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Springer Model Order Reduction via Orthogonal Polynomial Approximation

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Description

Model Order Reduction via Orthogonal Polynomial Approximation is a specialised academic text from Springer's Asia Pacific Mathematics Series that explores advanced mathematical techniques for simplifying complex systems through polynomial-based reduction methods. This volume (number 11 in the series) addresses the computational challenges of high-dimensional models by presenting rigorous theoretical frameworks and practical applications of orthogonal polynomial approximation. Designed for researchers, engineers, and graduate students in applied mathematics and computer science, this book provides comprehensive coverage of model reduction strategies that preserve system accuracy whilst significantly reducing computational burden. The Springer publication combines classical mathematical theory with modern computational approaches, making it an essential resource for those working with large-scale dynamical systems, control theory, or scientific computing where efficiency and precision are equally important.

Key Features

Part of Springer Asia Pacific Mathematics Series, volume 11, offering peer-reviewed academic content on advanced mathematical methods.

Focuses on orthogonal polynomial approximation techniques for systematic reduction of complex mathematical models.

Published by Springer, a leading international publisher specialising in scientific and technical literature.

Addresses model order reduction for engineering and scientific applications where computational efficiency is critical.

Product Specifications

Format
hardcover
Domain
Amazon UK
Release Date
28 October 2026
Listed Since
05 February 2026

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