Parametric Inner Bounds for the Extreme Eigenvalues of Real Symmetric Matrices

Here, inner bounds for the extreme eigenvalues of a real symmetric matrix are derived by using a two-dimensional subspace of Rn. The addition of a single parameter to the basis vectors and optimization thereof results in superior bounds, as compared to using fixed basis vectors. This is a rather simple procedure that is easily automated.

Authors

Institutions

Publication Details

Journal
Symmetry
Published
2025-11-27
DOI
https://doi.org/10.3390/sym17122031
Primary Topic
Matrix Theory and Algorithms
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Parametric Inner Bounds for the Extreme Eigenvalues of Real Symmetric Matrices

Virath Singh, Shivani Singh, P. Singh
Symmetry
Matrix Theory and Algorithms
article

Parametric Inner Bounds for the Extreme Eigenvalues of Real Symmetric Matrices

Virath Singh, Shivani Singh, P. Singh
article en

Abstract

Here, inner bounds for the extreme eigenvalues of a real symmetric matrix are derived by using a two-dimensional subspace of Rn. The addition of a single parameter to the basis vectors and optimization thereof results in superior bounds, as compared to using fixed basis vectors. This is a rather simple procedure that is easily automated.

SymmetryVol. 17(12)
University of South Africa (ZA), University of KwaZulu-Natal (ZA)
Openalex Percentile: Top 63%
Matrix Theory and Algorithms
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.