normrnd和randn中均适用于生成正态分布的随机数，区别在于normrnd可以自己指定均值MU和方差sigma。而randn生成的是标准的正态分布(即MU=0,sigma=1)。

R = normrnd(mu,sigma) generates random numbers from the normal distribution with mean parameter mu and standard deviation parameter sigma. mu and sigma can be vectors, matrices, or multidimensional arrays that have the same size, which is also the size of R. A scalar input for mu or sigma is expanded to a constant array with the same dimensions as the other input.

R = normrnd(mu,sigma,m,n,…) or R = normrnd(mu,sigma,[m,n,…]) generates an m-by-n-by-… array. The mu, sigma parameters can each be scalars or arrays of the same size as R.

Description example X = randn returns a random scalar drawn from the standard normal distribution. example X = randn(n) returns an n-by-n matrix of normally distributed random numbers. example X = randn(sz1,…,szN) returns an sz1-by-…-by-szN array of random numbers where sz1,…,szN indicate the size of each dimension. For example, randn(3,4) returns a 3-by-4 matrix. example X = randn(sz) returns an array of random numbers where size vector sz defines size(X). For example, randn([3 4]) returns a 3-by-4 matrix. example X = randn(_,typename) returns an array of random numbers of data type typename. The typename input can be either ‘single’ or ‘double’. You can use any of the input arguments in the previous syntaxes. example X = randn(_,’like’,p) returns an array of random numbers like p; that is, of the same object type as p. You can specify either typename or ‘like’, but not both. Note: The ‘seed’, ‘state’, and ‘twister’ inputs to the randn function are not recommended. Use the rng function instead. For more information, see Replace Discouraged Syntaxes of rand and randn.