Generation of pseudo random processes with given marginal distribution and autocorrelation function

Abstract

In this paper a new algorithm for generating a random process with a given marginal distri- bution and autocorrelation function is presented. By using the truncated distribution instead of the order statistics used in the earlier algorithm, the proposed algorithm achieves signiiScant speed up and accuracy. We also develop a scheme for deciding the transition probability matrix based on the Newton optimization technique, that is one of the key steps in the proposed algo-rithm. The experiment for 16 state randomized Markov chain shows about 14 times accelera-tion in comparison with the earher algorithm. The storage requirement is also much smaller.

Keywords:

• Autocorrelation
• Newton Optimization
• Random Process
• Randomized Markov Chain
• Simulation

C.R. Categories:

• G.3
• I.6

^*This work was supported in part by BK21 project and grant No. 2000-2-30300-004-3 from the Basic Research Program of Korea Science and Engineering Foundation

^‡[email protected]

^§[email protected]

^*This work was supported in part by BK21 project and grant No. 2000-2-30300-004-3 from the Basic Research Program of Korea Science and Engineering Foundation

^‡[email protected]

^§[email protected]

Notes

^*This work was supported in part by BK21 project and grant No. 2000-2-30300-004-3 from the Basic Research Program of Korea Science and Engineering Foundation

^‡[email protected]

^§[email protected]