How to convert a gaussian distributed rnd sequence to uniform dist and viceversa

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To convert a uniformly distributed random number sequence to a Gaussian distribution, the inverse of the cumulative distribution function (CDF) of the Gaussian distribution can be applied. Specifically, if F is the CDF of the Gaussian distribution and x is a uniform random variable in the range [0, 1], then y = F^{-1}(x) will yield a Gaussian-distributed output. Conversely, to transform a Gaussian distribution to a uniform distribution, one can use the CDF of the Gaussian distribution directly. This mathematical approach allows for effective conversion between the two distributions. Understanding these transformations is crucial for applications requiring specific statistical properties in random number generation.
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Hi PF,
I have a device (with a microcontroller) which generates random numbers. when I analyzed those numbers using Matlab software I found that it is following a uniform distribution. How can I mathematically (any algorithm?) convert this random output to a gaussian one. Also I would like to know the reverse case ie gaussian to uniform one.

-Devanand T
 
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If F is the cdf of the Gaussian distribution, and x is a point from your uniform distribution 0<=x<=1, then y= F^{-1} (x) has a Gaussian distribution.
 
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