Index-> contents reference index search Up-> SPT_HELP SignalGeneratorMain awgn Prev Next SPT_HELP-> SPTFunctionsByCategory Mathematical Functions Data Manipulation Functions SignalGeneratorMain AnalogFilterFunctions FIR Filter Design Window Functions IIR Filter Design FourierFunctions Plotting Functions Histogram Functions SignalGeneratorMain-> binbits nrzbits awgn cawgn ammod pmmod fmmod quadmod sinwave triwave sawwave sqrwave RandNumGens OtherSigGen awgn Headings-> Description Example

 Syntax `y = awgn(`mean,sigma`)` Syntax `y = awgn(`mean,sigma,Nrows`)` Syntax `y = awgn(`mean,sigma,Nrows,Mcols`)` Include: `include spt\awgn.oms` See Also cawgn
``` ARGUMENTS:      INPUTS:       mean  = SCALAR, any numerical type. Mean value of               requested noise distribution. Coerced to               DOUBLE before local processing.       sigma = SCALAR, any numerical type. Standard               deviation of requested noise distribution.               Equivalent to the RMS value of the noise.               Coerced to DOUBLE before local               processing.       Nrows = SCALAR, any numerical type. Number of rows               in returned matrix. Coerced to INTEGER               before local processing.         Ncols = SCALAR, any numerical type. Number of               columns in returned matrix. Coerced to               'integer' before local processing.      RETURN: MATRIX, type 'double', Nrows X Mcols matrix of AWGN. ```
Description ``` ```Creates a matrix of discrete samples of ADDITIVE WHITE GAUSSIAN NOISE (AWGN) with specified 'mean' and standard deviation 'sigma'. ``` ```This function returns discrete independent identically distributed samples of the normally (gaussian) distributed random variable. The result has a user-defined mean and standard deviation. ``` ```Example
Create a single sample, a vector of 6 samples, and a 6x5 array of samples of additive white Gaussian noise. ``` O>awgn(0,1) -0.26  O>awgn(0,1,6) { -0.65 -0.35  0.67  1.07  0.38 -0.47 } O>awgn(0,1,6,5) { [  1.19 ,  0.87 ,  2.46 ,  0.77 ,  0.06 ] [  1.57 , -0.38 , -0.99 ,  0.95 ,  0.20 ] [ -0.41 ,  0.09 ,  0.65 , -1.02 ,  1.59 ] [ -0.70 , -1.12 , -0.22 , -1.54 ,  0.43 ] [ -0.82 , -0.03 ,  1.17 ,  0.46 , -1.46 ] [  0.61 ,  0.48 , -0.28 ,  0.92 ,  1.59 ] } ```