System Identification with Quantized Observations (Systems & Control: Foundations & Applications)

Le Yi Wang; G. George Yin; Ji-Feng Zhang; Yanlong Zhao

ISBN 10: 0817649557 / ISBN 13: 9780817649555

Verlag: Birkhäuser, 2010

Beschreibung

Birkhaeuser Verlag; Boston, 2010. Hardcover. A Very Good, binding firm, some handling/scuff marks to boards, small abrasion bottom front board edge, couple of small scuff marks to fore-edge, rubbed board corners, without Dust wrapper. A nice, clean and unmarked copy. 8vo[octavo or approx. 6 x 9 inches], 317pp., appendix, references, indexed. We pack securely and ship daily with delivery confirmation on every book. The picture on the listing page is of the actual book for sale. Additional Scan(s) are available for any item, please inquire.Please note: Oversized books/sets MAY require additional postage then what is quoted for 2.2lb book.

Bestandsnummer des Verkäufers SKU1037479

Bibliografische Details

• Titel: System Identification with Quantized Observations (Systems & Control: Foundations & Applications)
• Verlag: Birkhäuser
• Erscheinungsjahr: 2010
• Sprache: Englisch
• ISBN-10: 0817649557
• ISBN-13: 9780817649555
• Einband: hardcover
• Zustand: Very Good
• Gewicht: 50 Unzen
• Verkäuferkataloge:
  • Math Text Books

Über diesen Titel

Inhaltsangabe

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.

Von der hinteren Coverseite

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.

Providing a comprehensive coverage of quantized identification, the book treats linear and nonlinear systems, as well as time-invariant and time-varying systems. The authors examine independent and dependent noises, stochastic- and deterministic-bounded noises, and also noises with unknown distribution functions. The key methodologies combine empirical measures and information-theoretic approaches to derive identification algorithms, provide convergence and convergence speed, establish efficiency of estimation, and explore input design, threshold selection and adaptation, and complexity analysis.

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. Selected material from the book may be used in graduate-level courses on system identification.