# Noise Generator (Binomial) (G Dataflow)

Version:

Generates a binomially-distributed pseudorandom pattern whose values are the number of occurrences of an event given the probability of that event occurring and the number of trials.

## reset

A Boolean that controls the reseeding of the noise sample generator after the first execution of the node. By default, this node maintains the initial internal seed state.

 True Accepts a new seed and begins producing noise samples based on the seed. If the given seed is less than or equal to 0, the node ignores a reset value of True and resumes producing noise samples as a continuation of the previous sequence. False Resumes producing noise samples as a continuation of the previous noise sequence. The node ignores new seed inputs while reset is False.

Default: False

## trials

The number of trials performed for each element of the output signal.

Default: 1

## trial probability

The probability that a given trial is true (1).

trial probability must be in the range [0, 1].

Default: 0.5

## seed

A number that initializes the noise generator.

The value of seed cannot be a multiple of 16364. If reset is unwired, this node maintains the internal seed state.

 seed is greater than 0 Generates noise samples based on the given seed value. For multiple calls to the node, the node accepts or rejects new seed inputs based on the given reset value. seed is less than or equal to 0 Generates a random seed value and produces noise samples based on that seed value. For multiple calls to the node, if seed remains less than or equal to 0, the node ignores the reset input 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.

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.

Default: The default value of this input changes depending on how you configure this node. If you configure this node to return a waveform, the default is 1000. If you configure this node to return an array of double-precision, floating-point numbers, the default is 128.

## binomial noise

Binomially-distributed, pseudorandom pattern.

This output returns a waveform or an array of double-precision, floating point numbers.

## error out

Error information. The node produces this output according to standard error behavior.

## Algorithm for Generating the Binomial Noise

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

$P\left(X=i\right)=\left(\begin{array}{c}n\\ i\end{array}\right){p}^{i}{\left(1-p\right)}^{n-i}\text{\hspace{0.17em}}\text{\hspace{0.17em}}\text{\hspace{0.17em}}\text{\hspace{0.17em}}\text{\hspace{0.17em}}\text{\hspace{0.17em}}\left(i=0,\text{\hspace{0.17em}}1,\text{\hspace{0.17em}}...,\text{\hspace{0.17em}}n\right)\text{\hspace{0.17em}}$

where

• n is trials
• p is trial probability
• $\left(\begin{array}{c}n\\ i\end{array}\right)$ equals $\frac{n!}{\left(n-i\right)!i!}$

To generalize, P(X = i) is the probability that i of the n trials equals 1 and n - i equals zero.

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

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

Where This Node Can Run:

Desktop OS: Windows

FPGA: Not supported