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Sampled-Data Models for Linear and Nonlinear Systems
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 samp...
| Call Number: | Libro Electrónico |
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| Main Authors: | , |
| Corporate Author: | |
| Format: | Electronic eBook |
| Language: | Inglés |
| Published: |
London :
Springer London : Imprint: Springer,
2014.
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| Edition: | 1st ed. 2014. |
| Series: | Communications and Control Engineering,
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| Subjects: | |
| Online Access: | Texto Completo |
Table of Contents:
- 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.