Vol 93, No 2 (2016)

An approach for constructing a complete system of formulas for the analytic continuation of the Lauricella generalized hypergeometric function F_D^(N) with any N beyond the boundary of the unit polydisk is proposed. The approach is exposed in detail for the continuation of the function under consideration in neighborhoods of points whose all N components equal 1 or ∞. For the Lauricella function, differential relations being analogues of Jacobi’s formula for the Gaussian hypergeometric function are also presented. The results can be applied to solve the crowding problem for the Schwarz–Christoffel integral and to the theory of the Riemann–Hilbert problem.

We address the homogenization of a variational inequality posed in perforated media issue from a unilateral problem for the p-Laplacian. We consider the n-Laplace operator in a perforated domain of ℝⁿ, n ≥ 3, with restrictions for the solution and its flux (the flux associated with the n-Laplacian) on the boundary of the perforations which are assumed to be isoperimetric. The solution is assumed to be positive on the boundary of the holes and the flux is bounded from above by a negative, nonlinear monotone function multiplied by a large parameter. A certain non periodical distribution of the perforations is allowed while the assumption that their size is much smaller than the periodicity scale is performed. We make it clear that in the average constants of the problem, the perimeter of the perforations appears for any shape.

New first-order methods are introduced for solving convex optimization problems from a fairly broad class. For composite optimization problems with an inexact stochastic oracle, a stochastic intermediate gradient method is proposed that allows using an arbitrary norm in the space of variables and a prox-function. The mean rate of convergence of this method and the probability of large deviations from this rate are estimated. For problems with a strongly convex objective function, a modification of this method is proposed and its rate of convergence is estimated. The resulting estimates coincide, up to a multiplicative constant, with lower complexity bounds for the class of composite optimization problems with an inexact stochastic oracle and for all usually considered subclasses of this class.

The classical semiparametric Bernstein–von Mises (BvM) results is reconsidered in a non-classical setup allowing finite samples and model misspecication. We obtain an upper bound on the error of Gaussian approximation of the posterior distribution for the target parameter which is explicit in the dimension of the target parameter and in the dimension of sieve approximation of the nuisance parameter. This helps to identify the so called critical dimension p_n of the sieve approximation of the full parameter for which the BvM result is applicable. If the bias induced by sieve approximation is small and dimension of sieve approximation is smaller then critical dimension than the BvM result is valid. In the important i.i.d. and regression cases, we show that the condition “p_n²q/n is small”, where q is the dimension of the target parameter and n is the sample size, leads to the BvM result under general assumptions on the model.

Algebraic polynomials bounded in absolute value by M > 0 in the interval [–1, 1] and taking a fixed value A at a > 1 are considered. The extremal problem of finding such a polynomial taking a maximum possible value at a given point b < −1 is solved. The existence and uniqueness of an extremal polynomial and its independence of the point b < −1 are proved. A characteristic property of the extremal polynomial is determined, which is the presence of an n-point alternance formed by means of active constraints. The dependence of the alternance pattern, the objective function, and the leading coefficient on the parameter A is investigated. A correspondence between the extremal polynomials in the problem under consideration and the Zolotarev polynomials is established.

New conditions for minimality, maximality, and nonmaximality of deficiency numbers of the minimal operator generated by the infinite Jacobi matrix with m × m matrix entries in the Hilbert space of mdimensional vectors are presented. Special attention is given to the case m = 1, i.e., to conditions on the elements of a tridiagonal numerical Jacobi matrix under which the determinate case of the classical power moment problem is realized.

A singularly perturbed elliptic convection–diffusion equation with a perturbation parameter ε (ε ∈ (0, 1]) is considered on a rectangle. As applied to this equation, a standard finite difference scheme on a uniform grid is studied under computer perturbations. This scheme is not ε-uniformly stable with respect to perturbations. The conditions imposed on a “computing system” are established under which a converging standard scheme (referred to as a computer difference scheme) remains stable.

A relationship between invariants of four-dimensional singularities of integrable Hamiltonian systems (with two degrees of freedom) and invariants of two-dimensional foliations on three-dimensional manifolds being the “boundaries” of these four-dimensional singularities is discovered. Nonequivalent singularities which, nevertheless, have equal three-dimensional invariants are found.

The relations between the necessary minimum conditions in an optimal control problem (Pontryagin maximum principle), the minimum conditions in the corresponding relaxation (weakened) problem, and sufficient conditions for the local controllability of the controlled system specifying the constraints in the original formulation are studied. An abstract optimization problem that models the basic properties of the optimal control problem is considered.

In this paper we study the behavior of concentration functions of weighted sums of independent random variables with respect to the arithmetic structure of coefficients. Recently, Tao and Vu formulated a so-called Inverse Principle in the Littlewood–Offord problem. We discuss the relations between this Inverse Principle and a similar principle formulated for sums of arbitrarily distributed independent random variables formulated by T. Arak in the 1980’s.

Hopf’s well-known conjecture is considered, which states that there exists no metric of strictly positive curvature on the topological product S² × S² of two 2-spheres. Three theorems are proved.

The eigenvalue problem generated by the Sturm–Liouville equation on the interval (0, π) with degenerate boundary conditions is considered. Under certain conditions imposed on the spectrum, it is shown that the system of eigen- and associated functions is not a basis in L₂(0, π).

The concept of a composite electromagnetic field in multilayered magnetodielectric (MD) systems is introduced. The concept is based on an “algebraic” description of plane electromagnetic fields relying on the phase approach [1], which is useful in optimizing film covers and solving inverse problems for MD systems [4–6].

An approach to the implementation of a recommender system based on ontologies of mathematical knowledge is presented. On the basis of a document browsed by a user, the system forms on line a list of recommendations, which include similar documents, key words, and definitions of these words from ontology and other terminological sources. The method of recommendations yields a vector representation of documents, taking into account the position of terms in the logical structure of the document and their ontological connections. On the basis of the cosine measure, a measure of proximity between documents is calculated. The order of documents in the list of recommendations is determined by values of the proximity measure. Various adaptations of the system to user scenarios aimed at the preparation of personalized recommendations are discussed.

A model of a discrete-time system with multiplicative noise is considered. For this model, a condition is derived under which the anisotropic norm of the system is bounded by the anisotropic norm of an auxiliary linear discrete-time stationary system with parametric uncertainty. Conditions for the anisotropic norm of the system with multiplicative noise to be bounded by a given positive number are obtained in terms of solutions of linear matrix inequalities and a single equation.