A parallel algorithm is implemented to simulate sample paths of stationary normal processes possessing a Butterworth-type covariance, in order to investigate asymptotic properties of the first passage time probability densities for time-varying boundaries. After a self-contained outline of the simulation procedure, computational results are included to show that for large times and for large boundaries the first passage time probability density through an asymptotically periodic boundary is exponentially distributed to an excellent degree of approximation. © 2011 Springer-Verlag Berlin Heidelberg.
CITATION STYLE
Di Nardo, E., Nobile, A. G., Pirozzi, E., & Ricciardi, L. M. (2001). Computer-aided simulations of gaussian processes and related asymptotic properties. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 2178 LNCS, pp. 67–78). Springer Verlag. https://doi.org/10.1007/3-540-45654-6_6
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