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.

Computer-aided simulations of Gaussian processes and related asymptotic properties.

DI NARDO, Elvira;
2001

Abstract

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.
Computer Aided Systems Theory - EUROCAST 2001
Las Palmas de Gran Canaria, Spain
February 19-23, 2001
Computer Aided Systems Theory - EUROCAST 2001 - Revised selected papers
Springer Verlag Germany:Tiergartenstrasse 17, D 69121 Heidelberg Germany:011 49 6221 3450, EMAIL: g.braun@springer.de, INTERNET: http://www.springer.de, Fax: 011 49 6221 345229
2178
67
78
9783540429593
http://www.springerlink.com/content/wae3tnmcu67mrfl5/
DI NARDO, Elvira; Nobile, A. G.; Pirozzi, E.; Ricciardi, L. M.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/2318/1561372
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