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Books > Computing & IT > Applications of computing > Artificial intelligence
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Data Fusion: Concepts and Ideas (Paperback, 2nd ed. 2012)
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Data Fusion: Concepts and Ideas (Paperback, 2nd ed. 2012)
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This textbook provides a comprehensive introduction to the concepts
and idea of multisensor data fusion.
It is an extensively revised second edition of the author's
successful book: "Multi-Sensor Data Fusion:
An Introduction" which was originally published by Springer-Verlag
in 2007.
The main changes in the new book are:
New Material: Apart from one new chapter there are approximately 30
new sections, 50 new examples and 100 new references. At the same
time, material which is out-of-date has been eliminated and the
remaining text has been rewritten for added clarity. Altogether,
the new book is nearly 70 pages
longer than the original book.
Matlab code: Where appropriate we have given details of Matlab code
which may be downloaded from the worldwide web. In a few places,
where such code is not readily available, we have included Matlab
code in the body of the text.
Layout. The layout and typography has been revised. Examples and
Matlab code now appear on a gray background for easy identification
and advancd material is marked with an asterisk.
The book is intended to be self-contained. No previous knowledge of
multi-sensor data fusion is assumed, although some familarity with
the basic tools of linear algebra, calculus and simple probability
is recommended.
Although conceptually simple, the study of mult-sensor data fusion
presents challenges that are unique within the education of the
electrical engineer or computer scientist. To become competent in
the field the student must become familiar with tools taken from a
wide range of diverse subjects including: neural networks, signal
processing, statistical estimation, tracking algorithms, computer
vision and control theory. All too often, the student views
multi-sensor data fusion as a miscellaneous assortment of different
processes which bear no relationship to each other. In contrast, in
this book the processes are unified by using a common statistical
framework. As a consequence, the underlying pattern of
relationships that exists between the different methodologies is
made evident.
The book is illustrated with many real-life examples taken from a
diverse range of applications and contains an extensive list of
modern references."
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