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Normally distributed random numbers and arrays



The randn function generates arrays of random numbers whose elements are normally distributed with mean 0 and variance 1.

Y = randn(n) returns an n-by-n matrix of random entries. An error message appears if n is not a scalar.

Y = randn(m,n) or Y = randn([m n]) returns an m-by-n matrix of random entries.

Y = randn(m,n,p,...) or Y = randn([m n p...]) generates random arrays.

Y = randn(size(A)) returns an array of random entries that is the same size as A.

randn, by itself, returns a scalar whose value changes each time it's referenced.

s = randn('state') returns a 2-element vector containing the current state of the normal generator. To change the state of the generator:

Resets the state to s.
Resets the generator to its initial state.
For integer j, resets the generator to its jth state.
Resets it to a different state each time.


MATLAB 5 uses a new multiseed random number generator that can generate all the floating-point numbers in the closed interval Theoretically, it can generate over values before repeating itself. MATLAB 4 used random number generators with a single seed. randn('seed',0)and randn('seed',j) use the MATLAB 4 generator. randn('seed') returns the current seed of the MATLAB 4 normal generator. randn('state',j) and randn('state',s) use the MATLAB 5 generator.


R = randn(3,4) may produce

For a histogram of the randn distribution, see hist.

See Also

rand        Uniformly distributed random numbers and arrays

randperm    Random permutation

sprand      Sparse uniformly distributed random matrix

sprandn     Sparse normally distributed random matrix

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