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Estimation of the regression function by Legendre wavelets | ||
Iranian Journal of Numerical Analysis and Optimization | ||
مقاله 1، دوره 12، Issue 3 (Special Issue) - On the occasion of the 75th birthday of Professor A. Vahidian and Professor F. Toutounian - شماره پیاپی 23، بهمن 2022، صفحه 497-512 اصل مقاله (334.99 K) | ||
نوع مقاله: Research Article | ||
شناسه دیجیتال (DOI): 10.22067/ijnao.2022.73876.1079 | ||
نویسندگان | ||
M. Hamzehnejad* 1؛ M.M. Hosseini2؛ A. Salemi2 | ||
1Department of Mathematic, Graduate University of Advanced Technology, Kerman, Iran. | ||
2Department of Applied Mathematics and Mahani Mathematical Research Center, Shahid Bahonar University of Kerman, Kerman, Iran. | ||
چکیده | ||
We estimate a function f with N independent observations by using Leg-endre wavelets operational matrices. The function f is approximated with the solution of a special minimization problem. We introduce an explicit expression for the penalty term by Legendre wavelets operational matrices. Also, we obtain a new upper bound on the approximation error of a differentiable function f using the partial sums of the Legendre wavelets. The validity and ability of these operational matrices are shown by several examples of real-world problems with some constraints. An accurate ap-proximation of the regression function is obtained by the Legendre wavelets estimator. Furthermore, the proposed estimation is compared with a non-parametric regression algorithm and the capability of this estimation is illustrated. | ||
کلیدواژهها | ||
Legendre wavelet؛ Operational matrix؛ Wavelet approximation؛ Regression function؛ Error analysis | ||
مراجع | ||
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