothar Reichel
Modeling complex systems that consist of different types of objects leads to multilayer networks, in which vertices are connected by both inter-layer and intra-layer edges. In this…
Network analysis with the aid of the path length matrix
Silvia Noschese, Lothar Reichel
Let a network be represented by a simple graph with vertices. A common approach to investigate properties of a network is to use the adjacency matrix $A=[a_{ij}]_…
A tensor formalism for multilayer network centrality measures using the Einstein product
Smahane El-Halouy, Silvia Noschese, Lothar Reichel
Complex systems that consist of different kinds of entities that interact in different ways can be modeled by multilayer networks. This paper uses the tensor formalism with the Ein…
The structured distance to singularity of a symmetric tridiagonal Toeplitz matrix
Silvia Noschese
This paper is concerned with the distance of a symmetric tridiagonal Toeplitz matrix to the variety of similarly structured singular matrices, and with determining the closest…
Perron communicability and sensitivity of multilayer networks
Smahane El-Halouy, Silvia Noschese, Lothar Reichel
Modeling complex systems that consist of different types of objects leads to multilayer networks, where nodes in the different layers represent different kind of objects. Nodes are…
On the banded Toeplitz structured distance to symmetric positive semidefiniteness
Silvia Noschese, Lothar Reichel
This paper is concerned with the determination of a close real banded positive definite Toeplitz matrix in the Frobenius norm to a given square real banded matrix. While it is stra…
Communication in Complex Networks
Omar De la Cruz Cabrera, Jiafeng Jin, Silvia Noschese +1
One of the properties of interest in the analysis of networks is \emph{global communicability}, i.e., how easy or difficult it is, generally, to reach nodes from other nodes by fol…
Estimating and increasing the structural robustness of a network
Silvia Noschese, Lothar Reichel
The capability of a network to cope with threats and survive attacks is referred to as its robustness. This paper discusses one kind of robustness, commonly denoted structural robu…
Functions and eigenvectors of partially known matrices with applications to network analysis
Mohammed Al Mugahwi, Omar De la Cruz Cabrera, Silvia Noschese +1
Matrix functions play an important role in applied mathematics. In network analysis, in particular, the exponential of the adjacency matrix associated with a network provides valua…
A spectral method for bipartizing a network and detecting a large anti-community
A. Concas, S. Noschese, L. Reichel +1
Relations between discrete quantities such as people, genes, or streets can be described by networks, which consist of nodes that are connected by edges. Network analysis aims to i…
Eigenvector sensitivity under general and structured perturbations of tridiagonal Toeplitz-type matrices
Silvia Noschese, Lothar Reichel
The sensitivity of eigenvalues of structured matrices under general or structured perturbations of the matrix entries has been thoroughly studied in the literature. Error bounds ar…
Arnoldi decomposition, GMRES, and preconditioning for linear discrete ill-posed problems
Silvia Gazzola, Silvia Noschese, Paolo Novati +1
GMRES is one of the most popular iterative methods for the solution of large linear systems of equations that arise from the discretization of linear well-posed problems, such as D…
Regularization matrices for discrete ill-posed problems in several space-dimensions
Laura Dykes, Guangxin Huang, Silvia Noschese +1
Many applications in science and engineering require the solution of large linear discrete ill-posed problems that are obtained by the discretization of a Fredholm integral equatio…
Computing Unstructured and Structured Polynomial Pseudospectrum Approximations
Silvia Noschese, Lothar Reichel
In many applications it is important to understand the sensitivity of eigenvalues of a matrix polynomial to perturbations of the polynomial. The sensitivity commonly is described b…
Approximated structured pseudospectra
Silvia Noschese, Lothar Reichel
Pseudospectra and structured pseudospectra are important tools for the analysis of matrices. Their computation, however, can be very demanding for all but small matrices. A new app…
Circulant preconditioners for discrete ill-posed Toeplitz systems
L. Dykes, S. Noschese, L. Reichel
Circulant preconditioners are commonly used to accelerate the rate of convergence of iterative methods when solving linear systems of equations with a Toeplitz matrix. Block extens…
Regularization matrices determined by matrix nearness problems
Guangxin Huang, Silvia Noschese, Lothar Reichel
This paper is concerned with the solution of large-scale linear discrete ill-posed problems with error-contaminated data. Tikhonov regularization is a popular approach to determine…
Some matrix nearness problems suggested by Tikhonov regularization
Silvia Noschese, Lothar Reichel
The numerical solution of linear discrete ill-posed problems typically requires regularization, i.e., replacement of the available ill-conditioned problem by a nearby better condit…
Differential equations for real-structured (and unstructured) defectivity measures
Paolo Buttà, Nicola Guglielmi, Manuela Manetta +1
Let be either a complex or real matrix with all distinct eigenvalues. We propose a new method for the computation of both the unstructured and the real-structured (if the matri…
Structured conditioning of Hamiltonian eigenvalue problems
Paolo Buttà, Silvia Noschese
We discuss the effect of structure-preserving perturbations on complex or real Hamiltonian eigenproblems and characterize the structured worst-case effect perturbations. We derive…