On the Moment Problem and Related Problems

Firstly, we recall the classical moment problem and some basic results related to it. By its formulation, this is an inverse problem: being given a sequence (yj)j∈ℕn of real numbers and a closed subset F⊆ℝn, n∈{1,2,…}, find a positive regular Borel measure μ on F such that ∫Ftjdμ=yj, j∈ℕn. This is the full moment problem. The existence, uniqueness, and construction of the unknown solution μ are the focus of attention. The numbers yj, j∈ℕn are called the moments of the measure μ. When a sandwich condition on the solution is required, we have a Markov moment problem. Secondly, we study the existence and uniqueness of the solutions to some full Markov moment problems. If the moments yj are self-adjoint operators, we have an operator-valued moment problem. Related results are the subject of attention. The truncated moment problem is also discussed, constituting the third aim of this work.

Approximating Solutions of Non-Linear Troesch’s Problem via an Efficient Quasi-Linearization Bessel Approach

Two collocation-based methods utilizing the novel Bessel polynomials (with positive coefficients) are developed for solving the non-linear Troesch’s problem. In the first approach, by expressing the unknown solution and its second derivative in terms of the Bessel matrix form along with some collocation points, the governing equation transforms into a non-linear algebraic matrix equation. In the second approach, the technique of quasi-linearization is first employed to linearize the model problem and, then, the first collocation method is applied to the sequence of linearized equations iteratively. In the latter approach, we require to solve a linear algebraic matrix equation in each iteration. Moreover, the error analysis of the Bessel series solution is established. In the end, numerical simulations and computational results are provided to illustrate the utility and applicability of the presented collocation approaches. Numerical comparisons with some existing available methods are performed to validate our results.

Investigation on the Aha-Experience as an Indicator of Correct Solutions in Functional Analysis in Engineering Design

The functional analysis of technical systems is an important part of the design process. To further improve the design process, especially the functional analysis, it must not be viewed as a monodisciplinary process. To this end, cognitive factors such as the aha-experience must also be included in studies of analysis processes to a greater extent. This paper investigates the relationship between the occurrence of aha-experiences and the correctness of solutions in the analysis of a technical system. An aha-experience is a strong feeling of subjective certainty that accompanies the cognitive process of suddenly finding a previously unknown solution. For this purpose, a study on the functional analysis was evaluated. The results show that many identified subfunctions of the system under investigation were identified with an aha-experience and that these subfunctions are more often correct. The results also suggest that aha-experiences occur more often among students than among experienced design engineers. Especially among students, a positive relation of aha-experiences on the correctness of the identified subfunction can be seen. This offers potential for further investigations to make aha-experiences useful in design methods.

Strong Solutions of Stochastic Differential Equations with Generalized Drift and Multidimensional Fractional Brownian Initial Noise

In this paper, we prove the existence of strong solutions to an stochastic differential equation with a generalized drift driven by a multidimensional fractional Brownian motion for small Hurst parameters $$H<\frac{1}{2}.$$ H < 1 2 . Here, the generalized drift is given as the local time of the unknown solution process, which can be considered an extension of the concept of a skew Brownian motion to the case of fractional Brownian motion. Our approach for the construction of strong solutions is new and relies on techniques from Malliavin calculus combined with a “local time variational calculus” argument.

Existence of a solution of discrete Emden-Fowler equation caused by continuous equation

<p style='text-indent:20px;'>The paper studies the asymptotic behaviour of solutions to a second-order non-linear discrete equation of Emden–Fowler type</p><p style='text-indent:20px;'><disp-formula> <label/> <tex-math id="FE1"> \begin{document}$ \Delta^2 u(k) \pm k^\alpha u^m(k) = 0 $\end{document} </tex-math></disp-formula></p><p style='text-indent:20px;'>where <inline-formula><tex-math id="M1">\begin{document}$ u\colon \{k_0, k_0+1, \dots\}\to \mathbb{R} $\end{document}</tex-math></inline-formula> is an unknown solution, <inline-formula><tex-math id="M2">\begin{document}$ \Delta^2 u(k) $\end{document}</tex-math></inline-formula> is its second-order forward difference, <inline-formula><tex-math id="M3">\begin{document}$ k_0 $\end{document}</tex-math></inline-formula> is a fixed integer and <inline-formula><tex-math id="M4">\begin{document}$ \alpha $\end{document}</tex-math></inline-formula>, <inline-formula><tex-math id="M5">\begin{document}$ m $\end{document}</tex-math></inline-formula> are real numbers, <inline-formula><tex-math id="M6">\begin{document}$ m\not = 0, 1 $\end{document}</tex-math></inline-formula>.</p>

THE INFLUENCE OF SOCIAL INNOVATION ON THE COMPETITIVENESS OF THE NATIONAL ECONOMY

The relationship between innovation and competitiveness results from several factors conditioning the emergence of a new, previously unknown solution to a problem, process, the appearance of a new product, or other facilities considered on a global scale, e.g. improving the functioning of the state.

Новый численный метод решения нелинейных стохастических интегральных уравнений

The purpose of this paper is to propose the Chebyshev cardinal functions for solving Volterra stochastic integral equations. The method is based on expanding the required approximate solution as the element of Chebyshev cardinal functions. Though the way, a new operational matrix of integration is derived for the mentioned basis functions. More precisely, the unknown solution is expanded in terms of the Chebyshev cardinal functions including undetermined coefficients. By substituting the mentioned expansion in the original problem, the operational matrix reducing the stochastic integral equation to system of algebraic equations. The convergence and error analysis of the etablished method are investigated in Sobolev space. The method is numerically evaluated by solving test problems caught from the literature by which the computational efficiency of the method is demonstrated. From the computational point of view, the solution obtained by this method is in excellent agreement with those obtained by other works and it is efficient to use for different problems.

Well-posedness and numerical approximation of a fractional diffusion equation with a nonlinear variable order

We prove well-posedness and regularity of solutions to a fractional diffusion porous media equation with a variable order that may depend on the unknown solution. We present a linearly implicit time-stepping method to linearize and discretize the equation in time, and present rigorous analysis for the convergence of numerical solutions based on proved regularity results.

The Reduced-Order Extrapolating Method about the Crank-Nicolson Finite Element Solution Coefficient Vectors for Parabolic Type Equation

This study is mainly concerned with the reduced-order extrapolating technique about the unknown solution coefficient vectors in the Crank-Nicolson finite element (CNFE) method for the parabolic type partial differential equation (PDE). For this purpose, the CNFE method and the existence, stability, and error estimates about the CNFE solutions for the parabolic type PDE are first derived. Next, a reduced-order extrapolating CNFE (ROECNFE) model in matrix-form is established with a proper orthogonal decomposition (POD) method, and the existence, stability, and error estimates of the ROECNFE solutions are proved by matrix theory, resulting in an graceful theoretical development. Specially, our study exposes that the ROECNFE method has the same basis functions and the same accuracy as the CNFE method. Lastly, some numeric tests are shown to computationally verify the validity and correctness about the ROECNFE method.

Regularity properties of the stochastic flow of a skew fractional Brownian motion

In this paper we prove, for small Hurst parameters, the higher-order differentiability of a stochastic flow associated with a stochastic differential equation driven by an additive multi-dimensional fractional Brownian noise, where the bounded variation part is given by the local time of the unknown solution process. The proof of this result relies on Fourier analysis-based variational calculus techniques and on intrinsic properties of the fractional Brownian motion.