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current | 16:07, 9 February 2015 | 300 × 300 (1 KB) | Krishnavedala | simplified drawing | |
15:19, 22 April 2007 | 169 × 163 (40 KB) | Alejo2083 | {{Information |Description= Information entropy of a Bernoulli trial ''X''. If ''X'' can assume values 0 and 1, entropy of ''X'' is defined as ''H''(''X'') = -Pr(''X''=0) log<sub>2</sub> Pr(''X''=0) - Pr(''X''=1) log<sub>2</sub> Pr(''X''=1). It has |
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