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Nonlinear System Identification ― Input-Output Modeling Approach: Volume 1: Nonlinear System Parameter Identification: 7 (Mathematical Modelling: Theory and Applications, 7) - Softcover
Synopsis
The subject of the book is to present the modeling, parameter estimation and other aspects of the identification of nonlinear dynamic systems. The treatment is restricted to the input-output modeling approach. Because of the widespread usage of digital computers discrete time methods are preferred. Time domain parameter estimation methods are dealt with in detail, frequency domain and power spectrum procedures are described shortly. The theory is presented from the engineering point of view, and a large number of examples of case studies on the modeling and identifications of real processes illustrate the methods. Almost all processes are nonlinear if they are considered not merely in a small vicinity of the working point. To exploit industrial equipment as much as possible, mathematical models are needed which describe the global nonlinear behavior of the process. If the process is unknown, or if the describing equations are too complex, the structure and the parameters can be determined experimentally, which is the task of identification. The book is divided into seven chapters dealing with the following topics: 1. Nonlinear dynamic process models 2. Test signals for identification 3. Parameter estimation methods 4. Nonlinearity test methods 5. Structure identification 6. Model validity tests 7. Case studies on identification of real processes Chapter I summarizes the different model descriptions of nonlinear dynamical systems.
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Product Description
This two-volume handbook presents a comprehensive overview of nonlinear dynamic system identification. The books include many aspects of nonlinear processes: modelling, parameter estimation, structure search, nonlinearity and model validity tests. The book includes not only nonparametric models but also parametric models which include a limited number of parameters. Time domain parameter estimation is dealt with in detail; frequency domain and power spectrum procedures are also included. Audience: This work is intended for postgraduate students, researchers and engineers whose work involves nonlinear systems. Many examples, case studies and experimental identifications of real processes have been included.
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Nonlinear System Identification ? Input-Output Modeling Approach: Volume 1: Nonlinear System Parameter Identification (Mathematical Modelling: Theory and Applications)
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Nonlinear System Identification -- Input-output Modeling Approach : Nonlinear System Parameter Identification
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Nonlinear System Identification ? Input-Output Modeling Approach: Volume 1: Nonlinear System Parameter Identification (Mathematical Modelling: Theory and Applications)
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Nonlinear System Identification Input-Output Modeling Approach (Paperback)
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Paperback. Condition: new. Paperback. The subject of the book is to present the modeling, parameter estimation and other aspects of the identification of nonlinear dynamic systems. The treatment is restricted to the input-output modeling approach. Because of the widespread usage of digital computers discrete time methods are preferred. Time domain parameter estimation methods are dealt with in detail, frequency domain and power spectrum procedures are described shortly. The theory is presented from the engineering point of view, and a large number of examples of case studies on the modeling and identifications of real processes illustrate the methods. Almost all processes are nonlinear if they are considered not merely in a small vicinity of the working point. To exploit industrial equipment as much as possible, mathematical models are needed which describe the global nonlinear behavior of the process. If the process is unknown, or if the describing equations are too complex, the structure and the parameters can be determined experimentally, which is the task of identification. The book is divided into seven chapters dealing with the following topics: 1. Nonlinear dynamic process models 2. Test signals for identification 3. Parameter estimation methods 4. Nonlinearity test methods 5. Structure identification 6. Model validity tests 7. Case studies on identification of real processes Chapter I summarizes the different model descriptions of nonlinear dynamical systems. The subject of the book is to present the modeling, parameter estimation and other aspects of the identification of nonlinear dynamic systems. Case studies on identification of real processes Chapter I summarizes the different model descriptions of nonlinear dynamical systems. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9789401059206
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Nonlinear System Identification ? Input-Output Modeling Approach: Volume 1: Nonlinear System Parameter Identification (Mathematical Modelling: Theory and Applications)
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Nonlinear System Identification -- Input-output Modeling Approach : Nonlinear System Parameter Identification
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Nonlinear System Identification ¿ Input-Output Modeling Approach
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The subject of the book is to present the modeling, parameter estimation and other aspects of the identification of nonlinear dynamic systems. The treatment is restricted to the input-output modeling approach. Because of the widespread usage of digital computers discrete time methods are preferred. Time domain parameter estimation methods are dealt with in detail, frequency domain and power spectrum procedures are described shortly. The theory is presented from the engineering point of view, and a large number of examples of case studies on the modeling and identifications of real processes illustrate the methods. Almost all processes are nonlinear if they are considered not merely in a small vicinity of the working point. To exploit industrial equipment as much as possible, mathematical models are needed which describe the global nonlinear behavior of the process. If the process is unknown, or if the describing equations are too complex, the structure and the parameters can be determined experimentally, which is the task of identification. The book is divided into seven chapters dealing with the following topics: 1. Nonlinear dynamic process models 2. Test signals for identification 3. Parameter estimation methods 4. Nonlinearity test methods 5. Structure identification 6. Model validity tests 7. Case studies on identification of real processes Chapter I summarizes the different model descriptions of nonlinear dynamical systems. 428 pp. Englisch. Seller Inventory # 9789401059206
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Nonlinear System Identification - Input-Output Modeling Approach
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. The subject of the book is to present the modeling, parameter estimation and other aspects of the identification of nonlinear dynamic systems. The treatment is restricted to the input-output modeling approach. Because of the widespread usage of digital comp. Seller Inventory # 5832556
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Nonlinear System Identification Input-Output Modeling Approach: Volume 1: Nonlinear System Parameter Identification
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Nonlinear System Identification - Input-Output Modeling Approach
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ISBN 10: 9401059209
ISBN 13: 9789401059206
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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -The subject of the book is to present the modeling, parameter estimation and other aspects of the identification of nonlinear dynamic systems. The treatment is restricted to the input-output modeling approach. Because of the widespread usage of digital computers discrete time methods are preferred. Time domain parameter estimation methods are dealt with in detail, frequency domain and power spectrum procedures are described shortly. The theory is presented from the engineering point of view, and a large number of examples of case studies on the modeling and identifications of real processes illustrate the methods. Almost all processes are nonlinear if they are considered not merely in a small vicinity of the working point. To exploit industrial equipment as much as possible, mathematical models are needed which describe the global nonlinear behavior of the process. If the process is unknown, or if the describing equations are too complex, the structure and the parameters can be determined experimentally, which is the task of identification. The book is divided into seven chapters dealing with the following topics: 1. Nonlinear dynamic process models 2. Test signals for identification 3. Parameter estimation methods 4. Nonlinearity test methods 5. Structure identification 6. Model validity tests 7. Case studies on identification of real processes Chapter I summarizes the different model descriptions of nonlinear dynamical systems.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 428 pp. Englisch. Seller Inventory # 9789401059206
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