Lower Bounds of the Smallest Singular Value of Matrices | Zendy

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Lower Bounds of the Smallest Singular Value of Matrices

Author(s) -

Ping Liao

Publication year - 2021

Publication title -

journal of mathematics research

Language(s) - English

Resource type - Journals

eISSN - 1916-9809

pISSN - 1916-9795

DOI - 10.5539/jmr.v13n5p1

Subject(s) - mathematics , singular value , hermitian matrix , trace (psycholinguistics) , upper and lower bounds , matrix norm , combinatorics , value (mathematics) , matrix (chemical analysis) , euclidean geometry , norm (philosophy) , complex matrix , pure mathematics , eigenvalues and eigenvectors , mathematical analysis , geometry , statistics , law , linguistics , physics , philosophy , materials science , chromatography , quantum mechanics , chemistry , political science , composite material

In this paper, we get a lower bound of the smallest singular value of an arbitrarily matrix A by the trace of H(A) and the Euclidean norm of H(A), where H(A) is Hermitian part of A, numerical examples show the e ectiveness of our results.

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