MATLAB Functions

Normally distributed random numbers and arrays

Y = randn(n)
Y = randn(m,n)
Y = randn([m n])
Y = randn(m,n,p,...)
Y = randn([m n p...])
Y = randn(size(A))
randn
s = randn('state')

Description

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:


`randn('state',s)`	Resets the state to `s`.
`randn('state',0)`	Resets the generator to its initial state.
`randn('state',j)`	For integer `j`, resets the generator to its `j`th state.
`randn('state',sum(100*clock))`	Resets it to a different state each time.

Remarks

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.

Examples

R = randn(3,4) may produce

 R =
    1.1650    0.3516    0.0591    0.8717
    0.6268   -0.6965    1.7971   -1.4462
    0.0751    1.6961    0.2641   -0.7012

For a histogram of the randn distribution, see hist.