An efficient method for solving a least square problem over mixed constraints

Jinzhi Luo

doi:10.1117/12.2692512

23 August 2023 An efficient method for solving a least square problem over mixed constraints

Jinzhi Luo

Proceedings Volume 12784, Second International Conference on Applied Statistics, Computational Mathematics, and Software Engineering (ASCMSE 2023); 1278419 (2023) https://doi.org/10.1117/12.2692512
Event: 2023 2nd International Conference on Applied Statistics, Computational Mathematics and Software Engineering (ASCMSE 2023), 2023, Kaifeng, China

Abstract

In this paper, we consider solving the generalized Sylvester equation AXB + CYD = E under mixed constraints {X^T = X, L₁ ≤ X ≤ U₁, Y^T = Y, L₂ ≤ Y ≤ U₂}, where A,C ∈ R^m×n, B,D ∈ R^n×m, E ∈ R^m×m and L₁,U₁,L₂,U₂ ∈ R^n×n are suitable given matrices, and the ||•|| is the Frobenius norm. An effective iterative algorithm is presented to solving the proposed problem and the relevant convergence properties of the algorithm are proved. Numerical examples are performed to demonstrate the algorithm is efficient.

Citation Download Citation

Jinzhi Luo "An efficient method for solving a least square problem over mixed constraints", Proc. SPIE 12784, Second International Conference on Applied Statistics, Computational Mathematics, and Software Engineering (ASCMSE 2023), 1278419 (23 August 2023); https://doi.org/10.1117/12.2692512

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