Images of Gaussian and other stochastic processes under closed, densely-defined, unbounded linear operators
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Publication:6496340
DOI10.1142/S0219530524400025WikidataQ129694962 ScholiaQ129694962MaRDI QIDQ6496340
Tadashi Matsumoto, Thomas J. Sullivan
Publication date: 3 May 2024
Published in: Analysis and Applications (Singapore) (Search for Journal in Brave)
Gaussian processunbounded operatorclosed operatorBochner integralHille's theoremdensely-defined operator
Gaussian processes (60G15) General second-order stochastic processes (60G12) Vector-valued measures and integration (46G10) Operators on Banach spaces (47B01)
Cites Work
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- Boundary value problems for elliptic partial differential operators on bounded domains
- Perturbation theory for linear operators.
- Solving differential equations with radial basis functions: Multilevel methods and smoothing
- Regularity of the sample paths of a general second order random field
- Sur une propriété de la loi de Gauss
- On reproducing kernel Banach spaces: generic definitions and unified framework of constructions
- Some Divergent Trigonometric Integrals
- Necessary and Sufficient Conditions for Differentiating under the Integral Sign
- Numerical Gaussian Processes for Time-Dependent and Nonlinear Partial Differential Equations
- Approximation of stochastic partial differential equations by a kernel-based collocation method
- Probabilistic Numerics
- Bayesian Probabilistic Numerical Methods in Time-Dependent State Estimation for Industrial Hydrocyclone Equipment
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