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MA50250: Inverse problems, data assimilation and filtering

[Page last updated: 23 October 2023]

Academic Year: 2023/24
Owning Department/School: Department of Mathematical Sciences
Credits: 6 [equivalent to 12 CATS credits]
Notional Study Hours: 120
Level: Masters UG & PG (FHEQ level 7)
Period:
Semester 2
Assessment Summary: CWRI 100%
Assessment Detail:
  • Coursework 1 (CWRI 40%)
  • Coursework 2 (CWRI 60%)
Supplementary Assessment:
Like-for-like reassessment (where allowed by programme regulations)
Requisites: Before taking this module you must take MA50174 OR take MA50178 OR take MA50281 or equivalent.
Learning Outcomes: By the end of this unit, you will be able to
  • formulate inverse problems and understand the importance of regularisation,
  • construct, analyse, and interpret solutions to inverse problems for a range of applications;
  • apply statistical filtering methods and interpret their solutions.



Aims: To understand inverse problems and their importance in many areas of science, and to develop theoretical and practical understanding of data assimilation, filtering, and regularisation methods for solving inverse problems.

Skills: Problem solving (T, F&A), computing (T, F&A), written and oral communication (F&A).

Content: Inverse problems; ill-posedness and regularisation methods, Tikhonov regularisation and truncated singular value decomposition. Variational regularisation.
Statistical data assimilation and filtering; variational methods (3DVar/4DVar); Kalman filters.
Applications, for example, in medical imaging, meteorology and oceanography.

Course availability:

MA50250 is Optional on the following courses:

Department of Mathematical Sciences

Notes:

  • This unit catalogue is applicable for the 2023/24 academic year only. Students continuing their studies into 2024/25 and beyond should not assume that this unit will be available in future years in the format displayed here for 2023/24.
  • Courses and units are subject to change in accordance with normal University procedures.
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