Poisson Noise VI

	initialize? controls the reseeding of the noise sample generator after the first call of the VI. If initialize? is TRUE, accepts a new state or new seed value and begins producing noise samples based on the new state or new seed value. If initialize? is FALSE, this VI maintains the initial internal seed state and resumes producing noise samples as a continuation of the previous noise sequence. The default is TRUE.
	samples specifies the number of samples contained in the output array. samples must be greater than 0. The default is 128.
	mean specifies the interval of a unit rate Poisson process. mean must be greater than or equal to 0. The default is 1.0.
	seed determines how to generate the internal seed state when initialize? is TRUE. If seed is greater than 0, this VI uses seed to generate the internal state directly. If seed is less than or equal to 0, this VI uses a random number to generate the internal state. seed must not be a multiple of 16384. If initialize? is FALSE, this VI ignores seed. The default is -1.
	poisson noise contains the Poisson-distributed, pseudorandom pattern.
	error returns any error or warning from the VI. You can wire error to the Error Cluster From Error Code VI to convert the error code or warning into an error cluster.

Poisson Noise Details

The Poisson Noise VI generates a Poisson-distributed pseudorandom sequence whose values are the number of discrete events that occur in a given interval. The following equation defines the probability density function of the poisson noise:

where is the mean.

The following equations define the mean value, µ, and the standard deviation value, , of the pseudorandom sequence:

µ = E{x} =

= [E{(x – µ)²}]^1/2 =

Poisson noise is the result of the 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.

You can use the initialize? input to generate a long random noise sequence block by block. The following block diagram shows two ways to generate identical 300-sample Poisson noise sequences with a seed of 2.

You also can use the Poisson Noise Waveform VI to generate a Poisson noise signal or the Discrete Random VI to generate random values from a Poisson-distributed variate.