From dawagner@tucson.princeton.edu Tue Mar 21 15:23:47 EST 1995 Article: 33479 of sci.crypt Newsgroups: sci.crypt Path: princeton!tucson.princeton.edu!dawagner From: dawagner@tucson.princeton.edu (David A. Wagner) Subject: Statistically distinguishing two random sources Message-ID: <1995Mar21.201232.22137@Princeton.EDU> Originator: news@hedgehog.Princeton.EDU Sender: news@Princeton.EDU (USENET News System) Nntp-Posting-Host: tucson.princeton.edu Organization: Princeton University Date: Tue, 21 Mar 1995 20:12:32 GMT Lines: 15 I'm sure this must be completely solved already somewhere... I have two memoryless random sources outputting b-bit chunks: one has the uniform distribution on {0,1}^b, and the other has some known distribution. I flip a coin, pick one of the two sources, and give you lots of outputs from that source. Assume you know the distribution of both sources, and think of b as small -- maybe 5 or 10. Roughly how many outputs do you need to distinguish the two sources with high probability? (in terms of their distributions) What algorithm would you use to actually do this? [I guess I'm looking for some sort of measure of the distance between the two random sources.]