Reprint

Numerical Linear Algebra and the Applications

Edited by
November 2021
126 pages
  • ISBN978-3-0365-2165-7 (Hardback)
  • ISBN978-3-0365-2166-4 (PDF)

This book is a reprint of the Special Issue Numerical Linear Algebra and the Applications that was published in

Computer Science & Mathematics
Engineering
Physical Sciences
Public Health & Healthcare
Summary

Numerical linear algebra is a very important topic in mathematics and has important recent applications in deep learning, machine learning, image processing, applied statistics, artificial intelligence and other interesting modern applications in many fields. The purpose of this Special Issue in Mathematics is to present the latest contributions and recent developments in numerical linear algebra and applications in different real domains. We invite authors to submit original and new papers and high-quality reviews related to the following topics: applied linear algebra, linear and nonlinear systems of equations, large matrix equations, numerical tensor problems with applications, ill-posed problems and image processing, linear algebra and applied statistics, model reduction in dynamic systems, and other related subjects. The submitted papers will be reviewed in line with the traditional submission process. This Special Issue will be dedicated to the inspired mathematician Constantin Petridi, who has devoted his life to mathematics.

Format
  • Hardback
License
© 2022 by the authors; CC BY-NC-ND license
Keywords
inverse scattering; reciprocity gap functional; chiral media; mixed boundary conditions; non-linear matrix equations; perturbation bounds; Lyapunov majorants; fixed-point principle; nonsymmetric differential matrix Riccati equation; cosine product; Golub–Kahan algorithm; Krylov subspaces; PCA; SVD; tensors; quadratic form; estimates; upper bounds; networks; perron vector; power method; lanczos method; pseudospectra; eigenvalues; matrix polynomial; perturbation; Perron root; large-scale matrices; approximation algorithm; high-dimensional; minimum norm solution; regularisation; Tikhonov; ℓp-ℓq; variable selection