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{{CyberTerm|definition=A lower bound on the entropy of a random variable. The precise formulation for min-entropy is&nbsp;<span class="math-tex">\((-\log_{2} \max p_{i})\)</span>&nbsp;for a discrete distribution having probabilities&nbsp;<span class="math-tex">\(p_{1},...,p_{k}\)</span>. Min-entropy is often used as a measure of the unpredictability of a random variable.|source=NIST IR 8427}}
{{CyberTerm|definition=A lower bound on the entropy of a random variable. The precise formulation for min-entropy is&nbsp;\((-\log_{2} \max p_{i})\)&nbsp;for a discrete distribution having probabilities&nbsp;\(p_{1},...,p_{k}\). Min-entropy is often used as a measure of the unpredictability of a random variable.|source=NIST IR 8427}}

Latest revision as of 00:24, 20 January 2026

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Min-entropy

A lower bound on the entropy of a random variable. The precise formulation for min-entropy is \((-\log_{2} \max p_{i})\) for a discrete distribution having probabilities \(p_{1},...,p_{k}\). Min-entropy is often used as a measure of the unpredictability of a random variable.


Source: NIST IR 8427 | Category: