Note: This page has been translated by MathWorks. Click here to see

To view all translated materials including this page, select Country from the country navigator on the bottom of this page.

To view all translated materials including this page, select Country from the country navigator on the bottom of this page.

Generate Bernoulli-distributed random binary numbers

Random Data Sources sublibrary of Comm Sources

The Bernoulli Binary Generator block generates random binary numbers using a
Bernoulli distribution. The Bernoulli distribution with parameter p produces
zero with probability p and one with probability 1-p. The Bernoulli
distribution has mean value 1-p and variance p(1-p). The
**Probability of a zero** parameter specifies p,
and can be any real number between zero and one.

The output signal can be a column or row vector, a two-dimensional
matrix, or a scalar. The number of rows in the output signal
corresponds to the number of samples in one frame and is determined
by the **Samples per frame** parameter. The number
of columns in the output signal corresponds to the number of
channels and is determined by the number of elements in the
**Probability of a zero** parameter. See
Sources and Sinks in
*Communications
Toolbox™ User's Guide* for more
details.

**Probability of a zero**The probability with which a zero output occurs. Specify the probability as a scalar or row vector whose elements are real numbers between 0 and 1. The number of elements in the

**Probability of a zero**parameter correspond to the number of independent channels output from the block.**Source of initial seed**The source of the initial seed for the random number generator. Specify the source as either

`Auto`

or`Parameter`

. When set to`Auto`

, the block uses the global random number stream.### Note

When

**Source of initial seed**is`Auto`

in`Code generation`

mode, the random number generator uses an initial seed of zero. Therefore, the block generates the same random numbers each time it is started. Use`Interpreted execution`

to ensure that the model uses different initial seeds. If`Interpreted execution`

is run in`Rapid accelerator`

mode, then it behaves the same as`Code generation`

mode.**Initial seed**The initial seed value for the random number generator. Specify the seed as a nonnegative integer scalar.

**Initial seed**is available when the**Source of initial seed**parameter is set to`Parameter`

.**Sample time**The time between each sample of a column of the output signal.

**Samples per frame**The number of samples per frame in one channel of the output signal. Specify

**Samples per frame**as a positive integer scalar.### Note

The time between output updates is equal to the product of

**Samples per frame**and**Sample time**. For example, if**Sample time**and**Samples per frame**equal one, the block outputs a binary sample every second. If**Samples per frame**is increased to 10, then a 10-by-1 vector is output every 10 seconds. This ensures that the equivalent output rate is not dependent on the**Samples per frame**parameter.**Output data type**The output type of the block can be specified as a

`boolean`

,`uint8`

,`uint16`

,`uint32`

,`single`

, or`double`

. The default is`double`

.**Simulate using**Select the simulation mode.

`Code generation`

On the first model run, simulate and generate code. If the structure of the block does not change, subsequent model runs do not regenerate the code.

If the simulation mode is

`Code generation`

, System objects corresponding to the blocks accept a maximum of nine inputs.`Interpreted execution`

Simulate model without generating code. This option results in faster start times but can slow subsequent simulation performance.