System Identification with Quantized Observations (eBook)
XVIII, 317 Seiten
Birkhäuser Boston (Verlag)
978-0-8176-4956-2 (ISBN)
This book presents recently developed methodologies that utilize quantized information in system identification and explores their potential in extending control capabilities for systems with limited sensor information or networked systems. The results of these methodologies can be applied to signal processing and control design of communication and computer networks, sensor networks, mobile agents, coordinated data fusion, remote sensing, telemedicine, and other fields in which noise-corrupted quantized data need to be processed.
System Identification with Quantized Observations is an excellent resource for graduate students, systems theorists, control engineers, applied mathematicians, as well as practitioners who use identification algorithms in their work.
This book concerns the identi?cation of systems in which only quantized output observations are available, due to sensor limitations, signal quan- zation, or coding for communications. Although there are many excellent treaties in system identi?cation and its related subject areas, a syst- atic study of identi?cation with quantized data is still in its early stage. This book presents new methodologies that utilize quantized information in system identi?cation and explores their potential in extending control capabilities for systems with limited sensor information or networked s- tems. The book is an outgrowth of our recent research on quantized iden- ?cation; it o?ers several salient features. From the viewpoint of targeted plants, it treats both linear and nonlinear systems, and both time-invariant and time-varying systems. In terms of noise types, it includes independent and dependent noises, stochastic disturbances and deterministic bounded noises, and noises with unknown distribution functions. The key meth- ologies of the book combine empirical measures and information-theoretic approaches to cover convergence, convergence rate, estimator e?ciency, - put design, threshold selection, and complexity analysis. We hope that it can shed new insights and perspectives for system identi?cation.
Overview.- System Settings.- Stochastic Methods for Linear Systems.- Empirical-Measure-Based Identification: Binary-Valued Observations.- Estimation Error Bounds: Including Unmodeled Dynamics.- Rational Systems.- Quantized Identification and Asymptotic Efficiency.- Input Design for Identification in Connected Systems.- Identification of Sensor Thresholds and Noise Distribution Functions.- Deterministic Methods for Linear Systems.- Worst-Case Identification under Binary-Valued Observations.- Worst-Case Identification Using Quantized Observations.- Identification of Nonlinear and Switching Systems.- Identification of Wiener Systems with Binary-Valued Observations.- Identification of Hammerstein Systems with Quantized Observations.- Systems with Markovian Parameters.- Complexity Analysis.- Space and Time Complexities, Threshold Selection, Adaptation.- Impact of Communication Channels on System Identification.
| Erscheint lt. Verlag | 18.5.2010 |
|---|---|
| Reihe/Serie | Systems & Control: Foundations & Applications | Systems & Control: Foundations & Applications |
| Zusatzinfo | XVIII, 317 p. 42 illus. |
| Verlagsort | Boston |
| Sprache | englisch |
| Themenwelt | Mathematik / Informatik ► Informatik ► Programmiersprachen / -werkzeuge |
| Mathematik / Informatik ► Informatik ► Theorie / Studium | |
| Mathematik / Informatik ► Mathematik ► Statistik | |
| Naturwissenschaften | |
| Technik ► Elektrotechnik / Energietechnik | |
| Technik ► Maschinenbau | |
| Technik ► Nachrichtentechnik | |
| Schlagworte | algorithm • algorithms • Analysis • binary-valued observation • Communication • complexity analysis • Identification • identification algorithm • Markov • nonlinear system • nonlinear system identification • Parameter Estimation • quantized observation • Signal • stochastic analysis • System • System Identification • worst-case identification |
| ISBN-10 | 0-8176-4956-5 / 0817649565 |
| ISBN-13 | 978-0-8176-4956-2 / 9780817649562 |
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