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  • Sprache: Englisch

    Verlag: Springer, 2011

    0857295217 / 9780857295217

    Serie: Buch 6 von 28 - Advanced Textbooks in Control and Signal Processing

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    Zustand: Good. Your purchase helps support Sri Lankan Children's Charity 'The Rainbow Centre'. Ex-library, so some stamps and wear, but in good overall condition. Our donations to The Rainbow Centre have helped provide an education and a safe haven to hundreds of children who live in appalling conditions.…

  • Sprache: Englisch

    Verlag: Springer 2011-05, 2011

    0857295217 / 9780857295217

    Serie: Buch 6 von 28 - Advanced Textbooks in Control and Signal Processing

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  • Sprache: Englisch

    Verlag: Springer, 2011

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  • Sprache: Englisch

    Verlag: Springer, 2011

    0857295217 / 9780857295217

    Serie: Buch 6 von 28 - Advanced Textbooks in Control and Signal Processing

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  • Sprache: Englisch

    Verlag: Springer, 2011

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    Serie: Buch 6 von 28 - Advanced Textbooks in Control and Signal Processing

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  • Sprache: Englisch

    Verlag: Springer London Ltd, GB, 2011

    0857295217 / 9780857295217

    Serie: Buch 6 von 28 - Advanced Textbooks in Control and Signal Processing

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    Paperback. Zustand: New. 2011th. System Identification shows the student reader how to approach the system identification problem in a systematic fashion. The process is divided into three basic steps: experimental design and data collection; model structure selection and parameter estimation; and model validation, each of which is the subject of one or more parts of the text. Following an introduction on system theory, particularly in relation to model representation and model properties, the book contains four parts covering. data-based identification - non-parametric methods for use when prior system knowledge is very limited; time-invariant identification for systems with constant parameters; time-varying systems identification, primarily with recursive estimation techniques; and. model validation methods.A fifth part, composed of appendices, covers the various aspects of the underlying mathematics needed to begin using the text.The book uses essentially semi-physical or gray-box modeling methods although data-based, transfer-function system descriptions are also introduced. The approach is problem-based rather than rigorously mathematical. The use of finite input-output data is demonstrated for frequency- and time-domain identification in static, dynamic, linear, nonlinear, time-invariant and time-varying systems. Simple examples are used to show readers how to perform and emulate the identification steps involved in various control design methods with more complex illustrations derived from real physical, chemical and biological applications being used to demonstrate the practical applicability of the methods described. End-of-chapter exercises (for which a downloadable instructors' Solutions Manual is available from fill in URL here) will both help students to assimilate what they have learned and make the book suitable forself-tuition by practitioners looking to brush up on modern techniques.Graduate and final-year undergraduate students will find this text to be a practical and realistic course in system identification that can be used for assessing the processes of a variety of engineering disciplines. System Identification will help academic instructors teaching control-related to give their students a good understanding of identification methods that can be used in the real world without the encumbrance of undue mathematical detail.…

  • Sprache: Englisch

    Verlag: Springer, 2011

    0857295217 / 9780857295217

    Serie: Buch 6 von 28 - Advanced Textbooks in Control and Signal Processing

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    Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - System Identification shows the student reader how to approach the system identification problem in a systematic fashion. The process is divided into three basic steps: experimental design and data collection; model structure selection and parameter estimation; and model validation, each of which is the subject of one or more parts of the text. Following an introduction on system theory, particularly in relation to model representation and model properties, the book contains four parts covering:- data-based identification - non-parametric methods for use when prior system knowledge is very limited;- time-invariant identification for systems with constant parameters;- time-varying systems identification, primarily with recursive estimation techniques; and- model validation methods.A fifth part, composed of appendices, covers the various aspects of the underlying mathematics needed to begin using the text.The book uses essentially semi-physical or gray-box modeling methods although data-based, transfer-function system descriptions are also introduced. The approach is problem-based rather than rigorously mathematical. The use of finite input-output data is demonstrated for frequency- and time-domain identification in static, dynamic, linear, nonlinear, time-invariant and time-varying systems. Simple examples are used to show readers how to perform and emulate the identification steps involved in various control design methods with more complex illustrations derived from real physical, chemical and biological applications being used to demonstrate the practical applicability of the methods described. End-of-chapter exercises (for which a downloadable instructors' Solutions Manual is available from fill in URL here) will both help students to assimilate what they have learned and make the book suitable forself-tuition by practitioners looking to brush up on modern techniques.Graduate and final-year undergraduate students will find this text to be a practical and realistic course in system identification that can be used for assessing the processes of a variety of engineering disciplines. System Identification will help academic instructors teaching control-related to give their students a good understanding of identification methods that can be used in the real world without the encumbrance of undue mathematical detail.…

  • Sprache: Englisch

    Verlag: Springer, 2011

    0857295217 / 9780857295217

    Serie: Buch 6 von 28 - Advanced Textbooks in Control and Signal Processing

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    Zustand: New. pp. 352.

  • Sprache: Englisch

    Verlag: Springer, Berlin, 2011

    0857295217 / 9780857295217

    Serie: Buch 6 von 28 - Advanced Textbooks in Control and Signal Processing

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    Paperback. Zustand: Brand New. 349 pages. 9.25x6.25x0.75 inches. In Stock.

  • Sprache: Englisch

    Verlag: Springer, 2011

    0857295217 / 9780857295217

    Serie: Buch 6 von 28 - Advanced Textbooks in Control and Signal Processing

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    Sprache: Englisch

    Verlag: Springer, 2011

    0857295217 / 9780857295217

    Serie: Buch 6 von 28 - Advanced Textbooks in Control and Signal Processing

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    Taschenbuch. Zustand: Neu. System Identification | An Introduction | Karel J. Keesman | Taschenbuch | Advanced Textbooks in Control and Signal Processing | xxvi | Englisch | 2011 | Springer | EAN 9780857295217 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.…

  • Sprache: Englisch

    Verlag: Springer, 2011

    0857295217 / 9780857295217

    Serie: Buch 6 von 28 - Advanced Textbooks in Control and Signal Processing

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  • Sprache: Englisch

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  • Sprache: Englisch

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    Serie: Buch 6 von 28 - Advanced Textbooks in Control and Signal Processing

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    Paperback. Zustand: New. 2011th. System Identification shows the student reader how to approach the system identification problem in a systematic fashion. The process is divided into three basic steps: experimental design and data collection; model structure selection and parameter estimation; and model validation, each of which is the subject of one or more parts of the text. Following an introduction on system theory, particularly in relation to model representation and model properties, the book contains four parts covering. data-based identification - non-parametric methods for use when prior system knowledge is very limited; time-invariant identification for systems with constant parameters; time-varying systems identification, primarily with recursive estimation techniques; and. model validation methods.A fifth part, composed of appendices, covers the various aspects of the underlying mathematics needed to begin using the text.The book uses essentially semi-physical or gray-box modeling methods although data-based, transfer-function system descriptions are also introduced. The approach is problem-based rather than rigorously mathematical. The use of finite input-output data is demonstrated for frequency- and time-domain identification in static, dynamic, linear, nonlinear, time-invariant and time-varying systems. Simple examples are used to show readers how to perform and emulate the identification steps involved in various control design methods with more complex illustrations derived from real physical, chemical and biological applications being used to demonstrate the practical applicability of the methods described. End-of-chapter exercises (for which a downloadable instructors' Solutions Manual is available from fill in URL here) will both help students to assimilate what they have learned and make the book suitable forself-tuition by practitioners looking to brush up on modern techniques.Graduate and final-year undergraduate students will find this text to be a practical and realistic course in system identification that can be used for assessing the processes of a variety of engineering disciplines. System Identification will help academic instructors teaching control-related to give their students a good understanding of identification methods that can be used in the real world without the encumbrance of undue mathematical detail.…

  • Sprache: Englisch

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    Serie: Buch 6 von 28 - Advanced Textbooks in Control and Signal Processing

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  • Sprache: Englisch

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    Serie: Buch 6 von 28 - Advanced Textbooks in Control and Signal Processing

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    Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -System Identification shows the student reader how to approach the system identification problem in a systematic fashion. The process is divided into three basic steps: experimental design and data collection; model structure selection and parameter estimation; and model validation, each of which is the subject of one or more parts of the text. Following an introduction on system theory, particularly in relation to model representation and model properties, the book contains four parts covering:- data-based identification - non-parametric methods for use when prior system knowledge is very limited;- time-invariant identification for systems with constant parameters;- time-varying systems identification, primarily with recursive estimation techniques; and- model validation methods.A fifth part, composed of appendices, covers the various aspects of the underlying mathematics needed to begin using the text.The book uses essentially semi-physical or gray-box modeling methods although data-based, transfer-function system descriptions are also introduced. The approach is problem-based rather than rigorously mathematical. The use of finite input-output data is demonstrated for frequency- and time-domain identification in static, dynamic, linear, nonlinear, time-invariant and time-varying systems. Simple examples are used to show readers how to perform and emulate the identification steps involved in various control design methods with more complex illustrations derived from real physical, chemical and biological applications being used to demonstrate the practical applicability of the methods described. End-of-chapter exercises (for which a downloadable instructors' Solutions Manual is available from fill in URL here) will both help students to assimilate what they have learned and make the book suitable forself-tuition by practitioners looking to brush up on modern techniques.Graduate and final-year undergraduate students will find this text to be a practical and realistic course in system identification that can be used for assessing the processes of a variety of engineering disciplines. System Identification will help academic instructors teaching control-related to give their students a good understanding of identification methods that can be used in the real world without the encumbrance of undue mathematical detail. 352 pp. Englisch.…

  • Sprache: Englisch

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    0857295217 / 9780857295217

    Serie: Buch 6 von 28 - Advanced Textbooks in Control and Signal Processing

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    Kartoniert / Broschiert. Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Uses a practical example-based approach to show students how identification really worksTeaches students the fundamentals of systems identification without unduly complicated mathematicsOn-line solutions manual will assist the instructor wi.…

  • Sprache: Englisch

    Verlag: Springer, 2011

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    Serie: Buch 6 von 28 - Advanced Textbooks in Control and Signal Processing

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    Zustand: New. Print on Demand pp. 352 109 Illus. (37 Col.).

  • Sprache: Englisch

    Verlag: Springer, 2011

    0857295217 / 9780857295217

    Serie: Buch 6 von 28 - Advanced Textbooks in Control and Signal Processing

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    Zustand: New. PRINT ON DEMAND pp. 352.

  • Sprache: Englisch

    Verlag: Springer, Springer Mai 2011, 2011

    0857295217 / 9780857295217

    Serie: Buch 6 von 28 - Advanced Textbooks in Control and Signal Processing

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    Taschenbuch. Zustand: Neu. This item is printed on demand - Print on Demand Titel. Neuware -System Identification shows the student reader how to approach the system identification problem in a systematic fashion. The process is divided into three basic steps: experimental design and data collection; model structure selection and parameter estimation; and model validation, each of which is the subject of one or more parts of the text.Following an introduction on system theory, particularly in relation to model representation and model properties, the book contains four parts covering:¿ data-based identification ¿ non-parametric methods for use when prior system knowledge is very limited;¿ time-invariant identification for systems with constant parameters;¿ time-varying systems identification, primarily with recursive estimation techniques; and¿ model validation methods.A fifth part, composed of appendices, covers the various aspects of the underlying mathematics needed to begin using the text.The book uses essentially semi-physical or gray-box modeling methods although data-based, transfer-function system descriptions are also introduced. The approach is problem-based rather than rigorously mathematical. The use of finite input¿output data is demonstrated for frequency- and time-domain identification in static, dynamic, linear, nonlinear, time-invariant and time-varying systems. Simple examples are used to show readers how to perform and emulate the identification steps involved in various control design methods with more complex illustrations derived from real physical, chemical and biological applications being used to demonstrate the practical applicability of the methods described. End-of-chapter exercises (for which a downloadable instructors¿ Solutions Manual is available from fill in URL here) will both help students to assimilate what they have learned and make the book suitable forself-tuition by practitioners looking to brush up on modern techniques.Graduate and final-year undergraduate students will find this text to be a practical and realistic course in system identification that can be used for assessing the processes of a variety of engineering disciplines. System Identification will help academic instructors teaching control-related to give their students a good understanding of identification methods that can be used in the real world without the encumbrance of undue mathematical detail.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 352 pp. Englisch.…