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arxiv: cs/0603064 · v2 · submitted 2006-03-16 · 💻 cs.IT · math.IT

Guessing under source uncertainty

classification 💻 cs.IT math.IT
keywords sourcedivergenceguessingredundancyfamilyidentifiedinformationmeasures
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This paper considers the problem of guessing the realization of a finite alphabet source when some side information is provided. The only knowledge the guesser has about the source and the correlated side information is that the joint source is one among a family. A notion of redundancy is first defined and a new divergence quantity that measures this redundancy is identified. This divergence quantity shares the Pythagorean property with the Kullback-Leibler divergence. Good guessing strategies that minimize the supremum redundancy (over the family) are then identified. The min-sup value measures the richness of the uncertainty set. The min-sup redundancies for two examples - the families of discrete memoryless sources and finite-state arbitrarily varying sources - are then determined.

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