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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.
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