Wolfram Language & System 11.0 (2016)|Legacy Documentation
represents a Gaussian white noise process with mean 0 and standard deviation 1.
represents a Gaussian white noise process with mean 0 and standard deviation σ.
represents a white noise process based on the distribution dist.
- WhiteNoiseProcess is also known as independent identically distributed (iid) process.
- WhiteNoiseProcess is a discrete-time random process.
- The slices of WhiteNoiseProcess are assumed to be independent and identically distributed random variables.
- The distribution dist can be any univariate distribution with mean 0 and finite variance.
- WhiteNoiseProcess can be used with such functions as Mean, PDF, Probability, and RandomFunction.