Title
A Majorization-Minimization Algorithm For Computing The Karcher Mean Of Positive Definite Matrices
Keywords
Karcher mean; Matrix geometric mean; Positive definite matrices
Abstract
An algorithm for computing the Karcher mean of n positive definite matrices is proposed, based on the majorization-minimization (MM) principle. The proposed MM algorithm is parameter-free, does not need to choose step sizes, and has a theoretical guarantee of asymptotic linear convergence.
Publication Date
1-1-2017
Publication Title
SIAM Journal on Matrix Analysis and Applications
Volume
38
Issue
2
Number of Pages
387-400
Document Type
Article
Personal Identifier
scopus
DOI Link
https://doi.org/10.1137/15M1024482
Copyright Status
Unknown
Socpus ID
85021723079 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/85021723079
STARS Citation
Zhang, Teng, "A Majorization-Minimization Algorithm For Computing The Karcher Mean Of Positive Definite Matrices" (2017). Scopus Export 2015-2019. 5813.
https://stars.library.ucf.edu/scopus2015/5813