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Convergence to the solution of the linear system with real quadrate non singular matrix A with real necessary different sign eigen values of two families of simple iteration method: two-parametric and symmetrized one-parametric generated by these A and b is considered. Also these methods are compared when matrix A is a symmetric one. In this case it is proved that the coefficient of the optimal compression of two-parametric family is strongly less than the coefficient of the optimal compression of symmetrized one-parametric family of the simple iteration method.

We consider integration Clein–Gordon and Dirac equations in Bianchi IX cosmology model. Using the noncommutative integration method we found the new exact solutions for Taub universe.

Noncommutative integration method for Bianchi IX model is based on the use of the special infinite-dimensional holomorphic representation of the rotation group, which is based on the nondegenerate orbit adjoint representation, and complex polarization of degenerate covector. The matrix elements of the representation of form a complete and orthogonal set and allow you to use the generalized Fourier transform. Casimir operator for rotation group under this transformation becomes constant. And the symmetry operators generated by the Killing vector fields in the linear differential operators of the first order from one dependent variable. Thus, the relativistic wave equation on the rotation group allow non-commutative reduction to ordinary differential equations. In contrast to the well-known method of separation of variables, noncommutative integration method takes into account the non-Abelian algebra of symmetry operators and provides solutions that carry information about the non-commutative symmetry of the task. Such solutions can be useful for measuring the vacuum quantum effects and the calculation of the Green’s functions by the splitting-point method.

The work for the Taub model compared the solutions obtained with the known, which are obtained by separation of variables. It is shown that the non-commutative solutions are expressed in terms of elementary functions, while the known solutions are defined by the Wigner function. And commutative reduced by the Klein–Gordon equation for Taub model coincides with the equation, reduced by separation of variables. A commutative reduced by the Dirac equation is equivalent to the reduced equation obtained by separation of variables.

Currently, different nonlinear numerical schemes of the spatial approximation are used in numerical simulation of boundary value problems for hyperbolic systems of partial differential equations (e. g. gas dynamics equations, MHD, deformable rigid body, etc.). This is due to the need to improve the order of accuracy and perform simulation of discontinuous solutions that are often occurring in such systems. The need for non-linear schemes is followed from the barrier theorem of S. K. Godunov that states the impossibility of constructing a linear scheme for monotone approximation of such equations with approximation order two or greater. One of the most accurate non-linear type schemes are ENO (essentially non oscillating) and their modifications, including WENO (weighted, essentially non oscillating) scemes. The last received the most widespread, since the same stencil width has a higher order of approximation than the ENO scheme. The benefit of ENO and WENO schemes is the ability to maintain a high-order approximation to the areas of non-monotonic solutions. The main difficulty of the analysis of such schemes comes from the fact that they themselves are nonlinear and are used to approximate the nonlinear equations. In particular, the linear stability condition was obtained earlier only for WENO5 scheme (fifth-order approximation on smooth solutions) and it is a numerical one. In this paper we consider the problem of construction and stability for WENO5, WENO7, WENO9, WENO11, and WENO13 finite volume schemes for the Hopf equation. In the first part of this article we discuss WENO methods in general, and give the explicit expressions for the coefficients of the polynomial weights and linear combinations required to build these schemes. We prove a series of assertions that can make conclusions about the order of approximation depending on the type of local solutions. Stability analysis is carried out on the basis of the principle of frozen coefficients. The cases of a smooth and discontinuous behavior of solutions in the field of linearization with frozen coefficients on the faces of the final volume and spectra of the schemes are analyzed for these cases. We prove the linear stability conditions for a variety of Runge-Kutta methods applied to WENO schemes. As a result, our research provides guidance on choosing the best possible stability parameter, which has the smallest effect on the nonlinear properties of the schemes. The convergence of the schemes is followed from the analysis.

We study polynomial solutions of gyrostat motion equations under potential and gyroscopic forces applied and of gyrostat motion equations in magnetic field taking into account Barnett–London effect. Mathematically, either of the above mentioned problems is described by a system of non-linear ordinary differential equations whose right hand sides contain fifteen constant parameters. These parameters characterize the gyrostat mass distribution, as well as potential and non-potential forces acting on gyrostat. We consider polynomial solutions of Steklov–Kovalevski–Gorjachev and Doshkevich classes. The structure of invariant relations for polynomial solutions shows that, as a rule, on top of the fifteen parameters mentioned one should add no less than twenty five problem parameters. In the process of solving such a multi-parametric problem in this paper we (in addition to analytic approach) apply numeric methods based on CAS. We break our studies of polynomial solutions existence into two steps. During the first step, we estimate maximal degrees of polynomials considered and obtain a non-linear algebraic system for parameters of differential equations and polynomial solutions. In the second step (using the above CAS software) we study the solvability conditions of the system obtained and investigate the conditions of the constructed solutions to be real.

We construct two new polynomial solutions for Kirchhoff–Poisson. The first one is described by the following property: the projection squares of angular velocity on the non-baracentric axes are the fifth degree polynomials of the angular velocity vector component of the baracentric axis that is represented via hypereliptic function of time. The second solution is characterized by the following: the first component of velocity conditions is a second degree polynomial, the second component is a polynomial of the third degree, and the square of the third component is the sixth degree polynomial of the auxiliary variable that is an inversion of the elliptic Legendre integral.

The third new partial solution we construct for gyrostat motion equations in the magnetic field with Barnett–London effect. Its structure is the following: the first and the second components of the angular velocity vector are the second degree polynomials, and the square of the third component is a fourth degree polynomial of the auxiliary variable which is found via inversion of the elliptic Legendre integral of the third kind.

All the solutions constructed in this paper are new and do not have analogues in the fixed point dynamics of a rigid body.

The paper describes a free software for research in the field of holomorphic dynamics based on the computational capabilities of the MATLAB environment. The software allows constructing not only single complex-valued mappings, but also their collectives as linearly connected, on a square or hexagonal lattice. In the first case, analogs of the Julia set (in the form of escaping points with color indication of the escape velocity), Fatou (with chaotic dynamics highlighting), and the Mandelbrot set generated by one of two free parameters are constructed. In the second case, only the dynamics of a cellular automaton with a complex-valued state of the cells and of all the coefficients in the local transition function is considered. The abstract nature of object-oriented programming makes it possible to combine both types of calculations within a single program that describes the iterated dynamics of one object.

The presented software provides a set of options for the field shape, initial conditions, neighborhood template, and boundary cells neighborhood features. The mapping display type can be specified by a regular expression for the MATLAB interpreter. This paper provides some UML diagrams, a short introduction to the user interface, and some examples.

The following cases are considered as example illustrations containing new scientific knowledge:

1) a linear fractional mapping in the form $Az^{n} +B/z^{n} $, for which the cases $n=2$, $4$, $n>1$, are known. In the portrait of the Fatou set, attention is drawn to the characteristic (for the classical quadratic mapping) figures of <>, showing short-period regimes, components of conventionally chaotic dynamics in the sea;

2) for the Mandelbrot set with a non-standard position of the parameter in the exponent $z(t+1)\Leftarrow z(t)^{\mu } $ sketch calculations reveal some jagged structures and point clouds resembling Cantor's dust, which are not Cantor's bouquets that are characteristic for exponential mapping. Further detailing of these objects with complex topology is required.

Multi-label classification models arise in various areas of life, which is explained by an increasing amount of information that requires prompt analysis. One of the mathematical methods for solving this problem is a plug-in approach, at the first stage of which, for each class, a certain ranking function is built, ordering all objects in some way, and at the second stage, the optimal thresholds are selected, the objects on one side of which are assigned to the current class, and on the other — to the other. Thresholds are chosen to maximize the target quality measure. The algorithms which properties are investigated in this article are devoted to the second stage of the plug-in approach which is the choice of the optimal threshold vector. This step becomes non-trivial if the $F$-measure of average precision and recall is used as the target quality assessment since it does not allow independent threshold optimization in each class. In problems of extreme multi-label classification, the number of classes can reach hundreds of thousands, so the original optimization problem is reduced to the problem of searching a fixed point of a specially introduced transformation $\boldsymbol V$, defined on a unit square on the plane of average precision $P$ and recall $R$. Using this transformation, two algorithms are proposed for optimization: the $F$-measure linearization method and the method of $\boldsymbol V$ domain analysis. The properties of algorithms are studied when applied to multi-label classification data sets of various sizes and origin, in particular, the dependence of the error on the number of classes, on the $F$-measure parameter, and on the internal parameters of methods under study. The peculiarity of both algorithms work when used for problems with the domain of $\boldsymbol V$, containing large linear boundaries, was found. In case when the optimal point is located in the vicinity of these boundaries, the errors of both methods do not decrease with an increase in the number of classes. In this case, the linearization method quite accurately determines the argument of the optimal point, while the method of $\boldsymbol V$ domain analysis — the polar radius.

A direct algorithm for solving a linear programming problem (LP), given in canonical form, is considered. The algorithm consists of two successive stages, in which the following LP problems are solved by a direct method: a non-degenerate auxiliary problem at the first stage and some problem equivalent to the original one at the second. The construction of the auxiliary problem is based on a multiplicative version of the Gaussian exclusion method, in the very structure of which there are possibilities: identification of incompatibility and linear dependence of constraints; identification of variables whose optimal values are obviously zero; the actual exclusion of direct variables and the reduction of the dimension of the space in which the solution of the original problem is determined. In the process of actual exclusion of variables, the algorithm generates a sequence of multipliers, the main rows of which form a matrix of constraints of the auxiliary problem, and the possibility of minimizing the filling of the main rows of multipliers is inherent in the very structure of direct methods. At the same time, there is no need to transfer information (basis, plan and optimal value of the objective function) to the second stage of the algorithm and apply one of the ways to eliminate looping to guarantee final convergence.

Two variants of the algorithm for solving the auxiliary problem in conjugate canonical form are presented. The first one is based on its solution by a direct algorithm in terms of the simplex method, and the second one is based on solving a problem dual to it by the simplex method. It is shown that both variants of the algorithm for the same initial data (inputs) generate the same sequence of points: the basic solution and the current dual solution of the vector of row estimates. Hence, it is concluded that the direct algorithm is an algorithm of the simplex method type. It is also shown that the comparison of numerical schemes leads to the conclusion that the direct algorithm allows to reduce, according to the cubic law, the number of arithmetic operations necessary to solve the auxiliary problem, compared with the simplex method. An estimate of the number of iterations is given.

A set of implicit difference schemes on the five-pointwise stensil is under construction. The analysis of properties of difference schemes is carried out in a space of undetermined coefficients. The spaces were introduced for the first time by A. S. Kholodov. Usually for properties of difference schemes investigation the problem of the linear programming was constructed. The coefficient at the main term of a discrepancy was considered as the target function. The optimization task with inequalities type restrictions was considered for construction of the monotonic difference schemes. The limitation of such an approach becomes clear taking into account that approximation of the difference scheme is defined only on the classical (smooth) solutions of partial differential equations.

The functional which minimum will be found put in compliance to the difference scheme. The functional must be the linear on the difference schemes coefficients. It is possible that the functional depends on net function – the solution of a difference task or a grid projection of the differential problem solution. If the initial terms of the functional expansion in a Taylor series on grid parameters are equal to conditions of classical approximation, we will call that the functional will be the generalized condition of approximation. It is shown that such functionals exist. For the simple linear partial differential equation with constant coefficients construction of the functional is possible also for the generalized (non-smooth) solution of a differential problem.

Families of functionals both for smooth solutions of an initial differential problem and for the generalized solution are constructed. The new difference schemes based on the analysis of the functionals by linear programming methods are constructed. At the same time the research of couple of self-dual problems of the linear programming is used. The optimum monotonic difference scheme possessing the first order of approximation on the smooth solution of differential problem is found. The possibility of application of the new schemes for creation of hybrid difference methods of the raised approximation order on smooth solutions is discussed.

The example of numerical implementation of the simplest difference scheme with the generalized approximation is given.

The localization of a vehicle is an important task in the field of intelligent transportation systems. It is well known that sensor fusion helps to create more robust and accurate systems for autonomous vehicles. Standard approaches, like extended Kalman Filter or Particle Filter, are inefficient in case of highly non-linear data or have high computational cost, which complicates using them in embedded systems. Significant increase of precision, especially in case when GPS (Global Positioning System) is unavailable, may be achieved by using landmarks with known location — such as traffic signs, traffic lights, or SLAM (Simultaneous Localization and Mapping) features. However, this approach may be inapplicable if a priori locations are unknown or not accurate enough. We suggest a new approach for refining coordinates of a vehicle by using landmarks, such as traffic signs. Core part of the suggested system is the Bayesian framework, which refines vehicle location using external data about the previous traffic signs detections, collected with crowdsourcing. This paper presents an approach that combines trajectories built using global coordinates from GPS and relative coordinates from Inertial Measurement Unit (IMU) to produce a vehicle's trajectory in an unknown environment. In addition, we collected a new dataset, including from smartphone GPS and IMU sensors, video feed from windshield camera, which were recorded during 4 car rides on the same route. Also, we collected precise location data from Real Time Kinematic Global Navigation Satellite System (RTK-GNSS) device, which can be used for validation. This RTK-GNSS system was used to collect precise data about the traffic signs locations on the route as well. The results show that the Bayesian approach helps with the trajectory correction and gives better estimations with the increase of the amount of the prior information. The suggested method is efficient and requires, apart from the GPS/IMU measurements, only information about the vehicle locations during previous traffic signs detections.