Den måndag 11 juli 2016 kl. 20:09:39 UTC+2 skrev Waffle: > On 11 July 2016 at 20:52, <jonas.thornv...@gmail.com> wrote: > > What kind of statistic law or mathematical conjecture or is it even a > > physical law is violated by compression of random binary data? > > > > I only know that Shanon theorised it could not be done, but were there any > > proof? > > Compression relies on some items in the dataset being more frequent > than others, if you have some dataset that is completely random it > would be hard to compress as most items have very similar number of > occurrances. > > > What is to say that you can not do it if the symbolic representation is > > richer than the symbolic represenatation of the dataset. > > > > Isn't it a fact that the set of squareroots actually depict numbers in a > > shorter way than their actual representation. > > A square root may be smaller numerically than a number but it > definitely is not smaller in terms of entropy. > > lets try to compress the number 2 for instance using square roots. > sqrt(2) = 1.4142 > the square root actually takes more space in this case even tho it is > a smaller number. so having the square root would have negative > compression in this case. > with some rounding back and forth we can probably get around the fact > that sqrt(2) would take an infinite amout of memory to accurately > represent but that neccesarily means restricting the values we are > possible of encoding. > > for sqrt(2) to not have worse space consumprion than the number 2 > itself we basically have to trow away precision so sqrt(2) ~= 1 > now i challenge you to get that 2 back out of that 1..
Well who it to say different kind of numbers isn't treated differently, i mean all numbers isn't squares. All numbers isn't naturals. -- https://mail.python.org/mailman/listinfo/python-list
