Comments on the Chernoff estimate
نویسندگان
چکیده
منابع مشابه
Chernoff Bounds
If m = 2, i.e., P = (p, 1 − p) and Q = (q, 1 − q), we also write DKL(p‖q). The Kullback-Leibler divergence provides a measure of distance between the distributions P and Q: it represents the expected loss of efficiency if we encode an m-letter alphabet with distribution P with a code that is optimal for distribution Q. We can now state the general form of the Chernoff Bound: Theorem 1.1. Let X1...
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ژورنال
عنوان ژورنال: ???????????: ??????, ?????, ??????????
سال: 2022
ISSN: ['2220-8054', '2305-7971']
DOI: https://doi.org/10.17586/2220-8054-2022-13-1-17-23