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[null,"1.","Record Nr.",null,"UNISA996445849203316"]
[null,null,"Titolo",null,"Model Order Reduction . Volume 1 System- and Data-Driven Methods and Algorithms / / ed. by Peter Benner"]
[null,null,"Pubbl/distr/stampa",null,"Berlin ; ; Boston : , : De Gruyter, , [2021]"]
[{"$nulls":4},"©2021"]
[null,null,"ISBN",null,"3-11-049896-0"]
[null,null,"Descrizione fisica",null,"1 online resource (X, 378 p.)"]
[null,null,"Collana",null,"Model Order Reduction ; ; Volume 1"]
[null,null,"Disciplina",null,"515.353"]
[null,null,"Soggetti",null,"MATHEMATICS / Numerical Analysis"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Note generali","Description based upon print version of record."]
[null,null,"Nota di contenuto",null,"Frontmatter -- Preface to the first volume of Model Order Reduction -- Contents -- 1 Model order reduction: basic concepts and notation -- 2 Balancing-related model reduction methods -- 3 Model order reduction based on moment-matching -- 4 Modal methods for reduced order modeling -- 5 Post-processing methods for passivity enforcement -- 6 The Loewner framework for system identification and reduction -- 7 Manifold interpolation -- 8 Vector fitting -- 9 Kernel methods for surrogate modeling -- 10 Kriging: methods and applications -- Index"]
[null,null,null,"Sommario/riassunto","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 two-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."]