Currently, there are various approaches to constructing quadrature formulas


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Currently, there are various approaches to constructing quadrature formulas. One of them is the classical approach to constructing quadrature formulas, which requires the accuracy of the polynomial formula for the highest possible order. Another of them is the functional approach to constructing quadrature formulas. In this case, the quadrature formula is created so that it is possible to minimize the norm of the error functional in a given Banach space [1,2,3,4]. Article [5] introduces novel and efficient quadrature formulas that combine the estimation of a function and its first derivative at evenly spaced data points, with a specific emphasis on enhancing computational efficiency in terms of both cost and time. The objective of the research presented in work [6] is to simplify the computation of the components involved in the integral transformation, denoted as and .The analytical expressions for these components encompass definite integrals. Instead of the Newton-Cotes formulas, it is proposed to use non-trivial quadrature formulas with unevenly distributed integration points. The quadrature method plays an essential role in the approximate solution of integral equations. In [7], the trapezoidal numerical integration formula is used to solve the Fredholm-Hammerstein integral equations. In [8], the perturbed Milne quadrature rule was derived for -fold differentiable functions. The following articles [9-15] create optimal quadrature formulas for different Hilbert spaces. Additionally, precise estimates of the created formulas are provided. The work consists of the following sections: 1 - introduction, 2 - problem statement section. In the second section, using the extremal function, the general form of the norm of the error functional is found. In Section 3, for the coefficients of the quadrature formula under consideration in the space , a system of linear equations of the Wiener-Hopf type was obtained; at the same time, the analytical form of the optimal coefficients of the quadrature formulas (1.1) was found for and in the space . In Section 4, the error functional (1.3) of the quadrature formula (1.1) is calculated for and . Section 5 provides numerical results.
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