The Order of Approximation by(0,1,…,q) Hermite-Fejer Interpolation Polynomials at Nearly Fejer's Points

Suppose that the outer mapping function of domain D has its second continuous derivatives. In this paper, the order proximation by (0,1,…,q) Hermite-Fejer interpolating polynomials at nearly Fejer's points of function of class A(D) are presented. Moreover in general the order of approximation is sharp.

ORDER OF MEAN APPROXIMATION BY MIXED QUASI HERMITE-FEJER INTERPOLATION

In this paper we introduce a new kind of the mixed Hermite--Fejér interpolation with boundary condi- tions and obtain the mean approximation order.Our results include a new theorem of Varma and Prasad.Be- sides,we also get some other results about the mean approximation.

ON THE EXACT DEGREE OF APPROXIMATION BY HERMITE-FEJER INTERPOLATION BASED ON THE LAGUERRE ABSCISSAS

For the nonpositive Hermite-Fejér interpolation based on the Laguerre abscissas, a pointwise two-sided estimate of the degree of approximation in the aleatoric interval [0, A] is first established.

MEAN CONVERGENCE OF HERMITE-FEJER TYPE INTERPOLATION ON AN ARBITRARY SYSTEM OF NODES

In this paper sufficient conditions for mean convergence and rate of convergence of Hermite-Fejer type interpolation in the Lp norm on an arbitrary system of nodes are presented.

HERMITE-FEJER TYPE INTERPOLATION OF HIGHER ORDER

The paperintroduces Herm ite-Fejértype(Herm ite type) interpolation ofhigherorder denoted by Smn (f)(Sm n(f)), and gives som e basic properties including expression form ulas, convergence relationship betw een Sm n(f) and Hmn(f) (Herm ite-Fejérinterpolation ofhigheror- der), and the saturation ofSmn(f).

MEAN CONVERGENCE OF HERMITE-FEJER TYPE INTERPOLATION

L' convergence of Hermite-Fejer interpolation and quasi-Hermite-Fejer interpolation based upon ze- ros of general orthogonal polynomials is investigated. This paper 'almost' characterizes such convergence for all continuous functions.

Uniform Convergence of Higher Order Quasi Hermite-Fejer Interpolation

Let Xn={xkn=cosθkn: θkn=（kπ）/（n+1）, 1≤k≤n}be the node system which consists ofroots of Un （x） =（sin（n+1）θ）/（sinθ）（x=cosθ θ∈[0,π]）, the second kind Chebyshevpolynomical. All the symbols below have the same meaning as Ref. [1]if notspecifically defined. We shall consider a kind of new interpolating problem in thisnote. For any non-negative integer q and f∈C[-1, 1], it is well known that thepolynomial Qnq（f）∈ПN （N=2（q+1） （n+1） -1） satisfying the following conditions isuniquely determined:Qnq(f, xkn) =f(xkn), 1≤k≤n; Qnq（f,±1）=f（±1）,Qnqj(f,xkn)=cjkn, 1≤k≤n,1≤j≤2q+1,Qnqj（f,1）=djn, Qnqj（f,-1）=gjn, 1≤j≤q,where cjkn,djn, gjnare any given real numbers. Qnq（f）is called the higher orderquasi Hermite-Fejer interpolation of f.We

ON THE SATURATION OF L_w^p-APPROXIMATION BY (O-q'-q) TYPE HERMITE-FEJER INTERPOLATING POLYNOMIALS

The 'o' saturation theorem and the degree of Lwp, approximation by (0 - q' - q) type Hermite-Fejer interpolating polynomials for mean convergence are obtained.

Suitable region of dynamic optimal interpolation for efficiently altimetry sea surface height mapping

The dynamic optimal interpolation(DOI)method is a technique based on quasi-geostrophic dynamics for merging multi-satellite altimeter along-track observations to generate gridded absolute dynamic topography(ADT).Compared with the linear optimal interpolation(LOI)method,the DOI method can improve the accuracy of gridded ADT locally but with low computational efficiency.Consequently,considering both computational efficiency and accuracy,the DOI method is more suitable to be used only for regional applications.In this study,we propose to evaluate the suitable region for applying the DOI method based on the correlation between the absolute value of the Jacobian operator of the geostrophic stream function and the improvement achieved by the DOI method.After verifying the LOI and DOI methods,the suitable region was investigated in three typical areas:the Gulf Stream(25°N-50°N,55°W-80°W),the Japanese Kuroshio(25°N-45°N,135°E-155°E),and the South China Sea(5°N-25°N,100°E-125°E).We propose to use the DOI method only in regions outside the equatorial region and where the absolute value of the Jacobian operator of the geostrophic stream function is higher than1×10^(-11).

Research on Interpolation Method for Missing Electricity Consumption Data

Missing value is one of the main factors that cause dirty data.Without high-quality data,there will be no reliable analysis results and precise decision-making.Therefore,the data warehouse needs to integrate high-quality data consistently.In the power system,the electricity consumption data of some large users cannot be normally collected resulting in missing data,which affects the calculation of power supply and eventually leads to a large error in the daily power line loss rate.For the problem of missing electricity consumption data,this study proposes a group method of data handling(GMDH)based data interpolation method in distribution power networks and applies it in the analysis of actually collected electricity data.First,the dependent and independent variables are defined from the original data,and the upper and lower limits of missing values are determined according to prior knowledge or existing data information.All missing data are randomly interpolated within the upper and lower limits.Then,the GMDH network is established to obtain the optimal complexity model,which is used to predict the missing data to replace the last imputed electricity consumption data.At last,this process is implemented iteratively until the missing values do not change.Under a relatively small noise level(α=0.25),the proposed approach achieves a maximum error of no more than 0.605%.Experimental findings demonstrate the efficacy and feasibility of the proposed approach,which realizes the transformation from incomplete data to complete data.Also,this proposed data interpolation approach provides a strong basis for the electricity theft diagnosis and metering fault analysis of electricity enterprises.

Integer multiple quantum image scaling based on NEQR and bicubic interpolation

As a branch of quantum image processing,quantum image scaling has been widely studied.However,most of the existing quantum image scaling algorithms are based on nearest-neighbor interpolation and bilinear interpolation,the quantum version of bicubic interpolation has not yet been studied.In this work,we present the first quantum image scaling scheme for bicubic interpolation based on the novel enhanced quantum representation(NEQR).Our scheme can realize synchronous enlargement and reduction of the image with the size of 2^(n)×2^(n) by integral multiple.Firstly,the image is represented by NEQR and the original image coordinates are obtained through multiple CNOT modules.Then,16 neighborhood pixels are obtained by quantum operation circuits,and the corresponding weights of these pixels are calculated by quantum arithmetic modules.Finally,a quantum matrix operation,instead of a classical convolution operation,is used to realize the sum of convolution of these pixels.Through simulation experiments and complexity analysis,we demonstrate that our scheme achieves exponential speedup over the classical bicubic interpolation algorithm,and has better effect than the quantum version of bilinear interpolation.

Wavelet Multi-Resolution Interpolation Galerkin Method for Linear Singularly Perturbed Boundary Value Problems

In this study,a wavelet multi-resolution interpolation Galerkin method(WMIGM)is proposed to solve linear singularly perturbed boundary value problems.Unlike conventional wavelet schemes,the proposed algorithm can be readily extended to special node generation techniques,such as the Shishkin node.Such a wavelet method allows a high degree of local refinement of the nodal distribution to efficiently capture localized steep gradients.All the shape functions possess the Kronecker delta property,making the imposition of boundary conditions as easy as that in the finite element method.Four numerical examples are studied to demonstrate the validity and accuracy of the proposedwavelet method.The results showthat the use ofmodified Shishkin nodes can significantly reduce numerical oscillation near the boundary layer.Compared with many other methods,the proposed method possesses satisfactory accuracy and efficiency.The theoretical and numerical results demonstrate that the order of theε-uniform convergence of this wavelet method can reach 5.

Comparison of Methods for Nitrate Interpolation in Wells in Aguascalientes, Mexico

The accuracy of interpolation models applied to groundwater depends, among other factors, on the interpolation method chosen. Therefore, it is necessary to compare different approaches. For this, different methods of interpolation of nitrate concentrations were contrasted in sixty-seven wells in an aquifer in Aguascalientes, Mexico. Four general interpolation methods were used in ArcGIS 10.5 to make the maps: IDW, Kriging, Natural Neighbor and Spline. In the modeling, only method type was varied. The input parameters (location, temporality, and nitrate concentration) were the same in the four interpolations;despite this, different maximum and minimum values were obtained for each interpolation method: for IDW, 0.2 to 22.0 mg/l, for Kriging, 3.5 to 16.5 mg/l, for Natural Neighbor, 0.3 to 21.7 mg/l and for Spline −30.8 to 37.2 mg/l. Finally, an assessment of the maps obtained was conducted by comparing them with the Official Mexican Standard (OMS), where 24 of the 67 wells were found outside the 10 mg/l that the OMS establishes as maximum permissible limit for human consumption. Taking as a starting point the measured values of nitrates (0.25 to 22.12 mg/l), as well as the spatial distribution of the interpolated values, it was determined that the Krigging method best fitted the data measured in the wells within the studied aquifer.

Comparison of Spatial Interpolation Methods of Precipitation Data in Central Macedonia, Greece

The purpose of this paper is to investigate the spatial interpolation of rainfall variability with deterministic and geostatic inspections in the Prefecture of Kilkis (Greece). The precipitation data where recorded from 12 meteorological stations in the Prefecture of Kilkis for 36 hydrological years (1973-2008). The cumulative monthly values of rainfall were studied on an annual and seasonal basis as well as during the arid-dry season. In the deterministic tests, the I.D.W. and R.B.F. checks were inspected, while in the geostatic tests, Ordinary Kriging and Universal Kriging respectively. The selection of the optimum method was made based on the least Root Mean Square Error (R.M.S.E.), as well as on the Mean Error (M.E.), as assessed by the cross validation analysis. The geostatical Kriging also considered the impact of isotropy and anisotropy across all time periods of data collection. Moreover, for Universal Kriging, the study explored spherical, exponential and Gaussian models in various combinations. Geostatistical techniques consistently demonstrated greater reliability than deterministic techniques across all time periods of data collection. Specifically, during the annual period, anisotropy was the prevailing characteristic in geostatistical techniques. Moreover, the results for the irrigation and seasonal periods were generally comparable, with few exceptions where isotropic methods yielded lower (R.M.S.E.) in some seasonal observations.

The Mean Convergence Order of Extended Hermite-Fejér Interpolation Operators

Weighted Lp mean convergence of Extended Hermite-Fejer operators based on the zeros of orthogonal polynomials with respct to the general weight and Jacobi weight is investigated. Suf ficient conditions for such convergence for all continuous functions are given.

The Comparison of Spatial Interpolation Methods on Temperature and Precipitation of Sanjiangyuan Area

In order to get the spatial grid data of monthly precipitation and monthly average temperature of Sanjiangyuan area, the Co-Kriging (COK) and thin plate smoothing splines(TPS) interpolation methods were applied by using the climate data during 1971-2000 of 58 meteorological stations around Qinghai Province and the 3 arc-second digital elevation model (DEM) data. The performance was evaluated by the smallest statistical errors by general cross validation (GCV). Root-mean-squared predicted errors (RMSE) and mean absolute errors (MAE) were used to compare the performance of the two methods. The results showed that: 1) After combing covariates into the models, both methods performed better; 2) The performance of TPS was significantly better than COK: for monthly average temperature, the RMSE derived from TPS was 69.48% higher than COK, as MAE increased by 70.56%. And for monthly precipitation, the RMSE derived from TPS was 28.07% higher than COK, as MAE increased by 29.06%.

Analysis of radial basis function interpolation approach

The radial basis function （RBF） interpolation approach proposed by Freedman is used to solve inverse problems encountered in well-logging and other petrophysical issues. The approach is to predict petrophysical properties in the laboratory on the basis of physical rock datasets, which include the formation factor, viscosity, permeability, and molecular composition. However, this approach does not consider the effect of spatial distribution of the calibration data on the interpolation result. This study proposes a new RBF interpolation approach based on the Freedman＇s RBF interpolation approach, by which the unit basis functions are uniformly populated in the space domain. The inverse results of the two approaches are comparatively analyzed by using our datasets. We determine that although the interpolation effects of the two approaches are equivalent, the new approach is more flexible and beneficial for reducing the number of basis functions when the database is large, resulting in simplification of the interpolation function expression. However, the predicted results of the central data are not sufficiently satisfied when the data clusters are far apart.

Application of the Delaunay triangulation interpolation in distortion XRII image

To alleviate the distortion of XRII X-ray image intensifier images in the C-arm CT computer tomography imaging system an algorithm based on the Delaunay triangulation interpolation is proposed.First the causes of the phenomenon the classical correction algorithms and the Delaunay triangulation interpolation are analyzed.Then the algorithm procedure is explained using flow charts and illustrations. Finally experiments are described to demonstrate its effectiveness and feasibility. Experimental results demonstrate that the Delaunay triangulation interpolation can have the following effects.In the case of the same center the root mean square distances RMSD and standard deviation STD between the corrected image with Delaunay triangulation interpolation and the ideal image are 5.760 4 ×10 -14 and 5.354 2 ×10 -14 respectively.They increase to 1.790 3 2.388 8 2.338 8 and 1.262 0 1.268 1 1.202 6 after applying the quartic polynomial model L1 and model L2 to the distorted images respectively.The RMSDs and STDs between the corrected image with the Delaunay triangulation interpolation and the ideal image are 2.489 × 10 -13 and 2.449 8 ×10 -13 when their centers do not coincide. When the quartic polynomial model L1 and model L2 are applied to the distorted images they are 1.770 3 2.388 8 2.338 8 and 1.269 9 1.268 1 1.202 6 respectively.

修整HERMITE-FEJER插值在ORLICZ空间中的逼近(英文)

给出了不等式‖ＰＮ‖（Ｍ）Ｗ≤Ｃｉｎｆα｛α＞０：１ｎｑｊ＝０ｎｋ＝１Ｍ［１α（１－ｘ２ｋｎ）ｊ｜ＰＮ（ｊ）（ｘｋ）｜］≤１｝其中Ｎ＝（ｑ＋１）ｎ－１，ＰＮ（ｘ）为阶≤Ｎ的代数多项式，ｘｋ（ｋ＝１，２，…，ｎ）为第一类Ｃｈｅｂｙ－ｓｈｅｖ多项式的零点．讨论了此不等式的应用．

修正高阶Hermite插值及Hermite-Fejer插值在L_ω～p空间中逼近的正逆定理(英文)

在L_ω～p空间中引入了一种 K-泛函并由此建立了一种以第一类 Chebyshev多项式的零点为结点的三种修正高阶 Hermite-Fejer插值多项式及一种修正的高阶 Hermite插值多项式在L_ω～p空间中逼近的正逆定理. 文中的结果说明,对于这几种修正高阶多项式插值的逼近问题而言,正定理的解决意味着逆定理的解决.