第二部門：計算力学（A)

[S02A-05] Simulation of a Normal Stochastic Process with a Long Correlation Distance

*Tadanobu SATO¹ (1. Kyoto University)

Keywords:normal stochastic process, correlation distance, covariance metrix

A stochastic process is defined by its correlation coefficient and probability density function. For the case that the stochastic characteristic is defend by normal distribution and if the covariance matrix is Cholesky decomposable or Eigenvalue decomposable the stochastic process can be expressed by a weighting sum of iid random number generated from the standard normal distribution, N(0,1). But for the case that the correlation distance becomes long the decomposition of covariance matrix becomes unstable, therefore the simulation of stochastic process using usual methods is unrealistic. The main purpose of this paper is to develop a simple algorithm for simulating the stochastic process with a long correlation distance