Process Simulation Using Randomized Markov Chain and Truncated Marginal Distribution
The Journal of Supercomputing - Special issue on computational issues in fluid dynamics optimization and simulation
Efficient Random Process Generation for Reliable Simulation of Complex Systems
ICCS '01 Proceedings of the International Conference on Computational Science-Part II
| Hi-index | 0.00 |
Often random processes with a given probability den-sity function (pdf) and a given power spectrum are desired. Usually, a discrete-time linear system is used to shape the power spectrum of an i.i.d. excitation process in the desired manner, but there does not exist a solution to simultaneously adjust the output pdf. In this paper a method is introduced to adjust the pdf at the output of a given linear system to al-most any desired shape by computing the required pdf of the excitation process, which can easily be shaped by a mem-oryless nonlinear system without any impact on the power spectrum. The method is based on Hermite polynomials to obtain an approximation of the pdf, cumulants to describe the effect of the linear system on the pdf, and a combina-torial algorithm to compute the Hermitian coefficients from cumulants, and vice versa. A numerical example gives evi-dence of the practical applicability.