randn

MATLAB의 내장함수인 randn은 각 항이 평균0과 분산1의 정규분포를 갖는 랜덤 수나 행렬을 생성한다.

RANDN Normally distributed pseudorandom numbers.     R = RANDN(N) returns an N-by-N matrix containing pseudorandom values drawn     from the standard normal distribution.  RANDN(M,N) or RANDN([M,N]) returns     an M-by-N matrix. RANDN(M,N,P,...) or RANDN([M,N,P,...]) returns an     M-by-N-by-P-by-... array. RANDN returns a scalar.  RANDN(SIZE(A)) returns     an array the same size as A.       Note: The size inputs M, N, P, ... should be nonnegative integers.     Negative integers are treated as 0.       R = RANDN(..., 'double') or R = RANDN(..., 'single') returns an array of     normal values of the specified class.       Compatibility Note: In versions of MATLAB prior to 7.7, you controlled     the internal state of the random number stream used by RANDN by calling     RANDN directly with the 'seed' or 'state' keywords.  That syntax is     still supported for backwards compatibility, but is deprecated. Beginning     in MATLAB 7.7, use the default stream as described in RANDSTREAM.       The sequence of numbers produced by RANDN is determined by the internal     state of the uniform pseudorandom number generator that underlies RAND,     RANDI, and RANDN.  RANDN uses one or more uniform values from that     default stream to generate each normal value.  Control the default     stream using its properties and methods.  See RANDSTREAM for details     about the default stream.       Resetting the default stream to the same fixed state allows computations     to be repeated.  Setting the stream to different states leads to unique     computations, however, it does not improve any statistical properties.     Since MATLAB uses the same state each time it starts up, RAND, RANDN, and     RANDI will generate the same sequence of numbers in each session unless     the state is changed.       Examples:          Generate values from a normal distribution with mean 1 and standard        deviation 2.           r = 1 + 2.*randn(100,1);          Generate values from a bivariate normal distribution with specified mean        vector and covariance matrix.           mu = [1 2];           Sigma = [1 .5; .5 2]; R = chol(Sigma);           z = repmat(mu,100,1) + randn(100,2)*R;          Save the current state of the default stream, generate 5 values,        restore the state, and repeat the sequence.           defaultStream = RandStream.getDefaultStream;           savedState = defaultStream.State;           z1 = randn(1,5)           defaultStream.State = savedState;           z2 = randn(1,5) % contains exactly the same values as z1          Replace the default stream with a stream whose seed is based on CLOCK, so        RANDN will return different values in different MATLAB sessions.  NOTE: It        is usually not desirable to do this more than once per MATLAB session.           RandStream.setDefaultStream(RandStream('mt19937ar','seed',sum(100*clock)));           randn(1,5)

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