Dynamic feature space modelling, filtering and self-tuning control of stochastic systems. a systems approach with economic and social applications.

Otter, Pieter W.:

A�o de publicaci�n: 1985

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Ehem. Bibliotheksexemplar mit Signatur und Stempel. GUTER Zustand, ein paar Gebrauchsspuren. Ex-library with stamp and library-signature. GOOD condition, some traces of use. Sj 689 354015642 Sprache: Englisch Gewicht in Gramm: 550. N� de ref. del art�culo 2090971

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T�tulo: Dynamic feature space modelling, filtering ...
A�o de publicaci�n: 1985

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Dynamic Feature Space Modelling, Filtering and Self-Tuning Control of Stochastic Systems. A Systems Approach with Economic and Social Applications. (=Lecture Notes in Economic and Mathematical Systems; 246).

Otter, Pieter W.:

Publicado por Springer Berlin, 1985

ISBN 10: 3540156542 ISBN 13: 9783540156543

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Paperback/ broschiert. Condici�n: Wie neu. 177 S. Mathematikwissenschaft Naturwissenschaft Mathematics Natural Science stochastische Systeme Stamped edges. Befriedigender Zustand With figures. Ex-Library. Brownish paper. ha1087758 Sprache: Englisch Gewicht in Gramm: 550. N� de ref. del art�culo: 403417

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Dynamic Feature Space Modelling, Filtering and Self-Tuning Control of Stochastic Systems : A Systems Approach with Economic and Social Applications

Otter, Pieter W.

Publicado por Springer, 1985

ISBN 10: 3540156542 ISBN 13: 9783540156543

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Condici�n: Sehr gut. Zustand: Sehr gut | Sprache: Englisch | Produktart: B�cher | The literature on systems seems to have been growing almost expo� nentially during the last decade and one may question whether there is need for another book. In the author's view, most of the literature on 'systems' is either technical in mathematical sense or technical ifF engineering sense (with technical words such as noise, filtering etc. ) and not easily accessible to researchers is other fields, in particular not to economists, econometricians and quantitative researchers in so� cial sciences. This is unfortunate, because achievements in the rather 'young' science of system theory and system engineering are of impor� tance for modelling, estimation and regulation (control) problems in other branches of science. State space mode~iing; the concept of ob� servability and controllability; the mathematical formulations of sta� bility; the so-called canonical forms; prediction error e~timation; optimal control and Kalman filtering are some examples of results of system theory and system engineering which proved to be successful in practice. A brief summary of system theoretical concepts is given in Chapter II where an attempt has been made to translate the concepts in� to the more 'familiar' language used in econometrics and social sciences by means of examples. By interrelating concepts and results from system theory with those from econometrics and social sciences, the author has attempted to narrow the gap between the more technical sciences such as engi� neering and social sciences and econometrics, and to contribute to either side. N� de ref. del art�culo: 651341/202

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Dynamic Feature Space Modelling, Filtering and Self-Tuning Control of Stochastic Systems: A Systems Approach with Economic and Social Applications . and Mathematical Systems, 246, Band 246)

Otter Pieter, W.:

Publicado por Springer-Verlag, 1985

ISBN 10: 3540156542 ISBN 13: 9783540156543

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Librería: Studibuch, Stuttgart, Alemania

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paperback. Condici�n: Gut. 200 Seiten; 9783540156543.3 Gewicht in Gramm: 500. N� de ref. del art�culo: 1009062

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Dynamic Feature Space Modelling, Filtering and Self-Tuning Control of Stochastic Systems | A Systems Approach with Economic and Social Applications

Pieter W. Otter

Publicado por Springer, 1985

ISBN 10: 3540156542 ISBN 13: 9783540156543

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Dynamic Feature Space Modelling, Filtering and Self-Tuning Control of Stochastic Systems: A Systems Approach with Economic and Social Applications ... in Economics and Mathematical Systems, 246)

Otter, Pieter W.

Publicado por Springer, 1985

ISBN 10: 3540156542 ISBN 13: 9783540156543

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Condici�n: New. N� de ref. del art�culo: ABLIING23Mar3113020160687

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Dynamic Feature Space Modelling, Filtering and Self-Tuning Control of Stochastic Systems : A Systems Approach with Economic and Social Applications

Pieter W. Otter

Publicado por Springer Berlin Heidelberg, 1985

ISBN 10: 3540156542 ISBN 13: 9783540156543

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Librería: AHA-BUCH GmbH, Einbeck, Alemania

Calificaci�n del vendedor: 5 de 5 estrellas

Taschenbuch. Condici�n: Neu. Druck auf Anfrage Neuware - Printed after ordering - The literature on systems seems to have been growing almost expo nentially during the last decade and one may question whether there is need for another book. In the author's view, most of the literature on 'systems' is either technical in mathematical sense or technical ifF engineering sense (with technical words such as noise, filtering etc. ) and not easily accessible to researchers is other fields, in particular not to economists, econometricians and quantitative researchers in so cial sciences. This is unfortunate, because achievements in the rather 'young' science of system theory and system engineering are of impor tance for modelling, estimation and regulation (control) problems in other branches of science. State space mode~iing; the concept of ob servability and controllability; the mathematical formulations of sta bility; the so-called canonical forms; prediction error e~timation; optimal control and Kalman filtering are some examples of results of system theory and system engineering which proved to be successful in practice. A brief summary of system theoretical concepts is given in Chapter II where an attempt has been made to translate the concepts in to the more 'familiar' language used in econometrics and social sciences by means of examples. By interrelating concepts and results from system theory with those from econometrics and social sciences, the author has attempted to narrow the gap between the more technical sciences such as engi neering and social sciences and econometrics, and to contribute to either side. N� de ref. del art�culo: 9783540156543

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