Accessibility navigation


Data-driven modeling for wave-propagation

van Leeuwen, T., Van Leeuwen, P. J. and Zhuk, S. (2020) Data-driven modeling for wave-propagation. In: Numerical Mathematics and Advanced Applications ENUMATH 2019, 30 Sept- 4 Oct 2019, Egmond aan Zee, The Netherlands, pp. 683-691, https://doi.org/10.1007/978-3-030-55874-1_67.

[img] Text - Accepted Version
· Restricted to Repository staff only until 22 August 2022.

272kB

It is advisable to refer to the publisher's version if you intend to cite from this work. See Guidance on citing.

To link to this item DOI: 10.1007/978-3-030-55874-1_67

Abstract/Summary

Many imaging modalities, such as ultrasound and radar, rely heavily on the ability to accurately model wave propagation. In most applications, the response of an object to an incident wave is recorded and the goal is to characterize the object in terms of its physical parameters (e.g., density or soundspeed). We can cast this as a joint parameter and state estimation problem. In particular, we consider the case where the inner problem of estimating the state is a weakly constrained dataassimilation problem. In this paper, we discuss a numerical method for solving this variational problem.

Item Type:Conference or Workshop Item (Paper)
Refereed:Yes
Divisions:Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology
ID Code:99534
Publisher:Springer

University Staff: Request a correction | Centaur Editors: Update this record

Page navigation