Fast Simulation of Additive Generalized Gaussian Noise Environments

摘要

Due to the complexity and associated inordinate computing time required to generate generalized Gaussian random variates, it is necessary to find faster ways to simulate events caused by additive generalized Gaussian noise. Following a concise review of the two known exact methods of generating generalized Gaussian random variates, an exact weighted counting approach is investigated for rapid estimation of the probability of events caused by the presence of additive generalized Gaussian noise. The weighted counting method reduces simulation times typically by 10(4) times, and will allow simulation of complex systems not previously feasible.