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Non-Symmetric Ornstein-Uhlenbeck Processes in Banach Space Via Dirichlet Forms

Published online by Cambridge University Press:  20 November 2018

Byron Schmuland
Affiliation:
Department of Statistics and Applied Probability University of Alberta Edmonton, Alberta T6G 2G1
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Abstract

We use recent advances in the theory of non-symmetric Dirichlet forms to study a class of Banach space valued Ornstein-Uhlenbeck processes. As an example, we look at Walsh's stochastic model of neural response and show that it is a continuous process in any Sobolev space Hα(α < ½), and that it takes values only among functions with unbounded variation.

Type
Research Article
Copyright
Copyright © Canadian Mathematical Society 1993

References

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