Video and Webinar Series

Reduced Order Modeling

Reduced order modeling (ROM) is a technique to simplify a high-fidelity mathematical model by reducing its computational complexity while preserving the dominant behavior of the complex model. This series highlights different applications of ROM and methods for creating reduced order models with MATLAB and Simulink.

Applications and Methods Reduced order modeling (ROM) is a technique to simplify a high-fidelity mathematical model by reducing its computational complexity while preserving the dominant behavior of the complex model. Explore how to create ROMS using reduced order modeling.

ROM using Machine Learning Learn how to create reduced-order models of high-fidelity systems using machine learning techniques in System Identification Toolbox.