Developed Algorithm for Supervising Identification of Non Linear Systems Using Higher Order Statistics: Modeling Internet Traffic
In this paper, the authors use the formulas of statistic techniques for developing an algorithm based on third order moments and autocorrelation function. This algorithm permits to identify non linear system coefficients for recovering the real information from input-output systems. Simulation examples and comparison with other method in the literature are provided to verify the performance of the developed algorithm. The obtained results demonstrate the efficiency and the accuracy of the developed algorithm for non linear system identification under various values of Signal to Noise Ratio (SNR) and different sample sizes N. To corroborate the theoretical results for a real process, they applied the developed algorithm to search a model able to represent the internet traffic data.