Gaussian white noise generator based on improved ziggurat algorithm

There exists nonlinear operations in judging the wedge and tail regions of the classical ziggurat algorithm, which is complicated and resource consuming. An improved ziggurat algorithm is proposed towards this problem. The improved algorithm optimizes the accepting model by piecewise linear fitting, including the wedge and tail regions, changes the algorithm into linear operations. The new algorithm is efficient with more than a 44% decrease of resource comsumption and has no significant performance deterioration, which is confirmed by simulation. An implementation of Gaussian white noise generator based on the improved algorithm is given; simulation and experiment results show that the generator has a high efficiency of resource consuming and data throughput rate. The generated Gaussian white noise has the good characteristics of normal distribution and smooth power spectrum.