Software

Giuseppe Rodriguez


Index:

blgaussexp:
Computation of the subgraph centrality of the nodes of a directed network.
Authors: C. Fenu, D. Martin, L. Reichel, and G. Rodriguez.
This set of functions allows the computation of the subgraph communicabilities between the nodes of a network, either undirected or directed, as well as the starting/ending convenience. The computation of is performed by block Gauss/Anti-Gauss quadrature. The functions were developed for Matlab, but they are compatible with Octave. They are described in the paper Last updated: October 27, 2014.

hubauth:
Computation of the hub/authority centrality of the nodes of a network.
Authors: J. Baglama, C. Fenu, L. Reichel, and G. Rodriguez.
This set of functions allows the computation of the hub/authority centrality of the nodes of a network by three different algorithms: Gauss quadrature, low-rank approximation, and a hybrid method. The functions were developed for Matlab, but they are compatible with Octave. They are described in the paper The package contains a modified version of the routine irlba described in the paper We also use the routine irblsvds_leja, from We include a copy of both routines in the package, for user's convenience.
Last updated: July 4, 2014.

sgcen:
Computation of the subgraph centrality of the nodes of an undirected network.
Authors: C. Fenu, D. Martin, L. Reichel, and G. Rodriguez.
This set of functions allows the computation of the subgraph centrality of the nodes of a network. The functions were developed for Matlab, but they are compatible with Octave. They are described in the paper The package contains a copy of the routine irbleigs from Last updated: Jun 16, 2014.

smt
Structured matrices toolbox.
Authors: M. Redivo-Zaglia and G. Rodriguez.
smt is a Matlab toolbox for structured matrix computation.
For documentation, see Last updated: January 20, 2011.

drsolve
Solver for linear systems with displacement structure.
Authors: A. Aricò and G. Rodriguez.
This package provides a set of Matlab functions to solve linear systems whose matrix belongs to the following classes: Cauchy-like, Toeplitz-like, Toeplitz+Hankel-like and Vandermonde-like. The solvers have a computational cost O(rn2), and use O(rn) memory locations, where n is the size and r is the displacement rank of the matrix.
See Last updated: May 9, 2011.

ErresTools
Choosing a regularization parameter by error estimation.
Authors: G. Rodriguez.
This small Matlab toolbox contains some functions for determining a suitable value of the regularization parameter in TSVD and Tikhonov regularization by employing the error estimates described in the papers Some of the functions require the toolbox Regularization Tools by P.C. Hansen.
Last updated: March 10, 2010.

toms729gw
Fast solver for Toeplitz linear systems.
Authors: A. Aricò and G. Rodriguez (for the Matlab MEX gateway).
Authors: P.C. Hansen and T. Chan (for the computational routines).
This is a Matlab (Fortran) MEX gateway for TOMS Algorithm 729 by P.C Hansen and T. Chan, which implements a look-ahead Levinson method for the solution of Toeplitz linear systems. The algorithm is described in the paper Last updated: February 27, 2010.

lbdtik
Tikhonov regularization by Lanczos bidiagonalization.
Authors: L. Reichel and G. Rodriguez.
This Matlab function computes the Tikhonov regularized solution a linear system, choosing the regularization parameter by minimizing an estimate of the error. A test driver, (which requires the Regularization Tools) is included. The algorithm is described in the paper Last updated: October 6, 2009.

tpls
Fast least squares solver for Toeplitz linear systems.
Author: G. Rodriguez.
This Matlab functions compute the least squares solution of an overdetermined, full-rank, Toeplitz linear system, by a fast algorithm. The method is based on the computation of the Schur complement of an augmented matrix, and is described in the paper Last updated: August 4, 2007.

corner.m
Find the corner of a discrete L-curve.
Authors: P.C. Hansen, T.K. Jensen, and G. Rodriguez.
This Matlab function implements an adaptive algorithm for computing the corner of a discrete L-curve. The L-curve is a technique used in regularization methods for estimating the regularization parameter. The algorithm is described in the paper This function is included in Version 4 of the Regularization Tools by P.C. Hansen.
Last updated: January 11, 2007.

Giuseppe Rodriguez
rodriguez@unica.it