Isbn: 9780486469355 - an introduction to identification (dover books on electrical engineering) (20 Ergebnisse)

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Paperback. Zustand: new. Paperback. Advanced undergraduates and graduate students of electrical, chemical, mechanical, and environmental engineering will appreciate this text for a course in systems identification. In addition to the theoretical basis for mathematical modeling, it covers a variety of tried-and-true identification algorithms and their applications. Moreover, its broad view and fairly modest mathematical level offer readers a quick appraisal of established methods and their limitations. In addition to surveys covering classical methods of identification - including impulse, step, and sine-wave testing - and identification based on correlation function, the text examines least-squares model fitting, statistical properties of estimators, optimal estimation, and Bayes and maximum-likelihood estimators. Other topics include experiment design and choice of model structure as well as model validation. Numerical examples show students how to apply the modeling theories, and a chapter on specialized topics introduces research areas. Suitable for advanced undergraduates and graduate students, this text covers the theoretical basis for mathematical modeling as well as a variety of identification algorithms and their applications. 1986 edition. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

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Taschenbuch. Zustand: Neu. Neuware - Advanced undergraduates and graduate students of electrical, chemical, mechanical, and environmental engineering will appreciate this text for a course in systems identification. In addition to the theoretical basis for mathematical modeling, it covers a variety of identification algorithms and their applications. Numerical examples show how to apply modeling theories. 1986 edition.…

Zustand: New. KlappentextrnrnSuitable for advanced undergraduates and graduate students, this text covers the theoretical basis for mathematical modeling as well as a variety of identification algorithms and their applications. 1986 edition.

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Paperback. Zustand: new. Paperback. Advanced undergraduates and graduate students of electrical, chemical, mechanical, and environmental engineering will appreciate this text for a course in systems identification. In addition to the theoretical basis for mathematical modeling, it covers a variety of tried-and-true identification algorithms and their applications. Moreover, its broad view and fairly modest mathematical level offer readers a quick appraisal of established methods and their limitations. In addition to surveys covering classical methods of identification - including impulse, step, and sine-wave testing - and identification based on correlation function, the text examines least-squares model fitting, statistical properties of estimators, optimal estimation, and Bayes and maximum-likelihood estimators. Other topics include experiment design and choice of model structure as well as model validation. Numerical examples show students how to apply the modeling theories, and a chapter on specialized topics introduces research areas. Suitable for advanced undergraduates and graduate students, this text covers the theoretical basis for mathematical modeling as well as a variety of identification algorithms and their applications. 1986 edition. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.…

Paperback. Zustand: new. Paperback. Advanced undergraduates and graduate students of electrical, chemical, mechanical, and environmental engineering will appreciate this text for a course in systems identification. In addition to the theoretical basis for mathematical modeling, it covers a variety of tried-and-true identification algorithms and their applications. Moreover, its broad view and fairly modest mathematical level offer readers a quick appraisal of established methods and their limitations. In addition to surveys covering classical methods of identification - including impulse, step, and sine-wave testing - and identification based on correlation function, the text examines least-squares model fitting, statistical properties of estimators, optimal estimation, and Bayes and maximum-likelihood estimators. Other topics include experiment design and choice of model structure as well as model validation. Numerical examples show students how to apply the modeling theories, and a chapter on specialized topics introduces research areas. Suitable for advanced undergraduates and graduate students, this text covers the theoretical basis for mathematical modeling as well as a variety of identification algorithms and their applications. 1986 edition. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…