Чисельне диференціювання табличних функцій у довільно розташованих вузлах інтерполяції

dc.citation.epage41
dc.citation.issue1
dc.citation.journalTitleУкраїнський журнал інформаційних технологій
dc.citation.spage25
dc.citation.volume5
dc.contributor.affiliationНаціональний університет “Львівська політехніка”
dc.contributor.affiliationLviv Polytechnic National University
dc.contributor.authorГрицюк, Юрій Іванович
dc.contributor.authorТушницький, Р. Б.
dc.contributor.authorHrytsiuk, Yu. I.
dc.contributor.authorTushnytskyy, R. B.
dc.coverage.placenameЛьвів
dc.coverage.placenameLviv
dc.date.accessioned2024-04-01T07:54:32Z
dc.date.available2024-04-01T07:54:32Z
dc.date.created2023-02-28
dc.date.issued2023-02-28
dc.description.abstractРозроблено методику чисельного диференціювання таблично-заданих функцій з використанням многочлена Тейлора n-го степеня, яка дає можливість обчислювати похідні k-го порядку (k £ n) у будь-яких точках між довільно розташованими вузлами інтерполяції від однієї, двох і багатьох незалежних змінних. Проаналізовано останні дослідження та публікації, що дало змогу встановити складність задачі обчислення похідних від функції за значеннями незалежних змінних на деякому інтервалі значень таблично-заданої функції. Наведено постановку задачі чисельного диференціювання таблично-заданих функцій з використанням многочлена Тейлора n-го степеня від однієї, двох і багатьох незалежних змінних. Встановлено, що будь-яку таблично-задану функцію спочатку потрібно згладити деякою функцією, аналітичний вираз якої є глобальним (локальним) інтерполяційним многочленом або многочленом, який отримано за МНК із деякою похибкою. Під похідною від такої таблично-заданої функції розуміють похідну від її інтерполянти. Розроблено метод чисельного диференціювання таблично-заданих функцій, сутність якого зводиться до добутку вектора-рядка Тейлора n-го степеня на матрицю k-го порядку його диференціювання (k £ n) і на вектор-стовпець коефіцієнтів відповідної інтерполянти. Наведено деякі постановки задач чисельного диференціювання таблично-заданих функцій з використанням многочлена Тейлора n-го степеня, відповідні алгоритми їх розв’язання та конкретні приклади реалізації. Встановлено, що для обчислення похідної k-го порядку від таблично-заданої функції за прийнятим значенням незалежної змінної потрібно виконати такі дії: за даними таблиці сформувати матричне рівняння, розв’язати його та отримати значення коефіцієнтів інтерполянти; підставити у відповідний матричний вираз коефіцієнти інтерполянти та значення незалежної змінної та виконати дії множення матриць, вказані у виразі. Здійснено перевірку правильності виконання розрахунків із використанням відповідних центральних різницевих формул. Встановлено, що обчислені похідні k-го порядку з використанням формул центральних скінченних різниць практично збігаються зі значеннями, отриманими за допомогою інтерполяційного многочлена Тейлора n-го степеня, тобто значення похідних обчислено правильно.
dc.description.abstractA methodology has been developed for numerically differentiating table-given functions using a Taylor polynomial of degree n, which enables the computation of k-th order derivatives (k £ n) at any point between arbitrarily located interpolation nodes in one, two, or multiple independent variables. Recent research and publications have been analysed, allowing for the assessment of the task complexity of computing derivatives of a function based on the values of independent variables within a certain interval of a table-given function. The formulation of the problem of numerical differentiation of periodic table-given functions using the Taylor polynomial of the nth order from one, two, and multiple independent variables is described. It is established that any tabulated function should be initially smoothed by some function whose analytical expression is a global (local) interpolating polynomial or a polynomial obtained by least squares approximation with some error. The derivative of such a table-given function is understood as the derivative of its interpolant. A method of numerical differentiation of table-given functions is developed, the essence of which is reduced to the product of the Taylor row vector of the n-th degree by the matrix of the k-th order of its differentiation (k £ n) and on the column vector of the coefficients of the corresponding interpolant. Some problem formulations of numerical differentiation of table-given functions using Taylor polynomials of degree n, corresponding solution algorithms, and specific implementation examples are provided. It has been established that to compute the k-th order derivative of a table-given function at a given value of the independent variable, the following steps need to be performed: based on the given table data, form a matrix equation, solve it to obtain the coefficients of the interpolant; substitute into the corresponding matrix expression the obtained interpolant coefficients and the independent variable value, and perform the matrix multiplication operations specified in the expression. The verification of the accuracy of the calculations using the appropriate central difference formulas was made. It was established that the calculated derivatives of the k-th order using the formulas of central finite differences practically coincide with the values ​​obtained using the Taylor polynomial interpolation of the n-th order, that is, the values ​​of the derivatives are calculated correctly.
dc.format.extent25-41
dc.format.pages17
dc.identifier.citationГрицюк Ю. І. Чисельне диференціювання табличних функцій у довільно розташованих вузлах інтерполяції / Ю. І. Грицюк, Р. Б. Тушницький // Український журнал інформаційних технологій. — Львів : Видавництво Львівської політехніки, 2023. — Том 5. — № 1. — С. 25–41.
dc.identifier.citationenHrytsiuk Yu. I. Numerical differentiation of table-given functions at arbitrarily located interpolation nodes / Yu. I. Hrytsiuk, R. B. Tushnytskyy // Ukrainian Journal of Information Technology. — Lviv : Lviv Politechnic Publishing House, 2023. — Vol 5. — No 1. — P. 25–41.
dc.identifier.doidoi.org/10.23939/ujit2023.01.025
dc.identifier.issn2707-1898
dc.identifier.urihttps://ena.lpnu.ua/handle/ntb/61566
dc.language.isouk
dc.publisherВидавництво Львівської політехніки
dc.publisherLviv Politechnic Publishing House
dc.relation.ispartofУкраїнський журнал інформаційних технологій, 1 (5), 2023
dc.relation.ispartofUkrainian Journal of Information Technology, 1 (5), 2023
dc.relation.references[1] Abinash Nayak. (2020). A new regularization approach for numerical differentiation. Inverse Problems in Science and Engineering, 28(13), 1747-1772. https://doi.org/10.1080/17415977.2020.1763983
dc.relation.references[2] Andrei D. Polyanin, & Alexander V. Manzhirov. (1998). Handbook of Integral Equations: Second Edition (Handbooks of Mathematical Equations). CRC Press, Boca Raton, 1142 p. URL: https://www.amazon.com/Handbook-Integral-Equations-Handbooks-Mathematical/dp/1584885076
dc.relation.references[3] Andrunyk, V. A. (2019). Numerical methods in computer sciences. Lviv: New World-2000, Vol. 1, 470 p. [In Ukrainian.
dc.relation.references[4] Andrunyk, V. A., Vysotska, V. A., & Pasichnyk V. V. (Ed.), et al. (2018). Numerical methods in computer science: textbook. Issue 2. Lviv: Novy svit-2000, 536 p. [In Ukrainian].
dc.relation.references[5] Andrunyk, V. A., Vysotska, V. A., Pasichnyk, V. V., et al. (2018). Numerical methods in computer science: textbook. Edited by V. V. Pasichnyk. Lviv: New World-2000, Vol. 2, 536 p. [In Ukrainian].
dc.relation.references[6] Bakhvalov, Ya. S., Zhidkov, I. L., & Kobelkov, G. M. (2002). Numerical methods. Moscow: Laboratory of basic knowledge, 632 p. [In Russian].
dc.relation.references[7] Balashova, S. D. (1992). Numerical methods: tutorial. In two parts. Kyiv: NMK VO, Part 1, 280 p., Part 2, 328 p. [In Ukrainian].
dc.relation.references[8] Bang Hu, & Shuai Lu. (2012). Numerical differentiation by a Tikhonov regularization method based on the discrete cosine transform. Applicable Analysis, 91(1), 719–736. https://doi.org/10.1080/00036811.2011.598862
dc.relation.references[9] Ben Adcock, Daan Huybrechs, & Jesús Martín-Vaquero. (2014). On the Numerical Stability of Fourier Extensions. Foundations of Computational Mathematics, 14, 635–687. https://doi.org/10.1007/s10208-013-9158-8
dc.relation.references[10] Binbin Yin, & Yuzhang Ye. (2006). Recovering the local volatility in Black–Scholes model by numerical differentiation. Applicable Analysis, 85(6–7), 681–692. https://doi.org/10.1080/00036810500475025
dc.relation.references[11] Boyko, L. T. (2009). Fundamentals of numerical methods: a study guide. Dnipropetrovsk: DNU Publishing House, 244 p. [In Ukrainian].
dc.relation.references[12] Branovytska, S. V., Medvedev, R. B., & Fialkov, Y. Ya. (2004). Computational mathematics and programming: textbook. Kyiv: IOC Publishing House "Polytechnic", 220 p. [In Ukrainian].
dc.relation.references[13] Cheng, J., Jia, X. Z., & Wang, Y. B. (2007). Numerical differentiation and its applications. Inverse Problems in Science and Engineering, 15(1), 339-357. https://doi.org/10.1080/17415970600839093
dc.relation.references[14] Chu-Li Fu, Xiao-Li Feng, Zhi Qian. (2010). Wavelets and high order numerical differentiation. Applied Mathematical Modelling, 34(11), 3008–3021. https://doi.org/10.1016/j.apm.2010.01.009
dc.relation.references[15] Demkiv, I. I. (2013). Interpolation of nonlinear operators on a continuous set of nodes. Abstract of Doctoral Dissertation for Candidate of Physics and Mathematics Sciences (01.01.07 – Computational mathematics). Ihor Ivanovich Demkiv. Kyiv: Institute of Mathematics of the National Academy of Sciences of Ukraine, 39 p. [In Ukrainian].
dc.relation.references[16] Diego A. Murio. (1993). The Mollification Method and Numerical Solution of Ill-posed Problems. New York: John Wiely & Sons, 254 p. https://doi.org/10.1002/9781118033210
dc.relation.references[17] Engl, H. W., Hanke, M., & Neubauer, A. (1996). Regularization of Inverse Problems. Mathematics and Its Applications, 375, Kluwer Academic Publishers Group, Dordrecht. https://doi.org/10.1007/978-94-009-1740-8
dc.relation.references[18] Esterby, O., & Zlatev, Z. (1987). Direct methods of sparse matrices. Translation by Hakim Ikramov. Moscow: Mir Publishing House, 118 p. [In Russian].
dc.relation.references[19] Feldman, L. P. (2000). Numerical methods and mathematical packages. Solving problems in the Machematica-3 package. Donetsk: Donetsk GTU, 96 p. [In Russian].
dc.relation.references[20] Feldman, L. P., Petrenko, A. I., & Dmytrieva, O. A. (2006). Numerical methods in computer science: textbook. Kyiv: BHV Publishing Group, 474 p. [In Ukrainian].
dc.relation.references[21] Filts, R. V. (1994). Calculation of Taylor and Fourier polynomials and their derivatives. Synopsis of lectures on the subject "Mathematical problems of electromechanics" for students. special 1801 "Electromechanics". Lviv: State University "Lviv Polytechnic", 24 p. [In Ukrainian].
dc.relation.references[22] Filts, R. V. (2010). Equilibrium calculus: monograph. Lviv: LDINTU named after Vyacheslav Chornovol, 184 p. [In Ukrainian].
dc.relation.references[23] Filtz, R. V. (1994). Differentiation of tabular functions. Synopsis of lectures on the subject "Mathematical problems of electromechanics" for students of the specialty 1801 "Electromechanics". Typescript edition of the "Electric Machines" department. Lviv: State University "Lviv Polytechnic", 52 p. [In Ukrainian].
dc.relation.references[24] Filz, R. V., Kotsyuba, M. V., & Hrytsiuk, Yu. I. (1991). Algorithm for computing the Taylor polynomial and its derivatives on a computer. Izvestiya vuzov. Electromechanics, No 5, 5–10. [In Russian].
dc.relation.references[25] Goncharov, O. A., Vasylieva, L. V., & Yunda, A. M. (2020). Numerical methods of solving applied problems: textbook. Sumy: Sumy State University, 142 p. [In Ukrainian].
dc.relation.references[26] Hanke M, Scherzer O. (1998). Error analysis of an equation error method for the identification of the diffusion coefficient in a quasi-linear parabolic differential equation. SIAM Journal on Applied Mathematics, 59(3), 1012–1027. https://doi.org/10.1137/S0036139997331628
dc.relation.references[27] Hanke, M., & Scherzer, O. (2001). Inverse Problems light: Numerical differentiation. American Mathematical Monthly, 108(6), 512–521. https://doi.org/10.2307/2695705
dc.relation.references[28] Herbert Egger, & Heinz W. Engl. (2005). Tikhonov regularization applied to the inverse problem of option pricing: convergence analysis and rates. Inverse Problems, 21(3), 1027–1045. https://doi.org/10.1088/0266-5611/21/3/014
dc.relation.references[29] Hrytsiuk, Yu. I. (2014). Computational methods and models in scientific research: monograph. Lviv: LSU BZD Publishing House. 288 p. [In Ukrainian].
dc.relation.references[30] Hrytsiuk, Yu. I., & Havrysh, V. I. (2022). Interpolation of table-given functions by Fourier polynomial. Scientific Bulletin of UNFU, 32(1), 88–102. https://doi.org/10.36930/40320414
dc.relation.references[31] Hrytsiuk, Yu. I., & Havrysh, V. I. (2022). Numerical differentiation of periodic tabular-specified functions using the Fourier polynomial. Scientific Bulletin of UNFU, 32(5), 69–79. https://doi.org/10.36930/40320410
dc.relation.references[32] Hrytsiuk, Yu. I., & Tushnytskyy, R. B. (2022). Interpolation of tabular functions from one independent variable using the Taylor polynomial. Ukrainian Journal of Information Technology, 4(2), 01–17. https://doi.org/10.23939/ujit2022.02.001
dc.relation.references[33] Huilin Xu, & Jijun Liu. (2010). Stable numerical differentiation for the second order derivatives. Advances in Computational Mathematics, 33, 431–447. https://doi.org/10.1007/s10444-009-9132-9
dc.relation.references[34] Jane Cullum. (1971). Numerical differentiation and regularization. SIAM Journal on Numerical Analysis, 8(2), 254–265. https://doi.org/10.1137/0708026
dc.relation.references[35] John P. Boyd. (2002). A Comparison of Numerical Algorithms for Fourier Extension of the First, Second, and Third Kinds. Journal of Computational Physics, 178(1), 118-160. https://doi.org/10.1006/jcph.2002.7023
dc.relation.references[36] Kopcha-Horyachkina, G. E. (2011). Numerical methods in computer science: educational and methodological manual, Part 1. Uzhgorod: Publishing House of Zakarpattia State University, 76 p. [In Ukrainian].
dc.relation.references[37] Krylyk, L. V., Bogach, I. V., & Lisovenko, A. I. (2019). Numerical Methods. Numerical integration of functions: tutorial. Vinnytsia: VNTU, 74 p. [In Ukrainian].
dc.relation.references[38] Krylyk, L. V., Bogach, I. V., & Prokopova, M. O. (2013). Computational mathematics. Interpolation and approximation of tabular data: tutorial. Vinnytsia: VNTU, 111 p. [In Ukrainian].
dc.relation.references[39] Kvetny, R. N., & Bogach, I. V. (2003). Interpolation of the function of two variables according to the Lagrange method. Bulletin of the Vinnytsia Polytechnic Institute, No 6, 365–368.
dc.relation.references[40] Leevan Ling. (2006). Finding Numerical Derivatives for Unstructured and Noisy Data by Multiscale Kernels. SIAM Journal on Numerical Analysis, 44(1). https://doi.org/10.1137/050630246
dc.relation.references[41] Lyon, M., Picard, J. (2014). The Fourier approximation of smooth but non-periodic functions from unevenly spaced data. Advances in Computational Mathematics, 40, 1073–1092. https://doi.org/10.1007/s10444-014-9342-7
dc.relation.references[42] Makarov V. L., Demkiv I. I. (2012). Interpolating integral continued fractions that do not require the substitution rule. Abstracts of the report in Kamianets-Podilsk, May 28 – June 3, 2012. Kyiv, pp. 63–64. [In Ukrainian].
dc.relation.references[43] Mamchuk, V. I. (2015). Numerical methods: tutorial. Kyiv: National Aviation University, 388 p. [In Ukrainian].
dc.relation.references[44] Markus Hegland, & Robert S. Anderssen. (2005). Resolution enhancement of spectra using differentiation. Inverse Problems, 21, 915. https://doi.org/10.1088/0266-5611/21/3/008
dc.relation.references[45] Martin Hanke, & Otmar Scherzer. (2001)Monthly, 108(6), 512–521. https://doi.org/10.1080/00029890.2001.11919778
dc.relation.references[46] Murio, D. A., Mejia, C. E., & Zhan, S. (1998). Discrete mollification and automatic numerical differentiation. Computers & Mathematics with Applications, 35(5), 1–13. https://doi.org/10.1016/S0898-1221(98)00001-7
dc.relation.references[47] Ovchinnikov, P. F. (Ed.), Lisitsyn, B. M., & Mikhailenko, V. M. (1989). Higher mathematics. Kyiv: High school, 679 p. URL: http://pdf.lib.vntu.edu.ua/books/2015/Ovchin_P2_2004_792.pdf
dc.relation.references[48] Pissanetzky, Sergio. (1988). Sparse Matrix Technology. Translation from English. Moscow: Mir Publishing House, 410 p. [In Russian].
dc.relation.references[49] Qian, Z., Fu, C. L., Xiong, X. T., & Wei, T. (2006). Fourier truncation method for high order numerical derivatives. Applied mathematics and computation, 181(2), 940–948. https://doi.org/10.1016/j.amc.2006.01.057
dc.relation.references[50] Ramm, A. G., & Smirnova, A. B. (2001). On stable numerical differentiation. Mathematics of Computation, Vol. 70, 1131–1153. https://doi.org/10.1090/S0025-5718-01-01307-2
dc.relation.references[51] Rodrigo B. Platte, Lloyd N. Trefethen, & Arno B. J. Kuijlaars. (2011). Impossibility of Fast Stable Approximation of Analytic Functions from Equispaced Samples. SIAM Review, 53(2), 308-318. URL: https://www.jstor.org/stable/23065166
dc.relation.references[52] Rudolf Gorenflo, & Sergio Vessella. (1991). Abel Integral Equations: Analysis and Applications. Lecture Notes in Mathematics, 1461. Berlin: Springer, 1991st Edition, 232 p. URL: https://www.amazon.com/Abel-Integral-EquationsApplications-Mathematics/dp/354053668X
dc.relation.references[53] Soyoung Ahn, U. JinChoi, & Alexander G. Ramm. (2006). A scheme for stable numerical differentiation. Journal of Computational and Applied Mathematics, 186(2), 325-334. https://doi.org/10.1016/j.cam.2005.02.002
dc.relation.references[54] Stanley R. Deans. (2007). The Radon Transform and Some of Its Applications (Dover Books on Mathematics). Dover Publications; Illustrated edition, 304 p. URL: https://www.amazon.com/Radon-Transform-Applications-Dover-Mathematics/dp/0486462412
dc.relation.references[55] Sviridenko, A. B. (2017). Direct multiplicative methods for sparse matrices. Newton methods. Computer research and modeling, Vol. 9 No. 5, 679−703. https://doi.org/10.20537/2076-7633-2017-9-5-679-703
dc.relation.references[56] Tsegelyk, H. G. (2004). Numerical methods: textbook for students. Lviv: Publishing House of the Lviv National University named after Ivan Franko, 407 p. [In Ukrainian].
dc.relation.references[57] Tsegelyk, H. G. (2004). Numerical methods: textbook for university students. Lviv National University named after Ivan Franko. Lviv, 407 p. [In Ukrainian].
dc.relation.references[58] Vasylyshyn, T. V., Goy, T. P., & Fedak, I. V. (2014). Integral equations: a study guide. Ivano-Frankivsk: Simyk, 222 p. URL: https://kmfa.pnu.edu.ua/wp-content/uploads/sites/64/2019/12/Василишин-Т.В.-Гой-Т.П.-Федак-І.В.-Інтегральні-рівняння.pdf
dc.relation.references[59] Wan, X. Q., Wang, Y. B., & Yamamoto, M. (2006). Detection of irregular points by regularization in numerical differentiation and application to edge detection. Inverse Problems, 22(3), 1089. https://doi.org/10.1088/0266-5611/22/3/022
dc.relation.references[60] Wang, Y. B., & Wei, T. (2005). Numerical differentiation for two-dimensional scattered data. Journal of Mathematical Analysis and Applications, 312(1), 121-137. https://doi.org/10.1016/j.jmaa.2005.03.025
dc.relation.references[61] Wang, Y. B., Jia, X. Z., & Cheng, J. (2002). A numerical differentiation method and its application to reconstruction of discontinuity. Inverse Problems, 18(6), 1461. https://doi.org/10.1088/0266-5611/18/6/301
dc.relation.references[62] Wei, T., & Hon, Y. C. (2007). Numerical differentiation by radial basis functions approximation. Advances in Computational Mathematics, 27(3), 247–272. https://doi.org/10.1007/s10444-005-9001-0
dc.relation.references[63] Wei, T., Hon, Y, C., & Wang, Y. B. (2005). Reconstruction of numerical derivatives from scattered noisy data. Inverse Problems, 21(2), 657–672. https://doi.org/10.1088/0266-5611/21/2/013
dc.relation.references[64] Weidong Chen. (2021). Regularized derivative interpolation for two dimensional band-limited functions. Signal Processing, 184, 107943. https://doi.org/10.1016/j.sigpro.2020.107943
dc.relation.references[65] Xie, O., Zhao Z. Y. (2013). Numerical differentiation of 2d functions by a mollification method based on Legendre expansion. International Journal of Computer Science, Vol. 10(1), 729–734. URL: https://ijcsi.org/papers/IJCSI-10-1-2-729-734.pdf
dc.relation.references[66] Yang, Lu. (2008). A perturbation method for numerical differentiation. Applied mathematics and computation, 199(1), 368–374. https://doi.org/10.1016/j.amc.2007.09.066
dc.relation.references[67] Yong-Fu Zhang, & Chong-Jun Li. (2019). A class of multistep numerical difference schemes applied in inverse heat conduction problem with a control parameter. Inverse Problems in Science and Engineering, 27(7), 887–942. https://doi.org/10.1080/17415977.2018.1501370
dc.relation.references[68] Zewen Wang, & Rongsheng Wen (2010). Numerical differentiation for high orders by an integration method. Journal of Computational and Applied Mathematics, 234(3), 941-948. https://doi.org/10.1016/j.cam.2010.01.056
dc.relation.references[69] Zhenyu Zhao, & Zehong Meng. (2010). Numerical differentiation for periodic functions. Inverse Problems in Science and Engineering, 18(7), 957-969. https://doi.org/10.1080/17415977.2010.492517
dc.relation.references[70] Zhenyu Zhao, Zehong Meng, & Guoqiang He. (2009). A new approach to numerical differentiation. Journal of Computational and Applied Mathematics, 232(2), 227–239. https://doi.org/10.1016/j.cam.2009.06.001
dc.relation.references[71] Zhenyu Zhao, Zehong Meng, Li Xu, & Junfeng Liu. (2009). A New Mollification Method for Numerical Differentiation of 2D Periodic Functions. IEEE International Joint Conference on Computational Sciences and Optimization, 24-26 April 2009, (pp. 205-207), Sanya, China. https://doi.org/10.1109/CSO.2009.174
dc.relation.references[72] Zhenyu Zhao. (2010). A truncated Legendre spectral method for solving numerical differentiation. International Journal of Computer Mathematics, 87(16), 3209–3217. https://doi.org/10.1080/00207160902974404
dc.relation.references[73] Zygmund, Antoni (Author), Fefferman, Robert A. (Ed.). (2002).Trigonometric series, I, II, Cambridge Mathematical Library (3rd ed.). Cambridge University Press, 784 p. URL: https://www.amazon.com/Trigonometric-Cambridge-Mathematical-Library-Zygmund/dp/05218905
dc.relation.referencesen[1] Abinash Nayak. (2020). A new regularization approach for numerical differentiation. Inverse Problems in Science and Engineering, 28(13), 1747-1772. https://doi.org/10.1080/17415977.2020.1763983
dc.relation.referencesen[2] Andrei D. Polyanin, & Alexander V. Manzhirov. (1998). Handbook of Integral Equations: Second Edition (Handbooks of Mathematical Equations). CRC Press, Boca Raton, 1142 p. URL: https://www.amazon.com/Handbook-Integral-Equations-Handbooks-Mathematical/dp/1584885076
dc.relation.referencesen[3] Andrunyk, V. A. (2019). Numerical methods in computer sciences. Lviv: New World-2000, Vol. 1, 470 p. [In Ukrainian.
dc.relation.referencesen[4] Andrunyk, V. A., Vysotska, V. A., & Pasichnyk V. V. (Ed.), et al. (2018). Numerical methods in computer science: textbook. Issue 2. Lviv: Novy svit-2000, 536 p. [In Ukrainian].
dc.relation.referencesen[5] Andrunyk, V. A., Vysotska, V. A., Pasichnyk, V. V., et al. (2018). Numerical methods in computer science: textbook. Edited by V. V. Pasichnyk. Lviv: New World-2000, Vol. 2, 536 p. [In Ukrainian].
dc.relation.referencesen[6] Bakhvalov, Ya. S., Zhidkov, I. L., & Kobelkov, G. M. (2002). Numerical methods. Moscow: Laboratory of basic knowledge, 632 p. [In Russian].
dc.relation.referencesen[7] Balashova, S. D. (1992). Numerical methods: tutorial. In two parts. Kyiv: NMK VO, Part 1, 280 p., Part 2, 328 p. [In Ukrainian].
dc.relation.referencesen[8] Bang Hu, & Shuai Lu. (2012). Numerical differentiation by a Tikhonov regularization method based on the discrete cosine transform. Applicable Analysis, 91(1), 719–736. https://doi.org/10.1080/00036811.2011.598862
dc.relation.referencesen[9] Ben Adcock, Daan Huybrechs, & Jesús Martín-Vaquero. (2014). On the Numerical Stability of Fourier Extensions. Foundations of Computational Mathematics, 14, 635–687. https://doi.org/10.1007/s10208-013-9158-8
dc.relation.referencesen[10] Binbin Yin, & Yuzhang Ye. (2006). Recovering the local volatility in Black–Scholes model by numerical differentiation. Applicable Analysis, 85(6–7), 681–692. https://doi.org/10.1080/00036810500475025
dc.relation.referencesen[11] Boyko, L. T. (2009). Fundamentals of numerical methods: a study guide. Dnipropetrovsk: DNU Publishing House, 244 p. [In Ukrainian].
dc.relation.referencesen[12] Branovytska, S. V., Medvedev, R. B., & Fialkov, Y. Ya. (2004). Computational mathematics and programming: textbook. Kyiv: IOC Publishing House "Polytechnic", 220 p. [In Ukrainian].
dc.relation.referencesen[13] Cheng, J., Jia, X. Z., & Wang, Y. B. (2007). Numerical differentiation and its applications. Inverse Problems in Science and Engineering, 15(1), 339-357. https://doi.org/10.1080/17415970600839093
dc.relation.referencesen[14] Chu-Li Fu, Xiao-Li Feng, Zhi Qian. (2010). Wavelets and high order numerical differentiation. Applied Mathematical Modelling, 34(11), 3008–3021. https://doi.org/10.1016/j.apm.2010.01.009
dc.relation.referencesen[15] Demkiv, I. I. (2013). Interpolation of nonlinear operators on a continuous set of nodes. Abstract of Doctoral Dissertation for Candidate of Physics and Mathematics Sciences (01.01.07 – Computational mathematics). Ihor Ivanovich Demkiv. Kyiv: Institute of Mathematics of the National Academy of Sciences of Ukraine, 39 p. [In Ukrainian].
dc.relation.referencesen[16] Diego A. Murio. (1993). The Mollification Method and Numerical Solution of Ill-posed Problems. New York: John Wiely & Sons, 254 p. https://doi.org/10.1002/9781118033210
dc.relation.referencesen[17] Engl, H. W., Hanke, M., & Neubauer, A. (1996). Regularization of Inverse Problems. Mathematics and Its Applications, 375, Kluwer Academic Publishers Group, Dordrecht. https://doi.org/10.1007/978-94-009-1740-8
dc.relation.referencesen[18] Esterby, O., & Zlatev, Z. (1987). Direct methods of sparse matrices. Translation by Hakim Ikramov. Moscow: Mir Publishing House, 118 p. [In Russian].
dc.relation.referencesen[19] Feldman, L. P. (2000). Numerical methods and mathematical packages. Solving problems in the Machematica-3 package. Donetsk: Donetsk GTU, 96 p. [In Russian].
dc.relation.referencesen[20] Feldman, L. P., Petrenko, A. I., & Dmytrieva, O. A. (2006). Numerical methods in computer science: textbook. Kyiv: BHV Publishing Group, 474 p. [In Ukrainian].
dc.relation.referencesen[21] Filts, R. V. (1994). Calculation of Taylor and Fourier polynomials and their derivatives. Synopsis of lectures on the subject "Mathematical problems of electromechanics" for students. special 1801 "Electromechanics". Lviv: State University "Lviv Polytechnic", 24 p. [In Ukrainian].
dc.relation.referencesen[22] Filts, R. V. (2010). Equilibrium calculus: monograph. Lviv: LDINTU named after Vyacheslav Chornovol, 184 p. [In Ukrainian].
dc.relation.referencesen[23] Filtz, R. V. (1994). Differentiation of tabular functions. Synopsis of lectures on the subject "Mathematical problems of electromechanics" for students of the specialty 1801 "Electromechanics". Typescript edition of the "Electric Machines" department. Lviv: State University "Lviv Polytechnic", 52 p. [In Ukrainian].
dc.relation.referencesen[24] Filz, R. V., Kotsyuba, M. V., & Hrytsiuk, Yu. I. (1991). Algorithm for computing the Taylor polynomial and its derivatives on a computer. Izvestiya vuzov. Electromechanics, No 5, 5–10. [In Russian].
dc.relation.referencesen[25] Goncharov, O. A., Vasylieva, L. V., & Yunda, A. M. (2020). Numerical methods of solving applied problems: textbook. Sumy: Sumy State University, 142 p. [In Ukrainian].
dc.relation.referencesen[26] Hanke M, Scherzer O. (1998). Error analysis of an equation error method for the identification of the diffusion coefficient in a quasi-linear parabolic differential equation. SIAM Journal on Applied Mathematics, 59(3), 1012–1027. https://doi.org/10.1137/S0036139997331628
dc.relation.referencesen[27] Hanke, M., & Scherzer, O. (2001). Inverse Problems light: Numerical differentiation. American Mathematical Monthly, 108(6), 512–521. https://doi.org/10.2307/2695705
dc.relation.referencesen[28] Herbert Egger, & Heinz W. Engl. (2005). Tikhonov regularization applied to the inverse problem of option pricing: convergence analysis and rates. Inverse Problems, 21(3), 1027–1045. https://doi.org/10.1088/0266-5611/21/3/014
dc.relation.referencesen[29] Hrytsiuk, Yu. I. (2014). Computational methods and models in scientific research: monograph. Lviv: LSU BZD Publishing House. 288 p. [In Ukrainian].
dc.relation.referencesen[30] Hrytsiuk, Yu. I., & Havrysh, V. I. (2022). Interpolation of table-given functions by Fourier polynomial. Scientific Bulletin of UNFU, 32(1), 88–102. https://doi.org/10.36930/40320414
dc.relation.referencesen[31] Hrytsiuk, Yu. I., & Havrysh, V. I. (2022). Numerical differentiation of periodic tabular-specified functions using the Fourier polynomial. Scientific Bulletin of UNFU, 32(5), 69–79. https://doi.org/10.36930/40320410
dc.relation.referencesen[32] Hrytsiuk, Yu. I., & Tushnytskyy, R. B. (2022). Interpolation of tabular functions from one independent variable using the Taylor polynomial. Ukrainian Journal of Information Technology, 4(2), 01–17. https://doi.org/10.23939/ujit2022.02.001
dc.relation.referencesen[33] Huilin Xu, & Jijun Liu. (2010). Stable numerical differentiation for the second order derivatives. Advances in Computational Mathematics, 33, 431–447. https://doi.org/10.1007/s10444-009-9132-9
dc.relation.referencesen[34] Jane Cullum. (1971). Numerical differentiation and regularization. SIAM Journal on Numerical Analysis, 8(2), 254–265. https://doi.org/10.1137/0708026
dc.relation.referencesen[35] John P. Boyd. (2002). A Comparison of Numerical Algorithms for Fourier Extension of the First, Second, and Third Kinds. Journal of Computational Physics, 178(1), 118-160. https://doi.org/10.1006/jcph.2002.7023
dc.relation.referencesen[36] Kopcha-Horyachkina, G. E. (2011). Numerical methods in computer science: educational and methodological manual, Part 1. Uzhgorod: Publishing House of Zakarpattia State University, 76 p. [In Ukrainian].
dc.relation.referencesen[37] Krylyk, L. V., Bogach, I. V., & Lisovenko, A. I. (2019). Numerical Methods. Numerical integration of functions: tutorial. Vinnytsia: VNTU, 74 p. [In Ukrainian].
dc.relation.referencesen[38] Krylyk, L. V., Bogach, I. V., & Prokopova, M. O. (2013). Computational mathematics. Interpolation and approximation of tabular data: tutorial. Vinnytsia: VNTU, 111 p. [In Ukrainian].
dc.relation.referencesen[39] Kvetny, R. N., & Bogach, I. V. (2003). Interpolation of the function of two variables according to the Lagrange method. Bulletin of the Vinnytsia Polytechnic Institute, No 6, 365–368.
dc.relation.referencesen[40] Leevan Ling. (2006). Finding Numerical Derivatives for Unstructured and Noisy Data by Multiscale Kernels. SIAM Journal on Numerical Analysis, 44(1). https://doi.org/10.1137/050630246
dc.relation.referencesen[41] Lyon, M., Picard, J. (2014). The Fourier approximation of smooth but non-periodic functions from unevenly spaced data. Advances in Computational Mathematics, 40, 1073–1092. https://doi.org/10.1007/s10444-014-9342-7
dc.relation.referencesen[42] Makarov V. L., Demkiv I. I. (2012). Interpolating integral continued fractions that do not require the substitution rule. Abstracts of the report in Kamianets-Podilsk, May 28 – June 3, 2012. Kyiv, pp. 63–64. [In Ukrainian].
dc.relation.referencesen[43] Mamchuk, V. I. (2015). Numerical methods: tutorial. Kyiv: National Aviation University, 388 p. [In Ukrainian].
dc.relation.referencesen[44] Markus Hegland, & Robert S. Anderssen. (2005). Resolution enhancement of spectra using differentiation. Inverse Problems, 21, 915. https://doi.org/10.1088/0266-5611/21/3/008
dc.relation.referencesen[45] Martin Hanke, & Otmar Scherzer. (2001)Monthly, 108(6), 512–521. https://doi.org/10.1080/00029890.2001.11919778
dc.relation.referencesen[46] Murio, D. A., Mejia, C. E., & Zhan, S. (1998). Discrete mollification and automatic numerical differentiation. Computers & Mathematics with Applications, 35(5), 1–13. https://doi.org/10.1016/S0898-1221(98)00001-7
dc.relation.referencesen[47] Ovchinnikov, P. F. (Ed.), Lisitsyn, B. M., & Mikhailenko, V. M. (1989). Higher mathematics. Kyiv: High school, 679 p. URL: http://pdf.lib.vntu.edu.ua/books/2015/Ovchin_P2_2004_792.pdf
dc.relation.referencesen[48] Pissanetzky, Sergio. (1988). Sparse Matrix Technology. Translation from English. Moscow: Mir Publishing House, 410 p. [In Russian].
dc.relation.referencesen[49] Qian, Z., Fu, C. L., Xiong, X. T., & Wei, T. (2006). Fourier truncation method for high order numerical derivatives. Applied mathematics and computation, 181(2), 940–948. https://doi.org/10.1016/j.amc.2006.01.057
dc.relation.referencesen[50] Ramm, A. G., & Smirnova, A. B. (2001). On stable numerical differentiation. Mathematics of Computation, Vol. 70, 1131–1153. https://doi.org/10.1090/S0025-5718-01-01307-2
dc.relation.referencesen[51] Rodrigo B. Platte, Lloyd N. Trefethen, & Arno B. J. Kuijlaars. (2011). Impossibility of Fast Stable Approximation of Analytic Functions from Equispaced Samples. SIAM Review, 53(2), 308-318. URL: https://www.jstor.org/stable/23065166
dc.relation.referencesen[52] Rudolf Gorenflo, & Sergio Vessella. (1991). Abel Integral Equations: Analysis and Applications. Lecture Notes in Mathematics, 1461. Berlin: Springer, 1991st Edition, 232 p. URL: https://www.amazon.com/Abel-Integral-EquationsApplications-Mathematics/dp/354053668X
dc.relation.referencesen[53] Soyoung Ahn, U. JinChoi, & Alexander G. Ramm. (2006). A scheme for stable numerical differentiation. Journal of Computational and Applied Mathematics, 186(2), 325-334. https://doi.org/10.1016/j.cam.2005.02.002
dc.relation.referencesen[54] Stanley R. Deans. (2007). The Radon Transform and Some of Its Applications (Dover Books on Mathematics). Dover Publications; Illustrated edition, 304 p. URL: https://www.amazon.com/Radon-Transform-Applications-Dover-Mathematics/dp/0486462412
dc.relation.referencesen[55] Sviridenko, A. B. (2017). Direct multiplicative methods for sparse matrices. Newton methods. Computer research and modeling, Vol. 9 No. 5, 679−703. https://doi.org/10.20537/2076-7633-2017-9-5-679-703
dc.relation.referencesen[56] Tsegelyk, H. G. (2004). Numerical methods: textbook for students. Lviv: Publishing House of the Lviv National University named after Ivan Franko, 407 p. [In Ukrainian].
dc.relation.referencesen[57] Tsegelyk, H. G. (2004). Numerical methods: textbook for university students. Lviv National University named after Ivan Franko. Lviv, 407 p. [In Ukrainian].
dc.relation.referencesen[58] Vasylyshyn, T. V., Goy, T. P., & Fedak, I. V. (2014). Integral equations: a study guide. Ivano-Frankivsk: Simyk, 222 p. URL: https://kmfa.pnu.edu.ua/wp-content/uploads/sites/64/2019/12/Vasylyshyn-T.V.-Hoi-T.P.-Fedak-I.V.-Intehralni-rivniannia.pdf
dc.relation.referencesen[59] Wan, X. Q., Wang, Y. B., & Yamamoto, M. (2006). Detection of irregular points by regularization in numerical differentiation and application to edge detection. Inverse Problems, 22(3), 1089. https://doi.org/10.1088/0266-5611/22/3/022
dc.relation.referencesen[60] Wang, Y. B., & Wei, T. (2005). Numerical differentiation for two-dimensional scattered data. Journal of Mathematical Analysis and Applications, 312(1), 121-137. https://doi.org/10.1016/j.jmaa.2005.03.025
dc.relation.referencesen[61] Wang, Y. B., Jia, X. Z., & Cheng, J. (2002). A numerical differentiation method and its application to reconstruction of discontinuity. Inverse Problems, 18(6), 1461. https://doi.org/10.1088/0266-5611/18/6/301
dc.relation.referencesen[62] Wei, T., & Hon, Y. C. (2007). Numerical differentiation by radial basis functions approximation. Advances in Computational Mathematics, 27(3), 247–272. https://doi.org/10.1007/s10444-005-9001-0
dc.relation.referencesen[63] Wei, T., Hon, Y, C., & Wang, Y. B. (2005). Reconstruction of numerical derivatives from scattered noisy data. Inverse Problems, 21(2), 657–672. https://doi.org/10.1088/0266-5611/21/2/013
dc.relation.referencesen[64] Weidong Chen. (2021). Regularized derivative interpolation for two dimensional band-limited functions. Signal Processing, 184, 107943. https://doi.org/10.1016/j.sigpro.2020.107943
dc.relation.referencesen[65] Xie, O., Zhao Z. Y. (2013). Numerical differentiation of 2d functions by a mollification method based on Legendre expansion. International Journal of Computer Science, Vol. 10(1), 729–734. URL: https://ijcsi.org/papers/IJCSI-10-1-2-729-734.pdf
dc.relation.referencesen[66] Yang, Lu. (2008). A perturbation method for numerical differentiation. Applied mathematics and computation, 199(1), 368–374. https://doi.org/10.1016/j.amc.2007.09.066
dc.relation.referencesen[67] Yong-Fu Zhang, & Chong-Jun Li. (2019). A class of multistep numerical difference schemes applied in inverse heat conduction problem with a control parameter. Inverse Problems in Science and Engineering, 27(7), 887–942. https://doi.org/10.1080/17415977.2018.1501370
dc.relation.referencesen[68] Zewen Wang, & Rongsheng Wen (2010). Numerical differentiation for high orders by an integration method. Journal of Computational and Applied Mathematics, 234(3), 941-948. https://doi.org/10.1016/j.cam.2010.01.056
dc.relation.referencesen[69] Zhenyu Zhao, & Zehong Meng. (2010). Numerical differentiation for periodic functions. Inverse Problems in Science and Engineering, 18(7), 957-969. https://doi.org/10.1080/17415977.2010.492517
dc.relation.referencesen[70] Zhenyu Zhao, Zehong Meng, & Guoqiang He. (2009). A new approach to numerical differentiation. Journal of Computational and Applied Mathematics, 232(2), 227–239. https://doi.org/10.1016/j.cam.2009.06.001
dc.relation.referencesen[71] Zhenyu Zhao, Zehong Meng, Li Xu, & Junfeng Liu. (2009). A New Mollification Method for Numerical Differentiation of 2D Periodic Functions. IEEE International Joint Conference on Computational Sciences and Optimization, 24-26 April 2009, (pp. 205-207), Sanya, China. https://doi.org/10.1109/CSO.2009.174
dc.relation.referencesen[72] Zhenyu Zhao. (2010). A truncated Legendre spectral method for solving numerical differentiation. International Journal of Computer Mathematics, 87(16), 3209–3217. https://doi.org/10.1080/00207160902974404
dc.relation.referencesen[73] Zygmund, Antoni (Author), Fefferman, Robert A. (Ed.). (2002).Trigonometric series, I, II, Cambridge Mathematical Library (3rd ed.). Cambridge University Press, 784 p. URL: https://www.amazon.com/Trigonometric-Cambridge-Mathematical-Library-Zygmund/dp/05218905
dc.relation.urihttps://doi.org/10.1080/17415977.2020.1763983
dc.relation.urihttps://www.amazon.com/Handbook-Integral-Equations-Handbooks-Mathematical/dp/1584885076
dc.relation.urihttps://doi.org/10.1080/00036811.2011.598862
dc.relation.urihttps://doi.org/10.1007/s10208-013-9158-8
dc.relation.urihttps://doi.org/10.1080/00036810500475025
dc.relation.urihttps://doi.org/10.1080/17415970600839093
dc.relation.urihttps://doi.org/10.1016/j.apm.2010.01.009
dc.relation.urihttps://doi.org/10.1002/9781118033210
dc.relation.urihttps://doi.org/10.1007/978-94-009-1740-8
dc.relation.urihttps://doi.org/10.1137/S0036139997331628
dc.relation.urihttps://doi.org/10.2307/2695705
dc.relation.urihttps://doi.org/10.1088/0266-5611/21/3/014
dc.relation.urihttps://doi.org/10.36930/40320414
dc.relation.urihttps://doi.org/10.36930/40320410
dc.relation.urihttps://doi.org/10.23939/ujit2022.02.001
dc.relation.urihttps://doi.org/10.1007/s10444-009-9132-9
dc.relation.urihttps://doi.org/10.1137/0708026
dc.relation.urihttps://doi.org/10.1006/jcph.2002.7023
dc.relation.urihttps://doi.org/10.1137/050630246
dc.relation.urihttps://doi.org/10.1007/s10444-014-9342-7
dc.relation.urihttps://doi.org/10.1088/0266-5611/21/3/008
dc.relation.urihttps://doi.org/10.1080/00029890.2001.11919778
dc.relation.urihttps://doi.org/10.1016/S0898-1221(98)00001-7
dc.relation.urihttp://pdf.lib.vntu.edu.ua/books/2015/Ovchin_P2_2004_792.pdf
dc.relation.urihttps://doi.org/10.1016/j.amc.2006.01.057
dc.relation.urihttps://doi.org/10.1090/S0025-5718-01-01307-2
dc.relation.urihttps://www.jstor.org/stable/23065166
dc.relation.urihttps://www.amazon.com/Abel-Integral-EquationsApplications-Mathematics/dp/354053668X
dc.relation.urihttps://doi.org/10.1016/j.cam.2005.02.002
dc.relation.urihttps://www.amazon.com/Radon-Transform-Applications-Dover-Mathematics/dp/0486462412
dc.relation.urihttps://doi.org/10.20537/2076-7633-2017-9-5-679-703
dc.relation.urihttps://kmfa.pnu.edu.ua/wp-content/uploads/sites/64/2019/12/Василишин-Т.В.-Гой-Т.П.-Федак-І.В.-Інтегральні-рівняння.pdf
dc.relation.urihttps://doi.org/10.1088/0266-5611/22/3/022
dc.relation.urihttps://doi.org/10.1016/j.jmaa.2005.03.025
dc.relation.urihttps://doi.org/10.1088/0266-5611/18/6/301
dc.relation.urihttps://doi.org/10.1007/s10444-005-9001-0
dc.relation.urihttps://doi.org/10.1088/0266-5611/21/2/013
dc.relation.urihttps://doi.org/10.1016/j.sigpro.2020.107943
dc.relation.urihttps://ijcsi.org/papers/IJCSI-10-1-2-729-734.pdf
dc.relation.urihttps://doi.org/10.1016/j.amc.2007.09.066
dc.relation.urihttps://doi.org/10.1080/17415977.2018.1501370
dc.relation.urihttps://doi.org/10.1016/j.cam.2010.01.056
dc.relation.urihttps://doi.org/10.1080/17415977.2010.492517
dc.relation.urihttps://doi.org/10.1016/j.cam.2009.06.001
dc.relation.urihttps://doi.org/10.1109/CSO.2009.174
dc.relation.urihttps://doi.org/10.1080/00207160902974404
dc.relation.urihttps://www.amazon.com/Trigonometric-Cambridge-Mathematical-Library-Zygmund/dp/05218905
dc.rights.holder© Національний університет “Львівська політехніка”, 2023
dc.subjectзашумлені дані
dc.subjectзгладжування функцій
dc.subjectінтерполяція табличних фунакції
dc.subjectформули центральних скінченних різниць
dc.subjectобчислення похідних
dc.subjecttaylor polynomial
dc.subjectsmoothing functions
dc.subjectinterpolation of tabular functions
dc.subjectformulas of central finite differences
dc.subjectcalculation of derivatives
dc.titleЧисельне диференціювання табличних функцій у довільно розташованих вузлах інтерполяції
dc.title.alternativeNumerical differentiation of table-given functions at arbitrarily located interpolation nodes
dc.typeArticle

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