In this paper we construct optimal, in certain sense, estimates of values of
linear functionals on solutions to two-point boundary value problems (BVPs) for
systems of linear first-order ordinary differential equations from observations
which are linear transformations of the same solutions perturbed by additive
random noises. It is assumed here that right-hand sides of equations and
boundary data as well as statistical characteristics of random noises in
observations are not known and belong to certain given sets in corresponding
functional spaces.
The creation and justification of the methods for minimax estimation of
parameters of the external boundary value problems for the Helmholtz equation
in unbounded domains are considered. When observations are distributed in
subdomains, the determination of minimax estimates is reduced to the solution
of integro-differential equations in bounded domains. When observations are
distributed on a system of surfaces the problem is reduced to solving integral
equations on an unclosed bounded surface which is a union of the boundary of
the domain and this system of surfaces.
The creation and justification of the methods for minimax estimation of
parameters of the external boundary value problems for the Helmholtz equation
in unbounded domains are considered. When observations are distributed in
subdomains, the determination of minimax estimates is reduced to the solution
of integro-differential equations in bounded domains. When observations are
distributed on a system of surfaces the problem is reduced to solving integral
equations on an unclosed bounded surface which is a union of the boundary of
the domain and this system of surfaces.