Numerical Data Fitting in Dynamical Systems: A Practical Introduction with Applications and Software (Applied Optimization, 77) - Hardcover
Real life phenomena in engineering, natural, or medical sciences are often described by a mathematical model with the goal to analyze numerically the behaviour of the system. Advantages of mathematical models are their cheap availability, the possibility of studying extreme situations that cannot be handled by experiments, or of simulating real systems during the design phase before constructing a first prototype. Moreover, they serve to verify decisions, to avoid expensive and time consuming experimental tests, to analyze, understand, and explain the behaviour of systems, or to optimize design and production. As soon as a mathematical model contains differential dependencies from an additional parameter, typically the time, we call it a dynamical model. There are two key questions always arising in a practical environment: 1 Is the mathematical model correct? 2 How can I quantify model parameters that cannot be measured directly? In principle, both questions are easily answered as soon as some experimental data are available. The idea is to compare measured data with predicted model function values and to minimize the differences over the whole parameter space. We have to reject a model if we are unable to find a reasonably accurate fit. To summarize, parameter estimation or data fitting, respectively, is extremely important in all practical situations, where a mathematical model and corresponding experimental data are available to describe the behaviour of a dynamical system.
"synopsis" may belong to another edition of this title.
- PublisherSpringer
- Publication date2002
- ISBN 10 1402010796
- ISBN 13 9781402010798
- BindingHardcover
- Number of pages408
Buy New
Learn more about this copy
US$ 300.43
Shipping:
US$ 53.35
From Germany to U.S.A.
Top Search Results from the AbeBooks Marketplace
Seller Image
Numerical Data Fitting in Dynamical Systems
Published by
Springer US
(2002)
ISBN 10: 1402010796
ISBN 13: 9781402010798
New
Hardcover
Quantity: > 20
Seller:
Rating
Book Description Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Real life phenomena in engineering, natural, or medical sciences are often described by a mathematical model with the goal to analyze numerically the behaviour of the system. Advantages of mathematical models are their cheap availability, the possibility of. Seller Inventory # 4092323
Buy New
US$ 300.43
Convert currency
Stock Image
NUMERICAL DATA FITTING IN DYNAMI
Seller:
Rating
Book Description Condition: New. New. In shrink wrap. Looks like an interesting title! 1.75. Seller Inventory # Q-1402010796
Buy New
US$ 376.26
Convert currency
Seller Image
Numerical Data Fitting in Dynamical Systems
Published by
Springer US Dez 2002
(2002)
ISBN 10: 1402010796
ISBN 13: 9781402010798
New
Hardcover
Quantity: 2
Seller:
Rating
Book Description Buch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Real life phenomena in engineering, natural, or medical sciences are often described by a mathematical model with the goal to analyze numerically the behaviour of the system. Advantages of mathematical models are their cheap availability, the possibility of studying extreme situations that cannot be handled by experiments, or of simulating real systems during the design phase before constructing a first prototype. Moreover, they serve to verify decisions, to avoid expensive and time consuming experimental tests, to analyze, understand, and explain the behaviour of systems, or to optimize design and production. As soon as a mathematical model contains differential dependencies from an additional parameter, typically the time, we call it a dynamical model. There are two key questions always arising in a practical environment: 1 Is the mathematical model correct 2 How can I quantify model parameters that cannot be measured directly In principle, both questions are easily answered as soon as some experimental data are available. The idea is to compare measured data with predicted model function values and to minimize the differences over the whole parameter space. We have to reject a model if we are unable to find a reasonably accurate fit. To summarize, parameter estimation or data fitting, respectively, is extremely important in all practical situations, where a mathematical model and corresponding experimental data are available to describe the behaviour of a dynamical system. 412 pp. Englisch. Seller Inventory # 9781402010798
Buy New
US$ 360.01
Convert currency
Seller Image
Numerical Data Fitting in Dynamical Systems : A Practical Introduction with Applications and Software
Published by
Springer US
(2002)
ISBN 10: 1402010796
ISBN 13: 9781402010798
New
Hardcover
Quantity: 1
Seller:
Rating
Book Description Buch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - Real life phenomena in engineering, natural, or medical sciences are often described by a mathematical model with the goal to analyze numerically the behaviour of the system. Advantages of mathematical models are their cheap availability, the possibility of studying extreme situations that cannot be handled by experiments, or of simulating real systems during the design phase before constructing a first prototype. Moreover, they serve to verify decisions, to avoid expensive and time consuming experimental tests, to analyze, understand, and explain the behaviour of systems, or to optimize design and production. As soon as a mathematical model contains differential dependencies from an additional parameter, typically the time, we call it a dynamical model. There are two key questions always arising in a practical environment: 1 Is the mathematical model correct 2 How can I quantify model parameters that cannot be measured directly In principle, both questions are easily answered as soon as some experimental data are available. The idea is to compare measured data with predicted model function values and to minimize the differences over the whole parameter space. We have to reject a model if we are unable to find a reasonably accurate fit. To summarize, parameter estimation or data fitting, respectively, is extremely important in all practical situations, where a mathematical model and corresponding experimental data are available to describe the behaviour of a dynamical system. Seller Inventory # 9781402010798
Buy New
US$ 364.34
Convert currency