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- W4376274503 abstract "This paper investigates the new model order reduction (MOR) methods via bivariate discrete orthogonal polynomials for two-dimensional (2-D) discrete systems. The 2-D discrete system is described by the Kurek model. First, we deduce algebraically the shift-transformation matrix of the classical discrete orthogonal polynomials of one variable. By means of the shift-transformation matrices, 2-D discrete systems are expanded in the spaces spanned by bivariate discrete orthogonal polynomials. The coefficient matrices are calculated from matrix equations. Then the reduced-order systems are produced by the orthogonal projection matrices defined by the coefficient matrices. Theoretical analysis shows that the reduced-order systems can match a certain number of coefficient vectors of the original outputs. Finally, one numerical example is simulated to demonstrate the feasibility and effectiveness of the proposed methods." @default.
- W4376274503 created "2023-05-13" @default.
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- W4376274503 date "2023-10-01" @default.
- W4376274503 modified "2023-09-27" @default.
- W4376274503 title "Reduced-order state-space models for two-dimensional discrete systems via bivariate discrete orthogonal polynomials" @default.
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- W4376274503 doi "https://doi.org/10.1016/j.matcom.2023.05.009" @default.
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