Time series: theory and methods
Time series: theory and methods
Simulation and the Monte Carlo Method
Simulation and the Monte Carlo Method
Handbook of Mathematical Functions, With Formulas, Graphs, and Mathematical Tables,
Handbook of Mathematical Functions, With Formulas, Graphs, and Mathematical Tables,
Intuitive Probability and Random Processes using MATLAB
Intuitive Probability and Random Processes using MATLAB
Coloring Non-Gaussian Sequences
IEEE Transactions on Signal Processing
IEEE Transactions on Information Theory
Hi-index | 35.68 |
A new method for representing and generating realizations of a wide-sense stationary non-Gaussian random process is described. The representation allows one to independently specify the power spectral density and the first-order probability density function of the random process. The only proviso is that the probability density function must be symmetric and infinitely divisible. The method proposed models the sinusoidal component frequencies as random variables, a key departure from the usual representation a of wide-sense stationary random process by the spectral theorem. Ergodicity in the mean and autocorrelation is also proven, under certain conditions. An example is given to illustrate its application to the K distribution, which is important in many physical modeling problems in radar and sonar.