|
Showing 1 - 5 of
5 matches in All Departments
This comprehensive text provides an excellent introduction to the
state of the art in the identification of network-connected
systems. It covers models and methods in detail, includes a case
study showing how many of these methods are applied in adaptive
optics and addresses open research questions. Specific models
covered include generic modelling for MIMO LTI systems, signal flow
models of dynamic networks and models of networks of local LTI
systems. A variety of different identification methods are
discussed, including identification of signal flow dynamics
networks, subspace-like identification of multi-dimensional systems
and subspace identification of local systems in an NDS. Researchers
working in system identification and/or networked systems will
appreciate the comprehensive overview provided, and the emphasis on
algorithm design will interest those wishing to test the theory on
real-life applications. This is the ideal text for researchers and
graduate students interested in system identification for networked
systems.
This book is intended for researchers active in the field of
(blind) system identification and aims to provide new
identification ideas/insights for dealing with challenging system
identification problems. It presents a comprehensive overview of
the state-of-the-art in the area, which would save a lot of time
and avoid collecting the scattered information from research
papers, reports and unpublished work. Besides, it is a
self-contained book by including essential algebraic, system and
optimization theories, which can help graduate students enter the
amazing blind system identification world with less effort.
Filtering and system identification are powerful techniques for
building models of complex systems. This 2007 book discusses the
design of reliable numerical methods to retrieve missing
information in models derived using these techniques. Emphasis is
on the least squares approach as applied to the linear state-space
model, and problems of increasing complexity are analyzed and
solved within this framework, starting with the Kalman filter and
concluding with the estimation of a full model, noise statistics
and state estimator directly from the data. Key background topics,
including linear matrix algebra and linear system theory, are
covered, followed by different estimation and identification
methods in the state-space model. With end-of-chapter exercises,
MATLAB simulations and numerous illustrations, this book will
appeal to graduate students and researchers in electrical,
mechanical and aerospace engineering. It is also useful for
practitioners. Additional resources for this title, including
solutions for instructors, are available online at
www.cambridge.org/9780521875127.
This book is intended for researchers active in the field of
(blind) system identification and aims to provide new
identification ideas/insights for dealing with challenging system
identification problems. It presents a comprehensive overview of
the state-of-the-art in the area, which would save a lot of time
and avoid collecting the scattered information from research
papers, reports and unpublished work. Besides, it is a
self-contained book by including essential algebraic, system and
optimization theories, which can help graduate students enter the
amazing blind system identification world with less effort.
Filtering and system identification are powerful techniques for
building models of complex systems. This 2007 book discusses the
design of reliable numerical methods to retrieve missing
information in models derived using these techniques. Emphasis is
on the least squares approach as applied to the linear state-space
model, and problems of increasing complexity are analyzed and
solved within this framework, starting with the Kalman filter and
concluding with the estimation of a full model, noise statistics
and state estimator directly from the data. Key background topics,
including linear matrix algebra and linear system theory, are
covered, followed by different estimation and identification
methods in the state-space model. With end-of-chapter exercises,
MATLAB simulations and numerous illustrations, this book will
appeal to graduate students and researchers in electrical,
mechanical and aerospace engineering. It is also useful for
practitioners. Additional resources for this title, including
solutions for instructors, are available online at
www.cambridge.org/9780521875127.
|
You may like...
Loot
Nadine Gordimer
Paperback
(2)
R398
R330
Discovery Miles 3 300
Loot
Nadine Gordimer
Paperback
(2)
R398
R330
Discovery Miles 3 300
Personal Shopper
Kristen Stewart, Nora von Waldstätten, …
DVD
R86
Discovery Miles 860
|