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Books > Professional & Technical > Technology: general issues > Instruments & instrumentation engineering
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Data Fusion Mathematics - Theory and Practice (Paperback)
Loot Price: R2,505
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Data Fusion Mathematics - Theory and Practice (Paperback)
Expected to ship within 12 - 17 working days
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Fills the Existing Gap of Mathematics for Data Fusion Data fusion
(DF) combines large amounts of information from a variety of
sources and fuses this data algorithmically, logically and, if
required intelligently, using artificial intelligence (AI). Also,
known as sensor data fusion (SDF), the DF fusion system is an
important component for use in various applications that include
the monitoring of vehicles, aerospace systems, large-scale
structures, and large industrial automation plants. Data Fusion
Mathematics: Theory and Practice offers a comprehensive overview of
data fusion, and provides a proper and adequate understanding of
the basic mathematics directly related to DF. The material covered
can be used for evaluation of the performances of any designed and
developed DF systems. It tries to answer whether unified data
fusion mathematics can evolve from various disparate mathematical
concepts, and highlights mathematics that can add credibility to
the data fusion process. Focuses on Mathematical Tools That Use
Data Fusion This text explores the use of statistical/probabilistic
signal/image processing, filtering, component analysis, image
algebra, decision making, and neuro-FL-GA paradigms in studying,
developing and validating data fusion processes (DFP). It covers
major mathematical expressions, and formulae and equations as well
as, where feasible, their derivations. It also discusses SDF
concepts, DF models and architectures, aspects and methods of type
1 and 2 fuzzy logics, and related practical applications. In
addition, the author covers soft computing paradigms that are
finding increasing applications in multisensory DF approaches and
applications. This book: Explores the use of interval type 2 fuzzy
logic and ANFIS in DF Covers the mathematical treatment of many
types of filtering algorithms, target-tracking methods, and
kinematic DF methods Presents single and multi-sensor tracking and
fusion mathematics Considers specific DF architectures in the
context of decentralized systems Discusses information filtering,
Bayesian approaches, several DF rules, image algebra and image
fusion, decision fusion, and wireless sensor network (WSN)
multimodality fusion Data Fusion Mathematics: Theory and Practice
incorporates concepts, processes, methods, and approaches in data
fusion that can help you with integrating DF mathematics and
achieving higher levels of fusion activity, and clarity of
performance. This text is geared toward researchers, scientists,
teachers and practicing engineers interested and working in the
multisensor data fusion area.
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