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  • Söderström, Torsten

    Edité par Cham, Springer., 2018

    ISBN 10 : 3319750003 ISBN 13 : 9783319750002

    Langue: anglais

    Vendeur : Universitätsbuchhandlung Herta Hold GmbH, Berlin, Allemagne

    Membre d'association : GIAQ ILAB VDA

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    EUR 10 expédition depuis Allemagne vers France

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    XXVII, 485 p. Hardcover. Communications and Control Engineering. Sprache: Englisch.

  • Torsten Söderström

    Edité par Springer International Publishing, 2018

    ISBN 10 : 3030091252 ISBN 13 : 9783030091255

    Langue: anglais

    Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne

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    EUR 181,89

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    EUR 10,99 expédition depuis Allemagne vers France

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    Taschenbuch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - This book presents an overview of the different errors-in-variables (EIV) methods that can be used for system identification. Readers will explore the properties of an EIV problem. Such problems play an important role when the purpose is the determination of the physical laws that describe the process, rather than the prediction or control of its future behaviour. EIV problems typically occur when the purpose of the modelling is to get physical insight into a process. Identifiability of the model parameters for EIV problems is a non-trivial issue, and sufficient conditions for identifiability are given. The author covers various modelling aspects which, taken together, can find a solution, including the characterization of noise properties, extension to multivariable systems, and continuous-time models. The book finds solutions that are constituted of methods that are compatible with a set of noisy data, which traditional approaches to solutions, such as (total) least squares, do not find. A number of identification methods for the EIV problem are presented. Each method is accompanied with a detailed analysis based on statistical theory, and the relationship between the different methods is explained. A multitude of methods are covered, including: instrumental variables methods; methods based on bias-compensation; covariance matching methods; and prediction error and maximum-likelihood methods. The book shows how many of the methods can be applied in either the time or the frequency domain and provides special methods adapted to the case of periodic excitation. It concludes with a chapter specifically devoted to practical aspects and user perspectives that will facilitate the transfer of the theoretical material to application in real systems. Errors-in-Variables Methods in System Identification gives readers the possibility of recovering true system dynamics from noisy measurements, while solving over-determined systems of equations, making it suitable for statisticians and mathematicians alike. The book also acts as a reference for researchers and computer engineers because of its detailed exploration of EIV problems.

  • Torsten Söderström

    Edité par Springer-Verlag Gmbh, 2018

    ISBN 10 : 3319750003 ISBN 13 : 9783319750002

    Langue: anglais

    Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne

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    EUR 181,89

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    Buch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - This book presents an overview of the different errors-in-variables (EIV) methods that can be used for system identification. Readers will explore the properties of an EIV problem. Such problems play an important role when the purpose is the determination of the physical laws that describe the process, rather than the prediction or control of its future behaviour. EIV problems typically occur when the purpose of the modelling is to get physical insight into a process. Identifiability of the model parameters for EIV problems is a non-trivial issue, and sufficient conditions for identifiability are given. The author covers various modelling aspects which, taken together, can find a solution, including the characterization of noise properties, extension to multivariable systems, and continuous-time models. The book finds solutions that are constituted of methods that are compatible with a set of noisy data, which traditional approaches to solutions, such as (total) least squares, do not find. A number of identification methods for the EIV problem are presented. Each method is accompanied with a detailed analysis based on statistical theory, and the relationship between the different methods is explained. A multitude of methods are covered, including: instrumental variables methods; methods based on bias-compensation; covariance matching methods; and prediction error and maximum-likelihood methods. The book shows how many of the methods can be applied in either the time or the frequency domain and provides special methods adapted to the case of periodic excitation. It concludes with a chapter specifically devoted to practical aspects and user perspectives that will facilitate the transfer of the theoretical material to application in real systems. Errors-in-Variables Methods in System Identification gives readers the possibility of recovering true system dynamics from noisy measurements, while solving over-determined systems of equations, making it suitable for statisticians and mathematicians alike. The book also acts as a reference for researchers and computer engineers because of its detailed exploration of EIV problems.

  • Torsten Söderström

    Edité par Springer International Publishing, Springer International Publishing Dez 2018, 2018

    ISBN 10 : 3030091252 ISBN 13 : 9783030091255

    Langue: anglais

    Vendeur : buchversandmimpf2000, Emtmannsberg, BAYE, Allemagne

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    EUR 181,89

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    EUR 15 expédition depuis Allemagne vers France

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    Taschenbuch. Etat : Neu. Neuware -This book presents an overview of the different errors-in-variables (EIV) methods that can be used for system identification. Readers will explore the properties of an EIV problem. Such problems play an important role when the purpose is the determination of the physical laws that describe the process, rather than the prediction or control of its future behaviour. EIV problems typically occur when the purpose of the modelling is to get physical insight into a process. Identifiability of the model parameters for EIV problems is a non-trivial issue, and sufficient conditions for identifiability are given. The author covers various modelling aspects which, taken together, can find a solution, including the characterization of noise properties, extension to multivariable systems, and continuous-time models. The book finds solutions that are constituted of methods that are compatible with a set of noisy data, which traditional approaches to solutions, such as (total) least squares, do not find.A number of identification methods for the EIV problem are presented. Each method is accompanied with a detailed analysis based on statistical theory, and the relationship between the different methods is explained. A multitude of methods are covered, including:instrumental variables methods;methods based on bias-compensation;covariance matching methods; andprediction error and maximum-likelihood methods.The book shows how many of the methods can be applied in either the time or the frequency domain and provides special methods adapted to the case of periodic excitation. It concludes with a chapter specifically devoted to practical aspects and user perspectives that will facilitate the transfer of the theoretical material to application in real systems.Errors-in-Variables Methods in System Identification gives readers the possibility of recovering true system dynamics from noisy measurements, while solving over-determined systems of equations, making it suitable for statisticians and mathematicians alike. The book also acts as a reference for researchers and computer engineers because of its detailed exploration of EIV problems.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 516 pp. Englisch.

  • Torsten Söderström

    Edité par Springer-Verlag Gmbh Apr 2018, 2018

    ISBN 10 : 3319750003 ISBN 13 : 9783319750002

    Langue: anglais

    Vendeur : buchversandmimpf2000, Emtmannsberg, BAYE, Allemagne

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    EUR 181,89

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    EUR 15 expédition depuis Allemagne vers France

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    Buch. Etat : Neu. Neuware -This book presents an overview of the different errors-in-variables (EIV) methods that can be used for system identification. Readers will explore the properties of an EIV problem. Such problems play an important role when the purpose is the determination of the physical laws that describe the process, rather than the prediction or control of its future behaviour. EIV problems typically occur when the purpose of the modelling is to get physical insight into a process. Identifiability of the model parameters for EIV problems is a non-trivial issue, and sufficient conditions for identifiability are given. The author covers various modelling aspects which, taken together, can find a solution, including the characterization of noise properties, extension to multivariable systems, and continuous-time models. The book finds solutions that are constituted of methods that are compatible with a set of noisy data, which traditional approaches to solutions, such as (total) least squares, do not find.A number of identification methods for the EIV problem are presented. Each method is accompanied with a detailed analysis based on statistical theory, and the relationship between the different methods is explained. A multitude of methods are covered, including:instrumental variables methods;methods based on bias-compensation;covariance matching methods; andprediction error and maximum-likelihood methods.The book shows how many of the methods can be applied in either the time or the frequency domain and provides special methods adapted to the case of periodic excitation. It concludes with a chapter specifically devoted to practical aspects and user perspectives that will facilitate the transfer of the theoretical material to application in real systems.Errors-in-Variables Methods in System Identification gives readers the possibility of recovering true system dynamics from noisy measurements, while solving over-determined systems of equations, making it suitable for statisticians and mathematicians alike. The book also acts as a reference for researchers and computer engineers because of its detailed exploration of EIV problems.Springer-Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 485 pp. Englisch.

  • Söderström, Torsten

    Edité par Springer, 2018

    ISBN 10 : 3030091252 ISBN 13 : 9783030091255

    Langue: anglais

    Vendeur : dsmbooks, Liverpool, Royaume-Uni

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    EUR 249,08

    Autre devise
    EUR 29,39 expédition depuis Royaume-Uni vers France

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    Paperback. Etat : New. New. book.

  • Söderström, Torsten

    Edité par Springer, 2018

    ISBN 10 : 3319750003 ISBN 13 : 9783319750002

    Langue: anglais

    Vendeur : Mispah books, Redhill, SURRE, Royaume-Uni

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    EUR 257,92

    Autre devise
    EUR 29,39 expédition depuis Royaume-Uni vers France

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    Hardcover. Etat : New. New. book.

  • Söderström, Torsten

    Edité par Springer, 2018

    ISBN 10 : 3319750003 ISBN 13 : 9783319750002

    Langue: anglais

    Vendeur : Revaluation Books, Exeter, Royaume-Uni

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    EUR 280,96

    Autre devise
    EUR 11,76 expédition depuis Royaume-Uni vers France

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    Hardcover. Etat : Brand New. 485 pages. 9.25x6.10x1.22 inches. In Stock.

  • Torsten Söderström

    Edité par Springer International Publishing, 2018

    ISBN 10 : 3319750003 ISBN 13 : 9783319750002

    Langue: anglais

    Vendeur : moluna, Greven, Allemagne

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    impression à la demande

    EUR 153,73

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    EUR 9,70 expédition depuis Allemagne vers France

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    Gebunden. Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Shows the reader how to deal with measurement noises present in both input to and output from a systemAssists readers in establishing the physical laws that describe their processes&nbspCompares the .

  • Torsten Söderström

    Edité par Springer International Publishing, 2018

    ISBN 10 : 3030091252 ISBN 13 : 9783030091255

    Langue: anglais

    Vendeur : moluna, Greven, Allemagne

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    impression à la demande

    EUR 153,73

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    Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Shows the reader how to deal with measurement noises present in both input to and output from a systemAssists readers in establishing the physical laws that describe their processes&nbspCompares the .

  • Torsten Söderström

    Edité par Springer International Publishing Dez 2018, 2018

    ISBN 10 : 3030091252 ISBN 13 : 9783030091255

    Langue: anglais

    Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne

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    impression à la demande

    EUR 181,89

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    EUR 11 expédition depuis Allemagne vers France

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    Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book presents an overview of the different errors-in-variables (EIV) methods that can be used for system identification. Readers will explore the properties of an EIV problem. Such problems play an important role when the purpose is the determination of the physical laws that describe the process, rather than the prediction or control of its future behaviour. EIV problems typically occur when the purpose of the modelling is to get physical insight into a process. Identifiability of the model parameters for EIV problems is a non-trivial issue, and sufficient conditions for identifiability are given. The author covers various modelling aspects which, taken together, can find a solution, including the characterization of noise properties, extension to multivariable systems, and continuous-time models. The book finds solutions that are constituted of methods that are compatible with a set of noisy data, which traditional approaches to solutions, such as (total) least squares, do not find. A number of identification methods for the EIV problem are presented. Each method is accompanied with a detailed analysis based on statistical theory, and the relationship between the different methods is explained. A multitude of methods are covered, including: instrumental variables methods; methods based on bias-compensation; covariance matching methods; and prediction error and maximum-likelihood methods. The book shows how many of the methods can be applied in either the time or the frequency domain and provides special methods adapted to the case of periodic excitation. It concludes with a chapter specifically devoted to practical aspects and user perspectives that will facilitate the transfer of the theoretical material to application in real systems. Errors-in-Variables Methods in System Identification gives readers the possibility of recovering true system dynamics from noisy measurements, while solving over-determined systems of equations, making it suitable for statisticians and mathematicians alike. The book also acts as a reference for researchers and computer engineers because of its detailed exploration of EIV problems. 516 pp. Englisch.

  • Torsten Söderström

    Edité par Springer-Verlag Gmbh Apr 2018, 2018

    ISBN 10 : 3319750003 ISBN 13 : 9783319750002

    Langue: anglais

    Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne

    Évaluation du vendeur 5 sur 5 étoiles Evaluation 5 étoiles, En savoir plus sur les évaluations des vendeurs

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    impression à la demande

    EUR 181,89

    Autre devise
    EUR 11 expédition depuis Allemagne vers France

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    Buch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book presents an overview of the different errors-in-variables (EIV) methods that can be used for system identification. Readers will explore the properties of an EIV problem. Such problems play an important role when the purpose is the determination of the physical laws that describe the process, rather than the prediction or control of its future behaviour. EIV problems typically occur when the purpose of the modelling is to get physical insight into a process. Identifiability of the model parameters for EIV problems is a non-trivial issue, and sufficient conditions for identifiability are given. The author covers various modelling aspects which, taken together, can find a solution, including the characterization of noise properties, extension to multivariable systems, and continuous-time models. The book finds solutions that are constituted of methods that are compatible with a set of noisy data, which traditional approaches to solutions, such as (total) least squares, do not find. A number of identification methods for the EIV problem are presented. Each method is accompanied with a detailed analysis based on statistical theory, and the relationship between the different methods is explained. A multitude of methods are covered, including: instrumental variables methods; methods based on bias-compensation; covariance matching methods; and prediction error and maximum-likelihood methods. The book shows how many of the methods can be applied in either the time or the frequency domain and provides special methods adapted to the case of periodic excitation. It concludes with a chapter specifically devoted to practical aspects and user perspectives that will facilitate the transfer of the theoretical material to application in real systems. Errors-in-Variables Methods in System Identification gives readers the possibility of recovering true system dynamics from noisy measurements, while solving over-determined systems of equations, making it suitable for statisticians and mathematicians alike. The book also acts as a reference for researchers and computer engineers because of its detailed exploration of EIV problems. 485 pp. Englisch.