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.
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