It also follows that if the symbol space is binary (0 or 1), then assuming a fully decorrelated and uniformly distributed sequence bits, the entropy per symbol (bit) is precisely log2(2) = 1.
>From that, it logically follows that an N bit long decorrelated and uniform sequence of bits (= "white noise") has N bits of entropy. In other words, "white noise" has the _maximum_ amount of entropy, since N bits can be guessed in a maximum of 2^N 'yes/no' guesses, therefore that is the maximum possible entropy. It follows, that if we estimate how much a signal looks like "white noise" (= how much 'decorrelation' or 'randomness' is in it), we can estimate entropy. -- dupswapdrop -- the music-dsp mailing list and website: subscription info, FAQ, source code archive, list archive, book reviews, dsp links http://music.columbia.edu/cmc/music-dsp http://music.columbia.edu/mailman/listinfo/music-dsp
