A Matrix Lsqr Algorithm for Solving Constrained Linear Operator Equations
نویسنده
چکیده
In this work, an iterative method based on a matrix form of LSQR algorithm is constructed for solving the linear operator equation A(X) = B and the minimum Frobenius norm residual problem ||A(X)−B||F where X ∈ S := {X ∈ Rn×n | X = G(X)}, F is the linear operator from Rn×n onto Rr×s, G is a linear selfconjugate involution operator and B ∈ Rr×s. Numerical examples are given to verify the efficiency of the constructed method.
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