JOURNAL ARTICLE

Riccati equation and metric geometric means of positive semidefinite matrices involving semi-tensor products

Pattrawut ChansangiamArnon Ploymukda

Year: 2023 Journal:   AIMS Mathematics Vol: 8 (10)Pages: 23519-23533   Publisher: American Institute of Mathematical Sciences

Abstract

<abstract><p>We investigate the Riccati matrix equation $ X A^{-1} X = B $ in which the conventional matrix products are generalized to the semi-tensor products $ \ltimes $. When $ A $ and $ B $ are positive definite matrices satisfying the factor-dimension condition, this equation has a unique positive definite solution, which is defined to be the metric geometric mean of $ A $ and $ B $. We show that this geometric mean is the maximum solution of the Riccati inequality. We then extend the notion of the metric geometric mean to positive semidefinite matrices by a continuity argument and investigate its algebraic properties, order properties and analytic properties. Moreover, we establish some equations and inequalities of metric geometric means for matrices involving cancellability, positive linear map and concavity. Our results generalize the conventional metric geometric means of matrices.</p></abstract>

Keywords:
Mathematics Positive-definite matrix Metric (unit) Geometric mean Matrix (chemical analysis) Riccati equation Algebraic Riccati equation Pure mathematics Dimension (graph theory) Tensor (intrinsic definition) Mathematical analysis Geometry Eigenvalues and eigenvectors Partial differential equation

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2
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1.30
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30
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0.74
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Citation History

Topics

Mathematical Inequalities and Applications
Physical Sciences →  Mathematics →  Applied Mathematics
Fixed Point Theorems Analysis
Physical Sciences →  Mathematics →  Geometry and Topology
Mathematics and Applications
Physical Sciences →  Mathematics →  Geometry and Topology
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