Regular Numerical Methods for Inverse and Ill-Posed Problems
Organizer
Corresp. Member of RAS V.V. Vasin
vasin@onzap.imm.intec.ru
Abstract
By an ill-posed problem is usually meant that, in which a "small" disturbance
of initial data causes a "large" perturbation of the result. This is
particularly specific to the problems that are commonly called the inverse
ones.
An important component of them is to use the data to specify or refine
the mathematical model. The theory of inverse and ill-posed problems
is gathering force in the last four decades and is directed
whether at traditional or relatively new applications. Nowadays the right
numerical algorithms and computer simulations play an increasingly
important role in studying the inverse and ill-posed problems.
The Minisymposium aims to discuss new results in theory, software and
applications in various fields of research related to the inverse and
ill-posed problems. The following issues are supposed to be considered:
- general numerical methods of regular approximation for inverse and
ill-posed problems;
- regular numerical methods for solving the inverse problems of control
and observation theory;
- height performance software for computer simulation of inverse and
ill-posed problems;
- specific numerical algorithms of solving the problems arising in
engineering sciences.
Presentations
- V.V. Vasin,
Iterative methods for unstable weakly nonlinear problems
- A.L. Ageev,
Regular algorithms for solving the first kind equations with
finite-dimensional nonlinearity
- V.I. Berdyshev,
Numerical methods of approximation connected with
the navigation problem
- A.I. Grebennikov,
Spline algorithms for data
processing and solving some inverse problems
- A.I. Korotkii,
Restoration of controls in nonlinear evolutionary systems
under uncertainty
- J.M. Marban and C. Palencia,
A new approach
to the numerical solution of parabolic problems backward in time
- Tch. Marinov,
Numerical Identification of Unknown Coefficient in Helmholtz
Equation via Method of Variational Imbedding
- V.A. Morozov,
The generalized sourcewiseness and the error estimates for
regularization of linear and nonlinear problems
- A.V. Nenarokomov, A.F. Emery and T.D. Fadale,
Uncertainties in mathematical models
and inverse problems
- I.F. Sivergina,
On the Input Estimation Problem for PDE:
the Regularized Solutions and Evolutionary Numerical Algorithms