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Ajouter au panierTaschenbuch. Etat : Neu. Model Order Reduction Techniques in Control System Design | Ramesh Komarasami | Taschenbuch | Englisch | 2025 | LAP LAMBERT Academic Publishing | EAN 9786208446062 | Verantwortliche Person für die EU: SIA OmniScriptum Publishing, Brivibas Gatve 197, 1039 RIGA, LETTLAND, customerservice[at]vdm-vsg[dot]de | Anbieter: preigu.
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Ajouter au panierTaschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware 176 pp. Englisch.
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Ajouter au panierPaperback. Etat : new. Paperback. In modeling physical systems, the order of the system gives an idea of the measure of accuracy of the modeling of the system. The higher order system model will be more accurate in describing the physical system. But in several cases, the amount of information contained in a complex model may obfuscate simple, insightful behaviors, which can be better captured and explored by a model with a much lesser order. Thus, by approximating a higher order system to a suitable lower order system, a much better understanding of the system is reached. Hence, the process of Model Order Reduction involves studying the properties of a complex dynamic system in application for reducing its complexity, while preserving (to the maximum possible extent) its input - output behavior. Depending upon the practical application, certain specific properties of the higher order complex system have to be preserved in the reduced order model. The detailed comparative analysis of proposed model order reduction scenarios over the conventional reduction schemes has been presented in this book to validate the effectiveness of the proposed reduction schemes. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
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Ajouter au panierTaschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -In modeling physical systems, the order of the system gives an idea of the measure of accuracy of the modeling of the system. The higher order system model will be more accurate in describing the physical system. But in several cases, the amount of information contained in a complex model may obfuscate simple, insightful behaviors, which can be better captured and explored by a model with a much lesser order. Thus, by approximating a higher order system to a suitable lower order system, a much better understanding of the system is reached. Hence, the process of Model Order Reduction involves studying the properties of a complex dynamic system in application for reducing its complexity, while preserving (to the maximum possible extent) its input - output behavior. Depending upon the practical application, certain specific properties of the higher order complex system have to be preserved in the reduced order model. The detailed comparative analysis of proposed model order reduction scenarios over the conventional reduction schemes has been presented in this book to validate the effectiveness of the proposed reduction schemes.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 176 pp. Englisch.
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