Sampled-data models for linear and nonlinear systems [electronic resource] / Juan I. Yuz, Graham C. Goodwin.
Yuz, Juan I., author.; Goodwin, Graham C. (Graham Clifford), 1945- author.
2014
QA276.6
Available Online

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Title Sampled-data models for linear and nonlinear systems [electronic resource] / Juan I. Yuz, Graham C. Goodwin.
Author Yuz, Juan I., author.
ISBN 9781447155621 electronic book
1447155629 electronic book
9781447155614
1306162459
9781306162456
DOI https://doi.org/10.1007/978-1-4471-5562-1
Published London : Springer, 2014.
Language English
Description 1 online resource (xvii, 289 pages) : illustrations (some color).
Item Number 10.1007/978-1-4471-5562-1 doi
Call Number QA276.6
Dewey Decimal Classification 519.5/2
Summary Sampled-data Models for Linear and Nonlinear Systems provides a fresh new look at a subject with which many researchers may think themselves familiar. Rather than emphasising the differences between sampled-data and continuous-time systems, the authors proceed from the premise that, with modern sampling rates being as high as they are, it is becoming more appropriate to emphasise connections and similarities.
Bibliography, etc. Note Includes bibliographical references and index.
Access Note Access limited to authorized users.
Source of Description Description based on online resource; title from PDF title page (SpringerLink, viewed October 21, 2013).
Added Author Goodwin, Graham C. (Graham Clifford), 1945- author.
Series Communications and control engineering series.
Linked Resources Online Access
Record Appears in Online Resources > Ebooks
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Part I: Deterministic Systems
Background on Sampling of Signals.-Sampled Data Models for Linear Deterministic Systems
Incremental Sampled Data Models
Asymptotic Sampling Zeros
Generalized Hold Devices
Robustness
Approximate Models for Linear Deterministic Systems
Approximate Models for Deterministic Nonlinear Systems
Applications of Approximate Sampled-data Models in Estimation and Control
Part II: Stochastic Systems
Background on Sampling of Stochastic Signals
Sampled-data Models for Linear Stochastic Systems
Incremental Stochastic Sampled-data Models
Asymptotic Sampling Zeros for Linear Stochastic Systems
Generalized Sampling Filters
Approximate Sampled-data Models for Linear Stochastic Systems
Stochastic Nonlinear Systems
Approximate Sampled-data Models for Nonlinear Stochastic Systems
Applications of Approximate Stochastic Sampled-data Models
Part III: Embellishments and Extensions
The Euler-Frobenius Polynominals
Models for Intersample Response
Approximate Sampled-data Models for Fractional Order Systems.

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