c++ - Time complexity of Random Gaussian Function -

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I have implemented the Cross-Entropy Minimization Method in C ++ while referring to the Ruby Code given to me < P> I can not understand how the random_gazy function is associated with normal distribution and what it really is doing. Apart from this, I am unable to know the complexity of this ceremony. Please help me with these two things dual random _gasian (double meaning, double staidew) {double u 1, u2, w; Do {u1 = 2 * ((double) rand () / RAITMX) - 1; U2 = 2 * ((double) rand () / RAidmx) - 1; W = u1 * u1 + u2 * u2; } While (w> = 1); W = sqrt ((-2.0 * log (w)) / w); Return means + (u2 * w) * stdev; }

Here the C ++ code is to solve the program Ax = B and it is working fine.

... while block corners (and; 1, and ;; 1) makes a point in the square until the point becomes root in a circle of radius centered in the original. The expected number of iterations is the ratio of regions, which is in absolute 4 / π or o (1) large-o-notation.

How is this process related to Gaussian distribution, one application of this is another page, which is a little code that includes your code.

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