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Entropy Measures, Maximum Entropy Principle and Emerging Applications (Paperback, Softcover reprint of the original 1st ed. 2003)
Loot Price: R5,706
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Entropy Measures, Maximum Entropy Principle and Emerging Applications (Paperback, Softcover reprint of the original 1st ed. 2003)
Series: Studies in Fuzziness and Soft Computing, 119
Expected to ship within 10 - 15 working days
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The last two decades have witnessed an enormous growth with regard
to ap plications of information theoretic framework in areas of
physical, biological, engineering and even social sciences. In
particular, growth has been spectac ular in the field of
information technology, soft computing, nonlinear systems and
molecular biology. Claude Shannon in 1948 laid the foundation of
the field of information theory in the context of communication
theory. It is in deed remarkable that his framework is as relevant
today as was when he 1 proposed it. Shannon died on Feb 24, 2001.
Arun Netravali observes "As if assuming that inexpensive,
high-speed processing would come to pass, Shan non figured out the
upper limits on communication rates. First in telephone channels,
then in optical communications, and now in wireless, Shannon has
had the utmost value in defining the engineering limits we face."
Shannon introduced the concept of entropy. The notable feature of
the entropy frame work is that it enables quantification of
uncertainty present in a system. In many realistic situations one
is confronted only with partial or incomplete information in the
form of moment, or bounds on these values etc.; and it is then
required to construct a probabilistic model from this partial
information. In such situations, the principle of maximum entropy
provides a rational ba sis for constructing a probabilistic model.
It is thus necessary and important to keep track of advances in the
applications of maximum entropy principle to ever expanding areas
of knowledge."
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