## Documentation Center |

The Gaussian Noise Generator block generates discrete-time white
Gaussian noise. You must specify the **Initial seed** vector
in the simulation.

The **Mean Value** and the **Variance** can
be either scalars or vectors. If either of these is a scalar, then
the block applies the same value to each element of a sample-based
output or each column of a frame-based output. Individual elements
or columns, respectively, are uncorrelated with each other.

When the **Variance** is a vector, its length
must be the same as that of the **Initial seed** vector.
In this case, the covariance matrix is a diagonal matrix whose diagonal
elements come from the **Variance** vector. Since
the off-diagonal elements are zero, the output Gaussian random variables
are uncorrelated.

When the **Variance** is a square matrix, it
represents the covariance matrix. Its off-diagonal elements are the
correlations between pairs of output Gaussian random variables. In
this case, the **Variance** matrix must be positive
definite, and it must be `N`-by-`N`,
where `N` is the length of the **Initial
seed**.

The probability density function of *n*-dimensional
Gaussian noise is

where *x* is a length-*n* vector, *K* is
the *n*-by-*n* covariance matrix,
µ is the mean value vector, and the superscript *T* indicates
matrix transpose.

The **Initial seed** parameter initializes
the random number generator that the Gaussian Noise Generator block
uses to add noise to the input signal. For best results, the **Initial
seed** should be a prime number greater than 30. Also, if
there are other blocks in a model that have an **Initial seed** parameter,
you should choose different initial seeds for all such blocks.

You can choose seeds for the Gaussian Noise Generator block using the Communications System Toolbox™ randseed function. At the MATLAB prompt, enter

randseed

This returns a random prime number greater than 30. Entering `randseed` again
produces a different prime number. If you supply an integer argument, `randseed` always
returns the same prime for that integer. For example, `randseed(5)` always
returns the same answer.

The output signal can be a frame-based matrix, a sample-based
row or column vector, or a sample-based one-dimensional array. These
attributes are controlled by the **Frame-based outputs**, **Samples
per frame**, and **Interpret vector parameters as
1-D** parameters. See Sources and Sinks in the *Communications System Toolbox User's
Guide* for more details.

If the **Initial seed** parameter is a vector,
then its length becomes the number of columns in a frame-based output
or the number of elements in a sample-based vector output. In this
case, the shape (row or column) of the **Initial seed** parameter
becomes the shape of a sample-based two-dimensional output signal.
If the **Initial seed** parameter is a scalar but
either the **Mean value** or **Variance** parameter
is a vector, then the vector length determines the output attributes
mentioned above.

**Mean value**The mean value of the random variable output.

**Variance**The covariance among the output random variables.

**Initial seed**The initial seed value for the random number generator.

**Sample time**The period of each sample-based vector or each row of a frame-based matrix.

**Frame-based outputs**Determines whether the output is frame-based or sample-based. This box is active only if

**Interpret vector parameters as 1-D**is unchecked.**Samples per frame**The number of samples in each column of a frame-based output signal. This field is active only if

**Frame-based outputs**is checked.**Interpret vector parameters as 1-D**If this box is checked, then the output is a one-dimensional signal. Otherwise, the output is a two-dimensional signal. This box is active only if

**Frame-based outputs**is unchecked.**Output data type**The output can be set to

`double`or`single`data types.

Random Source (DSP System Toolbox™ documentation), AWGN Channel, `rand` (built-in
MATLAB function), randseed

Was this topic helpful?