Frequency-limited reduced models for linear and bilinear systems on the Riemannian manifold
YL Jiang, KL Xu - IEEE Transactions on Automatic Control, 2020 - ieeexplore.ieee.org
In this article, we propose two new iterative algorithms to solve the frequency-limited
Riemannian optimization model order reduction problems of linear and bilinear systems …
Riemannian optimization model order reduction problems of linear and bilinear systems …
Multiprecision algorithms for computing the matrix logarithm
Two algorithms are developed for computing the matrix logarithm in floating point arithmetic
of any specified precision. The backward error-based approach used in the state of the art …
of any specified precision. The backward error-based approach used in the state of the art …
Algorithms for the computation of the matrix logarithm based on the double exponential formula
We consider the computation of the matrix logarithm by using numerical quadrature. The
efficiency of numerical quadrature depends on the integrand and the choice of quadrature …
efficiency of numerical quadrature depends on the integrand and the choice of quadrature …
An Improved Taylor Algorithm for Computing the Matrix Logarithm
The most popular method for computing the matrix logarithm is a combination of the inverse
scaling and squaring method in conjunction with a Padé approximation, sometimes …
scaling and squaring method in conjunction with a Padé approximation, sometimes …
Computing f-Divergences and Distances of High-Dimensional Probability Density Functions--Low-Rank Tensor Approximations
Very often, in the course of uncertainty quantification tasks or data analysis, one has to deal
with high-dimensional random variables (RVs). A high-dimensional RV can be described by …
with high-dimensional random variables (RVs). A high-dimensional RV can be described by …
Computing the Matrix Logarithm with the Romberg Integration Method
The matrix logarithm function has applicability in many engineering and science fields.
Improvements in its calculation, from the point of view of both accuracy and/or execution …
Improvements in its calculation, from the point of view of both accuracy and/or execution …
Computing ‐divergences and distances of high‐dimensional probability density functions
Very often, in the course of uncertainty quantification tasks or data analysis, one has to deal
with high‐dimensional random variables. Here the interest is mainly to compute …
with high‐dimensional random variables. Here the interest is mainly to compute …
The dual inverse scaling and squaring algorithm for the matrix logarithm
M Fasi, B Iannazzo - IMA Journal of Numerical Analysis, 2022 - academic.oup.com
The inverse scaling and squaring algorithm computes the logarithm of a square matrix by
evaluating a rational approximant to the logarithm at the matrix for a suitable choice of. We …
evaluating a rational approximant to the logarithm at the matrix for a suitable choice of. We …
Polynomial approximations for the matrix logarithm with computation graphs
E Jarlebring, J Sastre, J González - arXiv preprint arXiv:2401.10089, 2024 - arxiv.org
The most popular method for computing the matrix logarithm is a combination of the inverse
scaling and squaring method in conjunction with a Pad\'e approximation, sometimes …
scaling and squaring method in conjunction with a Pad\'e approximation, sometimes …
Logarithm of a Non-Singular Complex Matrix via the Dunford–Taylor Integral
D Caratelli, PE Ricci - Axioms, 2022 - mdpi.com
Using the Dunford–Taylor integral and a representation formula for the resolvent of a non-
singular complex matrix, we find the logarithm of a non-singular complex matrix applying the …
singular complex matrix, we find the logarithm of a non-singular complex matrix applying the …