Information theory is a relatively new branch of mathematics that
was made mathematically rigorous only in the 1940s. Since
information is energy, we have to measure, manage, regulate and
control it for the welfare of mankind. The main use of information
is to remove uncertainty. In fact, we measure information supplied
by the amount of uncertainty removed in an experiment. Hence the
measure of information is essentially a measure of uncertainty.
Various measures of information such as entropies and directed
divergence have attracted the interest of scientific community
recently primarily due to their use in several disciplines such as
in Biology, Psychology, Economics, Statistics, Cybernetics,
Questionnaire theory, coding theory and many more. The aim of this
book is to study generalized information measures and their
applications. New generalized exponential survival entropies are
defined and their important properties and applications have been
studied. The generalized 'useful' f-divergence information measures
have been introduced and their bounds have been derived.
General
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