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引用次数: 1
摘要
研究了Riccati矩阵方程$ X A^{-1} X = B $,其中常规矩阵积推广为半张量积$ \ltimes $。当$ A $和$ B $为满足因子维条件的正定矩阵时,该方程有一个唯一的正定解,定义为$ A $和$ B $的度量几何平均值。我们证明了这个几何平均值是里卡蒂不等式的最大解。然后通过连续性论证将度量几何均值的概念推广到正半定矩阵,并研究了它的代数性质、阶性质和解析性质。此外,我们还建立了包含可消性、正线性映射和凹性的矩阵的度量几何均值的方程和不等式。我们的结果推广了矩阵的常规度量几何平均值。
Riccati equation and metric geometric means of positive semidefinite matrices involving semi-tensor products
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.
期刊介绍:
AIMS Mathematics is an international Open Access journal devoted to publishing peer-reviewed, high quality, original papers in all fields of mathematics. We publish the following article types: original research articles, reviews, editorials, letters, and conference reports.