Model Order Reduction via Orthogonal Polynomial Approximation
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Beschreibung
This monograph presents a comprehensive exploration of model order reduction techniques rooted in orthogonal polynomials, addressing diverse dynamical systems such as linear, coupled, bilinear, time-delay, and nonlinear systems. By integrating general and specific polynomials—such as Laguerre and Chebyshev—as well as discrete orthogonal polynomials, the monograph introduces unified frameworks and innovative approaches, including structure-preserving reduction and hybrid methods. Organized thematically, the monograph combines theory with practical algorithms, emphasizing efficiency and accuracy. It features dedicated chapters on continuous-time and discrete-time systems, step-by-step derivations, and computational case studies. Readers will gain cutting-edge tools to simplify complex systems, accelerate simulations, and enhance design processes in engineering and applied mathematics.
This monograph presents a comprehensive exploration of model order reduction techniques rooted in orthogonal polynomials, addressing diverse dynamical systems such as linear, coupled, bilinear, time-delay, and nonlinear systems. By integrating general and specific polynomials—such as Laguerre and Chebyshev—as well as discrete orthogonal polynomials, the monograph introduces unified frameworks and innovative approaches, including structure-preserving reduction and hybrid methods. Organized thematically, the monograph combines theory with practical algorithms, emphasizing efficiency and accuracy. It features dedicated chapters on continuous-time and discrete-time systems, step-by-step derivations, and computational case studies. Readers will gain cutting-edge tools to simplify complex systems, accelerate simulations, and enhance design processes in engineering and applied mathematics.
The first comprehensive guide integrating general/specific/discrete orthogonal polynomials into model order reduction Structure-preserving frameworks tailored for complex dynamic systems, ensuring stability and accuracy in reduced models Handy step-by-step derivations help readers master the model order reduction via orthogonal polynomials and application
Autor*in
Yao-Lin Jiang
Themen in »Model Order Reduction via Orthogonal Polynomial Approximation«
Model order reduction Orthogonal polynomials Discrete orthogonal polynomials Dynamic systems System control