Transforming data to Gaussian using probability integral transform in Matlab:

n = 500;
x=exp(randn(n,1))+(randi(2,[n 1])-1).*(10+3*randn(n,1));
fhat = @(in) sum(x <= in)/n;
Fhat = @(A) arrayfun(fhat,A);
y=Fhat(x); z = icdf('normal',y,0,1);
figure; subplot(1,2,1); hist(x,20); xlabel('x');
subplot(1,2,2); hist(z,20); xlabel('z');

Results:

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