Wiener process

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Wiener process

[′vē·nər ‚prä·səs]
(mathematics)
A stochastic process with normal density at each stage, arising from the study of Brownian motion, which represents the limit of a sequence of experiments. Also known as Gaussian noise.
References in periodicals archive ?
It describes preliminary results on covariance and associated RKHS, the Gaussian process, the definition of multiple Wiener integrals for a general Gaussian process and stochastic integration for Gaussian random fields, Skorokhod and Malliavin derivatives for Gaussian random fields, filtering with general Gaussian noise, equivalence and singularity, and the Markov property of Gaussian fields and Dirichlet forms.