TY - JOUR
T1 - ON THE SPECTRAL FACTORIZATION OF SINGULAR, NOISY, AND LARGE MATRICES BY JANASHIA–LAGVILAVA METHOD
AU - Ephremidze, Lasha
AU - Gamkrelidze, Alexander
AU - Spitkovsky, Ilya
N1 - Funding Information:
The first and the third authors were supported by Faculty Research funding from the Division of Science and Mathematics, New York University Abu Dhabi. They were also supported in part by the EU through the H2020-MSCA-RISE-2020 project EffectFact, Grant agreement ID: 101008140.
Publisher Copyright:
© 2022 A. Razmadze Mathematical Institute of Iv. Javakhishvili Tbilisi State University. All rights reserved.
PY - 2022/12
Y1 - 2022/12
N2 - Janashia–Lagvilava algorithm is a relatively new method of matrix spectral factorization. In our previous publications on this topic, we demonstrated that the algorithm is capable to compete with other existing methods of factorization. In the present paper, we provide further refinements of the algorithm emphasizing that it might have a significant advantage in many scenarios arising in practical applications.
AB - Janashia–Lagvilava algorithm is a relatively new method of matrix spectral factorization. In our previous publications on this topic, we demonstrated that the algorithm is capable to compete with other existing methods of factorization. In the present paper, we provide further refinements of the algorithm emphasizing that it might have a significant advantage in many scenarios arising in practical applications.
KW - Janashia–Lagvilava method
KW - Matrix spectral factorization
KW - Numerical algorithms
UR - http://www.scopus.com/inward/record.url?scp=85149835940&partnerID=8YFLogxK
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M3 - Article
AN - SCOPUS:85149835940
SN - 2346-8092
VL - 176
SP - 361
EP - 366
JO - Transactions of A. Razmadze Mathematical Institute
JF - Transactions of A. Razmadze Mathematical Institute
IS - 3
ER -