Probability with Application and turings only crypto paper/manuscript


http://www.math.harvard.edu/~knill/probability/index.html

I actually understand 90 per cent of this. Now i can see that some of turings notation for f() and g() are symbols for random variables, he tended to use quantum mechanical structures leveraging norms (that normalize!), expectation values and conditional probabilities expressed as ratios such as g(a.b-1.c) / g(a.b-1).

Its also fun to see turing present k wiring sets on a wheel as k generators (of a distribution), then be concerned with several such wheels, and the case that the sequence of those generators can be required to have relative offsets that sum to zero and thereby construct a particular annihilating kernel that differentiates the measure-preserving space, being attracted towards a particular fixed point – the unique stationary distribution for the wheel settings.

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About home_pw@msn.com

Computer Programmer who often does network administration with focus on security servers. Very strong in Microsoft Azure cloud!
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