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Liao, A.-P., Bai, Z.-Z. and Lei, Y. (2006) Best Approximate Solution of Matrix Equation AXB + CYD = E. SIAM Journal on Matrix Analysis and Applications, 27, 675-688.
https://doi.org/10.1137/040615791

has been cited by the following article:

• TITLE: Least Squares Hermitian Problem of Matrix Equation (AXB, CXD) = (E, F) Associated with Indeterminate Admittance Matrices

  AUTHORS: Yanfang Liang, Shifang Yuan, Yong Tian, Mingzhao Li

  KEYWORDS: Matrix Equation, Least Squares Solution, Least Norm Solution, Hermitian Indeterminate Admittance Matrices

  JOURNAL NAME: Journal of Applied Mathematics and Physics, Vol.6 No.6, June 14, 2018

  ABSTRACT: For A∈CmΧn, if the sum of the elements in each row and the sum of the elements in each column are both equal to 0, then A is called an indeterminate admittance matrix. If A is an indeterminate admittance matrix and a Hermitian matrix, then A is called a Hermitian indeterminate admittance matrix. In this paper, we provide two methods to study the least squares Hermitian indeterminate admittance problem of complex matrix equation (AXB,CXD)=(E,F), and give the explicit expressions of least squares Hermitian indeterminate admittance solution with the least norm in each method. We mainly adopt the Moore-Penrose generalized inverse and Kronecker product in Method I and a matrix-vector product in Method II, respectively.