The Least Squares Hermitian (Anti)reflexive Solution with the Least Norm to Matrix Equation AXB = C
Xin Liu, Qing-Wen Wang · Mathematical Problems in Engineering · 2017
For a given generalized reflection matrix J, that is, JH = J, J2 = I, where JH is the conjugate transpose matrix of J, a matrix A ∈ Cn×n is called a Hermitian (anti)reflexive matrix with respect to J if AH = A and A = ±JAJ. By using the Kronecker product, we derive the explicit expression of least squares Hermitian (anti)reflexive solution with the least norm to matrix equation AXB = C over complex field.