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Multisensor Decision And Estimation Fusion (Hardcover, 2003 ed.)
Loot Price: R4,377
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Multisensor Decision And Estimation Fusion (Hardcover, 2003 ed.)
Series: The International Series on Asian Studies in Computer and Information Science, 14
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YUNMIN ZHU In the past two decades, multi sensor or multi-source
information fusion tech niques have attracted more and more
attention in practice, where observations are processed in a
distributed manner and decisions or estimates are made at the
individual processors, and processed data (or compressed
observations) are then transmitted to a fusion center where the
final global decision or estimate is made. A system with multiple
distributed sensors has many advantages over one with a single
sensor. These include an increase in the capability, reliability,
robustness and survivability of the system. Distributed decision or
estimation fusion prob lems for cases with statistically
independent observations or observation noises have received
significant attention (see Varshney's book Distributed Detec tion
and Data Fusion, New York: Springer-Verlag, 1997, Bar-Shalom's book
Multitarget-Multisensor Tracking: Advanced Applications, vol. 1-3,
Artech House, 1990, 1992,2000). Problems with statistically
dependent observations or observation noises are more difficult and
have received much less study. In practice, however, one often sees
decision or estimation fusion problems with statistically dependent
observations or observation noises. For instance, when several
sensors are used to detect a random signal in the presence of
observation noise, the sensor observations could not be
statistically independent when the signal is present. This book
provides a more complete treatment of the fundamentals of multi
sensor decision and estimation fusion in order to deal with general
random ob servations or observation noises that are correlated
across the sensors."
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