# Noise Generator (Poisson) (G Dataflow)

Version:

Generates a pseudorandom sequence of values that are the number of discrete events that occur in a specific interval of a unit rate Poisson process.

You can use the Poisson process to describe the probability of a certain number of events happening in a given period of time. For example, you can use the Poisson process to describe the nuclear decay of atoms and the number of messages a transmitting station receives.

## reset

A Boolean that controls the reseeding of the noise sample generator after the first call of the node.

 True Accepts a new state or new seed value and begins producing noise samples based on the new state or new seed value. False Maintains the initial internal seed state and resumes producing noise samples as a continuation of the previous noise sequence.

Default: False

## mean

Interval of a unit rate Poisson process. mean must be greater than or equal to 0.

Default: 1

## state in

Initial internal seed state of the noise generator.

This input must be passed from the state out output of another call to this node.

This node uses state in as the initial internal seed state of the noise generator if reset is True or if this is the first call of the node. If state in is unwired or contains invalid values, this nodes uses seed as the initial internal seed state of the noise generator.

### x seed

Internal x seed. x seed must be greater than 0.

### y seed

Internal y seed. y seed must be greater than 0.

### z seed

Internal z seed. z seed must be greater than 0.

## seed

Number that this node uses to initialize the noise generator.

This node initializes the noise generator using seed when this node meets both of the following conditions:

• This is the first call of this node or reset is True.
• state in is unwired or contains invalid values.
 seed is greater than 0 Generates noise samples based on the seed value. seed is less than or equal to 0 For the first call, this node generates a random seed value and produces noise samples based on that seed value. For subsequent calls to the node, if seed remains less than or equal to 0, the node maintains the initial internal seed state and produces noise samples as a continuation of the initial noise sequence.

Default: -1

## error in

Error conditions that occur before this node runs.

The node responds to this input according to standard error behavior.

Standard Error Behavior

Many nodes provide an error in input and an error out output so that the node can respond to and communicate errors that occur while code is running. The value of error in specifies whether an error occurred before the node runs. Most nodes respond to values of error in in a standard, predictable way.

error in does not contain an error error in contains an error
If no error occurred before the node runs, the node begins execution normally.

If no error occurs while the node runs, it returns no error. If an error does occur while the node runs, it returns that error information as error out.

If an error occurred before the node runs, the node does not execute. Instead, it returns the error in value as error out.

Default: No error

## sample rate

Sample rate in samples per second.

This input is available only if you configure this node to return a waveform.

Default: 1000

## samples

Number of samples in the signal.

samples must be greater than 0. Otherwise, this node returns an error.

This input is available when you configure this node to return a waveform or an array of double-precision, floating-point numbers.

Default: 1000

## t0

Timestamp of the output signal. If this input is unwired, this node uses the current time as the timestamp of the output signal.

This input is available only if you configure this node to return a waveform.

## Poisson noise

Poisson-distributed, pseudorandom pattern.

This output can return the following data types:

• Waveform
• Double-precision, floating-point number
• 1D array of double-precision, floating-point numbers

## state out

Final internal seed state of the noise generator.

Internal x seed.

Internal y seed.

Internal z seed.

## error out

Error information.

The node produces this output according to standard error behavior.

Standard Error Behavior

Many nodes provide an error in input and an error out output so that the node can respond to and communicate errors that occur while code is running. The value of error in specifies whether an error occurred before the node runs. Most nodes respond to values of error in in a standard, predictable way.

error in does not contain an error error in contains an error
If no error occurred before the node runs, the node begins execution normally.

If no error occurs while the node runs, it returns no error. If an error does occur while the node runs, it returns that error information as error out.

If an error occurred before the node runs, the node does not execute. Instead, it returns the error in value as error out.

## Algorithm for Generating the Poisson Noise

The following equation defines the probability density function of the Poisson noise this node generates:

$P\left(X=n\right)={e}^{-\lambda }\frac{{\lambda }^{n}}{n!}\text{\hspace{0.17em}}\text{\hspace{0.17em}}\text{\hspace{0.17em}}\text{\hspace{0.17em}}\text{\hspace{0.17em}}\text{\hspace{0.17em}}\left(n=0,\text{\hspace{0.17em}}1,\text{\hspace{0.17em}}...\right)\text{\hspace{0.17em}}$

where $\lambda$ is mean.

The following equations define the mean value, $\mu$, and the standard deviation value, $\sigma$, of the pseudorandom sequence:

$\mu =E\left\{x\right\}=\lambda$
$\sigma ={\left[E\left\{{\left(x-\mu \right)}^{2}\right\}\right]}^{1/2}=\sqrt{\lambda }$

Where This Node Can Run:

Desktop OS: Windows

FPGA: Not supported

Web Server: Not supported in VIs that run in a web application