CAAM 499 - Section 2
Data Assimilation
Fall 2005

links

General Information

About this Course

Data assimilation refers to the reconciliation of the dynamical model of a physical process with measurements and arises in a variety of applications including weather forecasting and process control. Typically, data assimilation leads to a class of inverse or parameter estimation problems in which one wants to determine parameters in a dynamical model, given by partial or ordinary differential equations, from observations.

Data Assimilation arises in meteorology and oceanography, but also in the parameter estimation for chemical and other processes. Recently data assimilation has also become an interesting topic in the design and application of sensor networks.

This course presents the mathematical background required for the numerical solution of data assimilation problems and applies the numerical methods developed to selected processes, such as the evolution of the temperature inside a building or the determination of the location of a hazardous substance.

This course assumes basic knowledge in linear algebra, differential equations, and Matlab (as taught in, e.g., CAAM 335 or 336 or 353). Additional background material will be provided as needed.

For a listing of topics see the lectures-page.

Time and Room

Organizational meeting: Thursday, August 25, 4pm in DH2014

Instructor

Matthias Heinkenschloss
Office: Duncan Hall 3088
Phone: x5176
Office Hours: Stop by my office, or make an appointment (e-mail preferred)
E-mail:heinken AT rice.edu

Note on Disability Based Accommodations

If you have a documented disability that will impact your work in this class, please contact me to discuss your needs. Additionally, you will need to register with the Disability Support Services Office in the Ley Student Center.

This web page is located at http://www.caam.rice.edu/~caam499-2 and maintained by Matthias Heinkenschloss.