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Model Order Reduction via Orthogonal Polynomial Approximation
Model Order Reduction via Orthogonal Polynomial Approximation
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261,93 €
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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 thema…

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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.

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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.

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