Generation and validation of Gaussian noise using random sequence
Thottempudi Pardhu, Usha Rani Nelakuditi, Suresh Pampana · 2014
In general many real time problems are represented with random variables. But a random variable is characterized by a Probability Density Function(PDF). As per the Central Limit Theorem any stochastic process handled with many random variables can be converged as a normal distribution. Hence normal distribution plays a key role in modeling real time problems contains many random variables. This paper dealt with the generation of Gaussian PDF using uniform random sequence. The generated PDF is validated in LABVIEW.