Computing the matrix sine and cosine simultaneously with a reduced number of products

10/01/2020
by   Muaz Seydaoglu, et al.
0

A new procedure is presented for computing the matrix cosine and sine simultaneously by means of Taylor polynomial approximations. These are factorized so as to reduce the number of matrix products involved. Two versions are developed to be used in single and double precision arithmetic. The resulting algorithms are more efficient than schemes based on Padé approximations for a wide range of norm matrices.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
03/18/2021

An efficient algorithm to compute the exponential of skew-Hermitian matrices for the time integration of the Schrödinger equation

We present a practical algorithm to approximate the exponential of skew-...
research
05/26/2022

Single-pass Nyström approximation in mixed precision

Low rank matrix approximations appear in a number of scientific computin...
research
07/24/2019

Exploiting variable precision in GMRES

We describe how variable precision floating point arithmetic can be used...
research
05/23/2023

Open-Source GEMM Hardware Kernels Generator: Toward Numerically-Tailored Computations

Many scientific computing problems can be reduced to Matrix-Matrix Multi...
research
01/04/2021

Some fast algorithms multiplying a matrix by its adjoint

We present a non-commutative algorithm for the multiplication of a 2 x 2...
research
07/29/2022

Low-Complexity Loeffler DCT Approximations for Image and Video Coding

This paper introduced a matrix parametrization method based on the Loeff...
research
03/12/2018

An algorithm for hiding and recovering data using matrices

We present an algorithm for the recovery of a matrix M (non-singular ∈ ...

Please sign up or login with your details

Forgot password? Click here to reset