Abstract
Differential algebras of generalized stochastic processes are constructed, which contain irregular processes as e. g. white noise. Solutions to nonlinear stochastic differential equations are obtained in these algebras. The methods extend the nonlinear theories of generalized functions as developed by J. F. Colombeau, Yu. V. Egorov, E. E. Rosinger to the stochastic setting. Both an approach based on regularized sample paths as well as on sequences of smooth L 0-valued functions are presented.
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Oberguggenberger, M. (1995). Generalized Functions and Stochastic Processes. In: Bolthausen, E., Dozzi, M., Russo, F. (eds) Seminar on Stochastic Analysis, Random Fields and Applications. Progress in Probability, vol 36. Birkhäuser, Basel. https://doi.org/10.1007/978-3-0348-7026-9_16
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DOI: https://doi.org/10.1007/978-3-0348-7026-9_16
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