Могилянський математичний журнал
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науково-дослiдних робiт, теоретичних дослiджень учених, науково-педагогiчних працiвникiв, аспiрантiв, магiстрiв i
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Тематичне розмаїття статей охоплює iсторiю математики, виклад результатiв теоретичних дослiджень з математики
i статистики, а також їх застосувань. Засновник (1996 р.) i видавець журналу - Нацiональний унiверситет "Києво-Могилянська академiя"
Виходив як частина багатосерiйного видання "Науковi записки НаУКМА" ("Фiзико-математичнi науки")
З 2018 р. - окреме видання, що має назву "Могилянський математичний журнал"
(англ. "Mohyla Mathematical Journal")
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- ItemA solution of a finitely dimensional Harrington problem for Cantor set(2022) Kusinski, SlawomirIn this paper we are exploring application of fusion lemma - a result about perfect trees, having its origin in forcing theory - to some special cases of a problem proposed by Leo Harrington in a book Analytic Sets. In all generality the problem ask whether given a sequence of functions from Rω to [0; 1] one can find a subsequence of it that is pointwise convergent on a product of perfect subsets of R. We restrict our attention mainly to binary functions on the Cantor set as well as outline the possible direction of generalization of result to other topological spaces and different notions of measurablity.
- ItemAbout the approximate solutions to linear and non-linear pseudodifferential reaction diffusion equations(2019) Drin, Yaroslav; Ushenko, Yuri; Drin, Iryna; Drin, SvitlanaBackground. The concept of fractal is one of the main paradigms of modern theoretical and experimental physics, radiophysics and radar, and fractional calculus is the mathematical basis of fractal physics, geothermal energy and space electrodynamics. We investigate the solvability of the Cauchy problem for linear and nonlinear inhomogeneous pseudodifferential diffusion equations. The equation contains a fractional derivative of a Riemann–Liouville time variable defined by Caputo and a pseudodifferential operator that acts on spatial variables and is constructed in a homogeneous, non-negative homogeneous order, a non-smooth character at the origin, smooth enough outside. The heterogeneity of the equation depends on the temporal and spatial variables and permits the Laplace transform of the temporal variable. The initial condition contains a restricted function. Objective. To show that the homotopy perturbation transform method (HPTM) is easily applied to linear and nonlinear inhomogeneous pseudodifferential diffusion equations. To prove the solvability and obtain the solution formula for the Cauchy problem series for the given linear and nonlinear diffusion equations. Methods. The problem is solved by the NPTM method, which combines a Laplace transform with a time variable and a homotopy perturbation method (HPM). After the Laplace transform, we obtain an integral equation which is solved as a series by degrees of the entered parameter with unknown coefficients. Substituting the input formula for the solution into the integral equation, we equate the expressions to equal parameter degrees and obtain formulas for unknown coefficients. When solving the nonlinear equation, we use a special polynomial which is included in the decomposition coefficients of the nonlinear function and allows the homotopy perturbation method to be applied as well for nonlinear non-uniform pseudodifferential diffusion equation. Results. The result is a solution of the Cauchy problem for the investigated diffusion equation, which is represented as a series of terms whose functions are found from the parametric series. Conclusions. In this paper we first prove the solvability and obtain the formula for solving the Cauchy problem as a series for linear and nonlinear inhomogeneous pseudodifferential equations
- ItemComputing the Moore-Penrose inverse for bidiagonal matrices(2019) Hakopian, YuriThe Moore-Penrose inverse is the most popular type of matrix generalized inverses which has many applications both in matrix theory and numerical linear algebra. It is well known that the Moore-Penrose inverse can be found via singular value decomposition. In this regard, there is the most effective algorithm which consists of two stages. In the first stage, through the use of the Householder reflections, an initial matrix is reduced to the upper bidiagonal form (the Golub-Kahan bidiagonalization algorithm). The second stage is known in scientific literature as the Golub-Reinsch algorithm. This is an iterative procedure which with the help of the Givens rotations generates a sequence of bidiagonal matrices converging to a diagonal form. This allows to obtain an iterative approximation to the singular value decomposition of the bidiagonal matrix. The principal intention of the present paper is to develop a method which can be considered as an alternative to the Golub-Reinsch iterative algorithm. Realizing the approach proposed in the study, the following two main results have been achieved. First, we obtain explicit expressions for the entries of the Moore-Penrose inverse of bidigonal matrices. Secondly, based on the closed form formulas, we get a finite recursive numerical algorithm of optimal computational complexity. Thus, we can compute the Moore-Penrose inverse of bidiagonal matrices without using the singular value decomposition.
- ItemDiameter Search Algorithms for Directed Cayley Graphs(2021-05) Olshevskyi, MaksymIt is considered a well known diameter search problem for finite groups. It can be formulated as follows: find the maximum possible diameter of the group over its system of generators. The diameter of a group over a specific system of generators is the diameter of the corresponding Cayley graph. In the paper a closely related problem is considered. For a specific system of generators find the diameter of corresponding Cayley graph. It is shown that the last problem is polynomially reduced to the problem of searching the minimal decomposition of elements over a system of generators. It is proposed five algorithms to solve the diameter search problem: simple down search algorithm, fast down search algorithm, middle down search algorithms, homogeneous down search algorithm and homogeneous middle down search algorithm.
- ItemA discrete regularization method for hidden Markov models embedded into reproducing kernel Hilbert space(2018) Kriukova, GalynaHidden Markov models are a well-known probabilistic graphical model for time series of discrete, partially observable stochastic processes. We consider the method to extend the application of hidden Markov models to non-Gaussian continuous distributions by embedding a priori probability distribution of the state space into reproducing kernel Hilbert space. Corresponding regularization techniques are proposed to reduce the tendency to overfitting and computational complexity of the algorithm, i.e. Nystr¨om subsampling and the general regularization family for inversion of feature and kernel matrices. This method may be applied to various statistical inference and learning problems, including classification, prediction, identification, segmentation, and as an online algorithm it may be used for dynamic data mining and data stream mining. We investigate, both theoretically and empirically, the regularization and approximation bounds of the discrete regularization method. Furthermore, we discuss applications of the method to real-world problems, comparing the approach to several state-of-the-art algorithms.
- ItemGeneralization of cross-entropy loss function for image classification(2020) Andreieva, Valeria; Shvai, NadiyaClassification task is one of the most common tasks in machine learning. This supervised learning problem consists in assigning each input to one of a finite number of discrete categories. Classification task appears naturally in numerous applications, such as medical image processing, speech recognition, maintenance systems, accident detection, autonomous driving etc. In the last decade methods of deep learning have proven to be extremely efficient in multiple machine learning problems, including classification. Whereas the neural network architecture might depend a lot on data type and restrictions posed by the nature of the problem (for example, real-time applications), the process of its training (i.e. finding model’s parameters) is almost always presented as loss function optimization problem. Cross-entropy is a loss function often used for multiclass classification problems, as it allows to achieve high accuracy results. Here we propose to use a generalized version of this loss based on Renyi divergence and entropy. We remark that in case of binary labels proposed generalization is reduced to cross-entropy, thus we work in the context of soft labels. Specifically, we consider a problem of image classification being solved by application of convolution neural networks with mixup regularizer. The latter expands the training set by taking convex combination of pairs of data samples and corresponding labels. Consequently, labels are no longer binary (corresponding to single class), but have a form of vector of probabilities. In such settings cross-entropy and proposed generalization with Renyi divergence and entropy are distinct, and their comparison makes sense. To measure effectiveness of the proposed loss function we consider image classification problem on benchmark CIFAR-10 dataset. This dataset consists of 60000 images belonging to 10 classes, where images are color and have the size of 32 x 32. Training set consists of 50000 images, and the test set contains 10000 images. For the convolution neural network, we follow [1] where the same classification task was studied with respect to different loss functions and consider the same neural network architecture in order to obtain comparable results. Experiments demonstrate superiority of the proposed method over cross-entropy for loss function parameter value a < 1. For parameter value a > 1 proposed method shows worse results than crossentropy loss function. Finally, parameter value a = 1 corresponds to cross-entropy.
- ItemǬ-зображення дiйсних чисел як узагальнення канторiвських систем числення(2022) Працьовитий, Микола; Бондаренко, Ольга; Ратушняк, Софія; Франчук, КатеринаРоботу присвячено узагальненню канторівської системи числення, яка визначається послідовністю основ( sn), 1 < sn ∈ N і послідовністю алфавітів An = {0, 1, ..., sn − 1}: [0; 1] ∋ x = ∞∑ n=1 αn / s1s2...sn, αn ∈ An, яке назване Ǭ-зображенням. Воно визначається нескінченною матрицею ||qik||, де i ∈ Ai, k ∈ N, що має властивості 0 < qik < 1, mk ∑ i=0 qik = 1, k ∈ N, ∞∏ n=1 max i {qik} = 0, а саме [0; 1] ∋ x = ai11 + ∞∑ k=2 [aikk k−1 ∏ j=1 qij (x)j ] ≡ Δi1i2...ik..., where ainn = in−1 ∑ j=0 qjn, in ∈ An, n ∈ N. У роботі розглянуто застосування вказаного зображення чисел у метричній теорії чисел, теорії розподілів випадкових величин, теорії локально складних функцій та фрактальному аналізі. Вивчено тополого-метричну структуру множини C[Ǭ; Vn] = {x : x = Δα1...αn..., αn ∈ Vn ⊂ An}. Виведено формулу для обчислення її міри Лебега: λ(C) = ∞∏ n=1 λ(Fn) / λ(Fn−1) = ∞∏ n=1 (1 − λ(Fn) / λ(Fn−1)), де F0 = [0; 1], Fn - об'єднання Ǭ-циліндрів рангу n, серед внутрішніх точок яких є точки множини C, Fn ≡ Fn−1 \ Fn. Знайдено критерій і деякі достатні умови нуль-мірності цієї множини. За додаткових умов на "матрицю" ||qik|| знайдено нормальну властивість Ǭ-зображення чисел (властивість, яку мають майже всі у розумінні міри Лебега числа). Отримані результати використано для встановлення лебегівської структури і типу розподілу випадкової величини, Ǭ-зображення якої є незалежними випадковими величинами. Доведено, що цифри Ǭ-зображення рівномірно розподіленої на [0; 1] випадкової величини є незалежними, і вказано їх розподіл. Доведено, що при обчисленні фрактальної розмірності Гаусдорфа Безиковича підмножин відрізка [0; 1] можна обмежитись покриттями Ǭ-циліндрами: Δc1...cm = {x : x = Deltac1...cki1...in..., in ∈ ∈ Ak+n}, якщо потужності алфавітів обмежені, а елементи "матриці" ||qik|| відокремлені від нуля. Для інферсора цифр Ǭ-зображення чисел, тобто функції, означеної рівністю I(x = = Δi1...in...) = Δ[m1−i1]...[mn−in]..., mn ≡ sn − 1 доведено неперервність, строгу монотонність, а для окремих випадків її сингулярність (рівність похідної нулю майже скрізь у розумінні міри Лебега).
- ItemRegularization by Denoising for Inverse Problems in Imaging(2022) Kravchuk, Oleg; Kriukova, GalynaIn this work, a generalized scheme of regularization of inverse problems is considered, where a priori knowledge about the smoothness of the solution is given by means of some self-adjoint operator in the solution space. The formulation of the problem is considered, namely, in addition to the main inverse problem, an additional problem is defined, in which the solution is the right-hand side of the equation. Thus, for the regularization of the main inverse problem, an additional inverse problem is used, which brings information about the smoothness of the solution to the initial problem. This formulation of the problem makes it possible to use operators of high complexity for regularization of inverse problems, which is an urgent need in modern machine learning problems, in particular, in image processing problems. The paper examines the approximation error of the solution of the initial problem using an additional problem.
- ItemRemarks on my algebraic problem of determining similarities between certain quotient boolean algebras(2022) Frankiewicz, RyszardRemarks on my algebraic problem of determining similarities between certain quotient boolean algebras. In this paper we survey results about quotient boolean algebras of type P(κ)/fin(κ) and condition for them to be or not to be isomorphic for different cardinals к. Our consideration have their root in the classical result of Parovicenko and a less classical, nevertheless really considerable result about non-existence of P-points by S. Shellah. Our main point of interest are the algebras P(ω)/fin(ω) i P(ℵ1)/fin(ℵ1).
- ItemRisk modelling approaches for student-like models with fractal activity time(2021) Solomanchuk, Georgiy; Shchestyuk, NataliiaThe paper focuses on value at risk (V@R) measuring for Student-like models of markets with fractal activity time (FAT). The fractal activity time models were introduced by Heyde to try to encompass the empirically found characteristics of read data and elaborated on for Variance Gamma, normal inverse Gaussian and skewed Student distributions. But problem of evaluating an value at risk for this model was not researched. It is worth to mention that if we use normal or symmetric Student‘s models than V@R can be computed using standard statistical packages. For calculating V@R for Student-like models we need Monte Carlo method and the iterative scheme for simulating N scenarios of stock prices. We model stock prices as a diffusion processes with the fractal activity time and for modeling increments of fractal activity time we use another diffusion process, which has a given marginal inverse gamma distribution. The aim of the paper is to perform and compare V@R Monte Carlo approach and Markowitz approach for Student-like models in terms of portfolio risk. For this purpose we propose procedure of calculating V@R for two types of investor portfolios. The first one is uniform portfolio, where d assets are equally distributed. The second is optimal Markowitz portfolio, for which variance of return is the smallest out of all other portfolios with the same mean return. The programmed model which was built using R-statistics can be used as to the simulations for any asset and for construct optimal portfolios for any given amount of assets and then can be used for understanding how this optimal portfolio behaves compared to other portfolios for Student-like models of markets with fractal activity time. Also we present numerical results for evaluating V@R for both types of investor portfolio. We show that optimal Markowitz portfolio demonstrates in the most of cases the smallest possible Value at Risk comparing with other portfolios. Thus, for making investor decisions under uncertainty we recommend to apply portfolio optimization and value at risk approach jointly.
- ItemSimulating stochastic diffusion processes and processes with "market" time(2020) Boluh, Kateryna; Shchestyuk, NataliiaThe paper focuses on modelling, simulation techniques and numerical methods concerned stochastic processes in subject such as financial mathematics and financial engineering. The main result of this work is simulation of a stochastic process with new market active time using Monte Carlo techniques. The processes with market time is a new vision of how stock price behavior can be modeled so that the nature of the process is more real. The iterative scheme for computer modelling of this process was proposed. It includes the modeling of diffusion processes with a given marginal inverse gamma distribution. Graphs of simulation of the Ornstein-Uhlenbeck random walk for different parameters, a simulation of the diffusion process with a gamma-inverse distribution and simulation of the process with market active time are presented.
- ItemSolvable Lie algebras of derviations of rank one(2019) Petravchuk, Anatolii; Sysak, KaterynaLet K be a field of characteristic zero, A = K[x1,...,xn] the polynomial ring and R = K(x1,...,xn) the field of rational functions in n variables over K. The Lie algebra Wn(K) of all K-derivations on A is of great interest since its elements may be considered as vector fields on Kn with polynomial coefficients. If L is a subalgebra of Wn(K), then one can define the rank rkAL of L over A as the dimension of the vector space RL over the field R. Finite dimensional (over K) subalgebras of Wn(K) of rank 1 over A were studied by the first author jointly with I. Arzhantsev and E. Makedonskiy. We study solvable subalgebras L of Wn(K) with rkAL = 1, without restrictions on dimension over K. Such Lie algebras are described in terms of Darboux polynomials.
- ItemSpeech audio modeling by means of causal moving average equipped gated attention(2022) Ivaniuk, AndriiIn the paper we compare different attention mechanisms on the task of audio generation using unsupervised approaches following previous work in language modeling. It is important problem, as far as speech synthesis technology could be used to convert textual information into acoustic waveform signals. These representations can be conveniently integrated into mobile devices and used in such applications as voice messengers or email apps. Sometimes it is difficult to understand and read important messages when being abroad. The lack of appropriate computer systems or some security problems may arise. With this technology, e-mail messages can be listened quickly and efficiently on smartphones, boosting productivity. Apart from that, it is used to assist visually impaired people, so that, for instance, the screen content can be automatically read aloud to a blind user. Nowadays, home appliances, like slow cookers can use this system too for reading culinary recipes, automobiles for voice navigation to the destination spot, or language learners for pronunciation teaching. Speech generation is the opposite problem of automatic speech recognition (ASR) and is researched since the second half of the eighteen’s century. Also, this technology also helps vocally handicapped people find a way to communicate with others who do not understand sign language. However, there is a problem, related to the fact that the audio sampling rate is very high, thus lea,ding to very long sequences which are computationally difficult to model. Second challenge is that speech signals with the same semantic meaning can be represented by a lot of signals with significant variability, which is caused by channel environment, pronunciation or speaker timbre characteristics. To overcome these problems, we train an autoencoder model to discretize continuous audio signal into a finite set of discriminative audio tokens which have a lower sampling rate. Subsequently, autoregressive models, which are not conditioned on text, are trained on this representation space to predict the next token, based on previous sequence elements. Hence, this modeling approach resembles causal language modeling. In our study, we show that unlike in the original MEGA work, traditional attention outperforms moving average equipped gated attention, which shows that EMA gated attention is not stable yet and requires careful hyper-parameter optimization.
- ItemTwo approaches for option pricing under illiquidity(2022) Pauk, Viktoriia; Petrenko, Oksana; Shchestyuk, NataliyaThe paper focuses on option pricing under unusual behaviour of the market, when the price may not be changed for some time what is quite a common situation on the modern financial markets. There are some patterns that can cause permanent price gaps to form and lead to illiquidity. For example, global changes that have a negative impact on financial activity, or a small number of market participants, or the market is quite young and is just in the process of developing, etc. In the paper discrete and continuous time approaches for modelling market with illiquidity and evaluation option pricing were considered. Trinomial discrete time model improves upon the binomial model by allowing a stock price not only to move up, down but stay the same with certain probabilities, what is a desirable feature for the illiquid modelling. In the paper parameters for real financial data were identified and the backward induction algorithm for building call option price trinomial tree was applied. Subdiffusive continuous time model allows successfully apply the physical models for describing the trapping events to model financial data stagnation’s periods. In this paper the Inverse Gaussian process IG was proposed as a subordinator for the subdiffusive modelling of illiquidity and option pricing. The simulation of the trajectories for subordinator, inverse subordinator and subdiffusive GBM were performed. The Monte Carlo method for option evaluation was applied. Our aim was not only to compare these two models each with other, but also to show that both models adequately describe the illiquid market and can be used for option pricing on this market. For this purpose absolute relative percentage (ARPE) and root mean squared error (RMSE) for both models were computed and analysed. Thanks to the proposed approaches, the investor gets a tools, which allows him to take into account the illiquidity.
- ItemАлгоритм обчислень у силовських 2-підгрупах знакозмінних груп за допомогою системи комп'ютерної алгебри GAP(2018) Ольшевська, ВітаУ статтi наведено алгоритм перевiрки, чи є певна множина елементiв S мiнiмальною системою твiрних для силовської 2-пiдгрупи знакозмiнної групи Syl2(A2n ), за допомогою системи комп’ютерної алгебри GAP. Для невеликих n (n = 3 i n = 4) проведено обчислення за допомогою цього алгоритму. Зокрема, перевiрено абелевiсть, пораховано потужнiсть та кiлькiсть елементiв мiнiмальної системи твiрних комутантiв у кожнiй з груп Syl2(A8), Syl2(A16) та фактор-групах цих силовських 2-пiдгруп по комутанту.
- ItemАлгоритм пошуку кількості рухомих точок підстановок із силовських 2-підгруп Syl2(S2n) симетричних груп S2n(2021) Ольшевська, ВітаУ статті запропоновано алгоритм пошуку кількості рухомих точок підстановок силовських 2-підгруп Syl2(S2n) симетричних груп S2n, n є N. Для побудови цього алгоритму використано ізоморфізм між групою Syl2(S2n) та групою бінарних кореневих дерев з мітками. Також обчислено складність запропонованого алгоритму та його середню кількість кроків для силовської 2-підгрупи симетричної групи S2n. Обраховано кількість підстановок із Syl2(S2n), що мають максимальну кількість рухомих точок.
- ItemАнтиподальні графи діаметра 4(2018) Прончук, ЛюдмилаМетричний простiр (X, d) називається антиподальним, якщо для довiльної точки x iснує таке y, що для довiльної точки z множини X виконується рiвнiсть d(x, z) + d(z, y) = d(x, y). Вiдомими конструкцiями антиподальних графiв є графи Хемiнга, графи Джонсона, графи вечiрки (Coctail-party графи). У статтi [1] було побудовано конструкцiю антиподальних графiв дiаметра 3. Використовуючи iдею конструкцiї Стевановича P(G) з [1], побудовано конструкцiю для напiвканонiчних графiв на множинi з чотирьох вершин F(G), за допомогою якої можна побудувати антиподальнi графи дiаметра 4. Оскiльки iснує всього два напiвканонiчних графи на множинi з чотирьох вершин, побудовано два антиподальних графи дiаметра 4. Для кожного з них доведено антиподальнiсть.
- ItemВолодимир Васильович Кириченко(2019) Олійник, Андрій; Олійник, БогданаСтаттю присвячено пам’ятi видатного українського математика i педагога, одного iз засновникiв київської школи теорiї зображень i теорiї кiлець, професора Київського нацiонального унiверситету iменi Тараса Шевченка Володимира Васильовича Кириченка.
- ItemДо 150-річчя від дня народження Георгія Феодосійовича Вороного (1868-1908)(2018) Митник, Юрій; Кашпіровський, Олексій; Олійник, БогданаСтаттю присвячено 150-й рiчницi вiд дня народження видатного українського математика Георгiя Феодосiйовича Вороного. Описано його життєвий шлях, основнi математичнi результати i публiкацiї.
- ItemДослiдження стохастичної поведiнки клiтинних автоматiв(2022) Глушенков, Сергій; Чорней, РусланКлітинні автомати дають змогу моделювати широкий спектр складних систем із локальною взаємодією. Попри те, що загалом поведінка окремо взятих клітинних автоматів може бути дуже простою, вдала їх комбінація або задання нестандартних правил взаємодії може значно ускладнити поведінку системи і призвести до доволі неоднозначних та непередбачуваних результатів спостережень. Стохастичність допомагає наблизити симульоване середовище до реальних умов і знайти оптимальну стратегію, яка буде більш стійкою до усіх можливих видів подій, в тому числі малоймовірних. Саме стохастичні клітинні автомати широко використовують у відтворенні природних явищ та процесів, симуляції транспортних потоків, криптографії тощо. У середовищах з наявним зовнішнім впливом стає актуальною задача пошуку оптимального керування системою. У цій статті розглянуто оптимальні стратегії керування для систем стохастичних клітинних автоматів, наведено приклад використання алгоритму покращення стратегії в задачі гасіння лісових пожеж, проаналізовано оптимальність вибраної стратегії.