Model Order Reduction via Orthogonal Polynomial Approximation (Springer Asia Pacific Mathematics Series)

Jiang, Yao-Lin

Springer Verlag, Singapore（2026/07発売）

• 製本 Hardcover:ハードカバー版／ページ数 298 p.
• 言語 ENG
• 商品コード 9789819583744

Full Description

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.

Contents

Preface.- Introduction.- Chapter 1 Preliminaries.- Chapter 2 Model Order Reduction based on General Orthogonal Polynomials.- Chapter 3 Model Order Reduction based on Specific Orthogonal Polynomials.- Chapter 4 Model Order Reduction based on Discrete Orthogonal Polynomials.- Chapter 5 Approximation of Orthogonal Polynomials Combining with Other Model Order Reduction Methods.- References.- Index.