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![Model Order Reduction: System- and Data-Driven Methods and Algorithms, Volume 1](/uploads/posts/2021-12/1639582041_9441_mod_l_ord_r_r_duction__volum__1.jpg)
Автор: Peter Benner, Stefano Grivet-Talocia, Alfio Quarteroni
Издательство: De Gruyter
Год: 2021
Страниц: 388
Язык: английский
Формат: pdf (true), epub
Размер: 38.1 MB
An increasing complexity of models used to predict real-world systems leads to the need for algorithms to replace complex models with far simpler ones, while preserving the accuracy of the predictions. This three-volume handbook covers methods as well as applications. This first volume focuses on real-time control theory, data assimilation, real-time visualization, high-dimensional state spaces and interaction of different reduction techniques. This first volume starts with an introductory chapter to Model Order Reduction (MOR) in general as a very broad field of research, encompassing multiple techniques with applications in a wide variety of fields.