We prove the existence of solutions to the Kuramoto–Sivashinsky equation with low regularity data in function spaces based on the Wiener algebra and in pseudomeasure spaces. In any spatial dimension, we allow the data to have its antiderivative in the Wiener algebra. In one spatial dimension, we also allow data that are in a pseudomeasure space of negative order. In two spatial dimensions, we also allow data that are in a pseudomeasure space one derivative more regular than in the one-dimensional case. In the course of carrying out the existence arguments, we show a parabolic gain of regularity of the solutions as compared to the data. Subsequently, we show that the solutions are in fact analytic at any positive time in the interval of existence.
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Stochastic linear-quadratic optimal control problems — Recent developments
In this paper, we present a brief survey for some recent developments of stochastic linear-quadratic optimal controls. We mainly concentrate on the results obtained by the authors and their collaborators in the last decay.
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- Award ID(s):
- 2305475
- PAR ID:
- 10499996
- Publisher / Repository:
- Elsevier
- Date Published:
- Journal Name:
- Annual Reviews in Control
- Volume:
- 56
- Issue:
- C
- ISSN:
- 1367-5788
- Page Range / eLocation ID:
- 100899
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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