An actual problem of identification theory is considered related to the non-formalized task of evaluating the model structure. Novel approaches to structural identification (SI) propose solutions to various problems of identification theory based on the analysis of geometric frameworks (GFs). This formalized approach to the structural identifiability (SID) for nonlinear dynamical systems of various classes shows that structural identifiability follows from SI. Additionally, based on the GF, estimates for the Lyapunov exponents (LEs) of dynamical systems are shown to be recoverable, detectable, and identifiable. When combined with synthesized methods and algorithms, they can be applied to the construction of mathematical models for complex processes and systems. Thus, they can be used in decision-making systems, process forecasting, control of nonlinear systems, and processing of heterogeneous time series. Novel Approaches to Structural Identification Using Geometric Framework Analysis proposes various solutions to the problem of identification theory. It discusses the development of adaptive identification and control systems for analyzing complex processes and systems. Covering topics such as parametric restrictions, distributed lags, and interconnected systems, this book is an excellent resource for data analysis specialists, mathematical software developers, professionals, researchers, scholars, academicians, and more.
Die Inhaltsangabe kann sich auf eine andere Ausgabe dieses Titels beziehen.
Nikolay Karabutov graduated from Kharkiv Institute of Radio Electronics (Ukraine) in 1972. He got his PhD in 1982. He got his Doctor of Engineering in 1993. He obtained an academic title of the Professor in 1998. Head of the Department of Informatics and Computer Technologies of the Moscow State Academy of the Water Transport (1995-2002). He is Professor of Problem Control Department at MIREA - Russian Technological University since 2002. Professor Karabutov got the State Award in Science and Technology of the Russian Federation in 1995 for researches on adaptive systems. He was the Professor of Department of Applied Informatics under the Moscow State Industrial University (2002-20014), professor Mathematics department of the Moscow Financial University (2011-2014), professor Department of Applied Informatics of Moscow Polytechnic University.
„Über diesen Titel“ kann sich auf eine andere Ausgabe dieses Titels beziehen.
Anbieter: PBShop.store UK, Fairford, GLOS, Vereinigtes Königreich
HRD. Zustand: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000. Bestandsnummer des Verkäufers L1-9798337308227
Anzahl: Mehr als 20 verfügbar
Anbieter: PBShop.store US, Wood Dale, IL, USA
HRD. Zustand: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000. Bestandsnummer des Verkäufers L1-9798337308227
Anzahl: Mehr als 20 verfügbar
Anbieter: GreatBookPrices, Columbia, MD, USA
Zustand: New. Bestandsnummer des Verkäufers 51209963-n
Anzahl: Mehr als 20 verfügbar
Anbieter: GreatBookPricesUK, Woodford Green, Vereinigtes Königreich
Zustand: New. Bestandsnummer des Verkäufers 51209963-n
Anzahl: Mehr als 20 verfügbar
Anbieter: GreatBookPrices, Columbia, MD, USA
Zustand: As New. Unread book in perfect condition. Bestandsnummer des Verkäufers 51209963
Anzahl: Mehr als 20 verfügbar
Anbieter: GreatBookPricesUK, Woodford Green, Vereinigtes Königreich
Zustand: As New. Unread book in perfect condition. Bestandsnummer des Verkäufers 51209963
Anzahl: Mehr als 20 verfügbar
Anbieter: Rarewaves.com USA, London, LONDO, Vereinigtes Königreich
Hardback. Zustand: New. Bestandsnummer des Verkäufers LU-9798337308227
Anzahl: Mehr als 20 verfügbar
Anbieter: Grand Eagle Retail, Bensenville, IL, USA
Hardcover. Zustand: new. Hardcover. An actual problem of identification theory is considered related to the non-formalized task of evaluating the model structure. Novel approaches to structural identification (SI) propose solutions to various problems of identification theory based on the analysis of geometric frameworks (GFs). This formalized approach to the structural identifiability (SID) for nonlinear dynamical systems of various classes shows that structural identifiability follows from SI. Additionally, based on the GF, estimates for the Lyapunov exponents (LEs) of dynamical systems are shown to be recoverable, detectable, and identifiable. When combined with synthesized methods and algorithms, they can be applied to the construction of mathematical models for complex processes and systems. Thus, they can be used in decision-making systems, process forecasting, control of nonlinear systems, and processing of heterogeneous time series. Novel Approaches to Structural Identification Using Geometric Framework Analysis proposes various solutions to the problem of identification theory. It discusses the development of adaptive identification and control systems for analyzing complex processes and systems. Covering topics such as parametric restrictions, distributed lags, and interconnected systems, this book is an excellent resource for data analysis specialists, mathematical software developers, professionals, researchers, scholars, academicians, and more. "We consider an actual problem of identification theory related to the non-formalized task of evaluating the model structure. We consider an actual problem of identification theory related to the non-formalized task of evaluating the model structure"-- This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Bestandsnummer des Verkäufers 9798337308227
Anbieter: CitiRetail, Stevenage, Vereinigtes Königreich
Hardcover. Zustand: new. Hardcover. An actual problem of identification theory is considered related to the non-formalized task of evaluating the model structure. Novel approaches to structural identification (SI) propose solutions to various problems of identification theory based on the analysis of geometric frameworks (GFs). This formalized approach to the structural identifiability (SID) for nonlinear dynamical systems of various classes shows that structural identifiability follows from SI. Additionally, based on the GF, estimates for the Lyapunov exponents (LEs) of dynamical systems are shown to be recoverable, detectable, and identifiable. When combined with synthesized methods and algorithms, they can be applied to the construction of mathematical models for complex processes and systems. Thus, they can be used in decision-making systems, process forecasting, control of nonlinear systems, and processing of heterogeneous time series. Novel Approaches to Structural Identification Using Geometric Framework Analysis proposes various solutions to the problem of identification theory. It discusses the development of adaptive identification and control systems for analyzing complex processes and systems. Covering topics such as parametric restrictions, distributed lags, and interconnected systems, this book is an excellent resource for data analysis specialists, mathematical software developers, professionals, researchers, scholars, academicians, and more. "We consider an actual problem of identification theory related to the non-formalized task of evaluating the model structure. We consider an actual problem of identification theory related to the non-formalized task of evaluating the model structure"-- This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Bestandsnummer des Verkäufers 9798337308227
Anzahl: 1 verfügbar
Anbieter: preigu, Osnabrück, Deutschland
Buch. Zustand: Neu. New Approaches to Identifying Structures Using Geometric Structure Analysis | Design and Adaptation | Nikolay Nikolayevich Karabutov | Buch | Englisch | 2025 | IGI Global | EAN 9798337308227 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand. Bestandsnummer des Verkäufers 134009204
Anzahl: 5 verfügbar