Reduced-order modeling methods via bivariate discrete orthogonal polynomials for two-dimensional discrete state-delayed systems

• Published in: Multidimensional systems and signal processing Vol. 34; no. 1; pp. 227 - 248
• Main Authors: Wang, Zhao-Hong, Jiang, Yao-Lin, Xu, Kang-Li
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.03.2023; Springer Nature B.V
• Subjects: Artificial Intelligence; Bivariate analysis; Circuits and Systems; Discrete systems; Electrical Engineering; Engineering; Model reduction; Polynomials; Reduced order models; Signal,Image and Speech Processing; State space models; Thermal expansion; Transformations (mathematics); Two dimensional models; 2-D discrete state-delayed systems; Model order reduction; Bivariate discrete orthogonal polynomials; Matching coefficients

Model order reduction (MOR) techniques via bivariate discrete orthogonal polynomials are developed for two-dimensional (2-D) discrete state-delayed systems. The mathematical model of 2-D discrete systems is established on the basis of the Fornasini-Marchesini local state-space model. First, the forw...