MATLAB Function Reference

randn

Normally distributed random numbers and arrays

Syntax

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, variance , and standard deviation .

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 jth state.
randn('state',sum(100*clock))	Resets it to a different state each time.

Examples

Example 1. 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.

Example 2. Generate a random distribution with a specific mean and variance . To do this, multiply the output of randn by the standard deviation , and then add the desired mean. For example, to generate a 5-by-5 array of random numbers with a mean of .6 that are distributed with a variance of 0.1

x = .6 + sqrt(0.1) * randn(5)
x =

    0.8713    0.4735    0.8114    0.0927    0.7672
    0.9966    0.8182    0.9766    0.6814    0.6694
    0.0960    0.8579    0.2197    0.2659    0.3085
    0.1443    0.8251    0.5937    1.0475   -0.0864
    0.7806    1.0080    0.5504    0.3454    0.5813

See Also

rand, randperm, sprand, sprandn

rand

randperm