caa a22 4500 378921185 CHVBK 20180305123605.0 cr unu---uuuuu 161128e20040301xx s 000 0 eng 10.1515/156939604323091216 doi (NATIONALLICENCE)gruyter-10.1515/156939604323091216 White noise and simulation of ordinary Gaussian processes [Elektronische Daten] [Bénédicte Puig, Fabrice Poirion] A generalized process , where E is a nuclear space, is a random variable family such that the map is linear and continuous. The Gaussian white noise process is a well-known example. It is characterized by a Gaussian measure on the dual space E′ of E. Ordinary Gaussian processes can be constructed from the white noise process using the duality relation: where is a family of functions in E. The goal of this paper is to show that all the classical simulation methods of Gaussian processes found in the literature are derived from this construction, by fixing the appropriate nuclear space E and family . Copyright 2004, Walter de Gruyter Puig Bénédicte ONERA, BP72 92322 Chatillon, France aut Poirion Fabrice ONERA, BP72 92322 Chatillon, France aut Monte Carlo Methods and Applications Walter de Gruyter 10/1(2004-03-01), 69-89 0929-9629 10:1<69 2004 10 mcma https://doi.org/10.1515/156939604323091216 text/html Onlinezugriff via DOI 1 research article jats NATIONALLICENCE 856 40 https://doi.org/10.1515/156939604323091216 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Puig Bénédicte ONERA, BP72 92322 Chatillon, France aut NATIONALLICENCE 700 1- Poirion Fabrice ONERA, BP72 92322 Chatillon, France aut NATIONALLICENCE 773 0- Monte Carlo Methods and Applications Walter de Gruyter 10/1(2004-03-01), 69-89 0929-9629 10:1<69 2004 10 mcma CC0 http://creativecommons.org/publicdomain/zero/1.0 nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-gruyter