Ill-Posed Problems Research Group

Our research group studies regularization methods for solving ill-posed problems and rules for choosing the regularization parameter. Ill-posed problems are problems, solutions of which are unstable under data perturbations. Typical examples of such problems are integral equations of the first kind. To reduce the influence of data perturbations (for example, measurement errors) in the approximate solution, it is essential to control the stability of the algorithm by proper choice of the regularization parameter.

Members

• Uno Hämarik (Associate Professor emeritus, Visiting Research Fellow of Institute of Mathematics and Statistics)
• Toomas Raus (Associate Professor emeritus, Visiting Research Fellow of Institute of Mathematics and Statistics)
• Urve Kangro (Associate Professor of Institute of Mathematics and Statistics)
• Reimo Palm (Lecturer of Institute of Computer Science)
• Gennadi Vainikko (Professor Emeritus of Institute of Mathematics and Statistics, Academician of Estonian Academy of Science)