Multivariate Vandermonde Determinants and General Birkhoff Interpolation

In this paper, we consider the Straight Line Type Node Configuration C （SLTNCC） in multivariate polynomial interpolation as the result of different kinds of transformations of lines （such as parallel translations, rotations）. Corresponding to these transformations we define different kinds of interpolation problems for the SLTNCC. The expression of the confluent multivariate Vandermonde determinant of the coefficient matrix for each of these interpolation problems is obtained, and from this expression we conclude the related interpolation problem is unisolvent. Also, we give a kind of generalization of the SLTNCC in Section 5. As well, we obtain an expression of the interpolating polynomial for a kind of interpolation problem discussed in this paper.

A fast algorithm for multivariate Hermite interpolation

Multivariate Hermite interpolation is widely applied in many fields, such as finite element construction, inverse engineering, CAD etc.. For arbitrarily given Hermite interpolation conditions, the typical method is to compute the vanishing ideal I （the set of polynomials satisfying all the homogeneous interpolation conditions are zero） and then use a complete residue system modulo I as the interpolation basis. Thus the interpolation problem can be converted into solving a linear equation system. A generic algorithm was presented in [18], which is a generalization of BM algorithm [22] and the complexity is O（τ^3） where r represents the number of the interpolation conditions. In this paper we derive a method to obtain the residue system directly from the relative position of the points and the corresponding derivative conditions （presented by lower sets） and then use fast GEPP to solve the linear system with O（（τ ＋ 3）τ^2） operations, where τ is the displacement-rank of the coefficient matrix. In the best case τ = 1 and in the worst case τ = [τ/n], where n is the number of variables.

Some Experiments with Multivariate Objective Analysis Scheme of Heights and Winds Using Optimum Interpolation

A two-dimensional, multitvariate objective analysis scheme for simultaneous analysis of geopotential height and wind fields has been developed over Indian and adjoining region for use in numerical weather prediction. The height-height correlations calculated using daily data of four July months (1976-1979), are used to derive the other autocorrelations and cross-correlations assuming geostropic relationship. A Gaussian function is used to model the autocorrelation function. Since the scheme is multivariate the regression coefficients (weights) are matrix.Near the equator, the geostrophic approximation relating mass and wind is decoupled in a way similar to Bergman (1979). The objective analyses were made over Indian and adjoining region for 850, 700, 500, 300 and 200 hPa levels for the period from 4 July to 8 July 1979, 12 GMT. The analyses obtained using multivariate optimum interpolation scheme depict the synoptic situations satisfactorily. The analyses were also compared with the FGGE analyses (from ECMWF) and also with the station observations by computing the root mean square (RMS) errors and the RMS errors are comparable with those obtained in other similar studies.

ON HIGH DIMENSIONAL INTERPOLATION

This paper introduces the definition of the Orthogonal Type Node Configuration and discusses the corresponding multivariate Lagrange, Hermite and Birkhoff interpolation problems in high dimensional space R s(s>2). This node configuration can be considered to be a kind of extension of the Cross Type Node Configuration , in R 2 to high dimensional spaces. And the Mixed Type Node Configuration in R s(s>2) is also discussed in this paper in an example.

Multivariate Objective Analysis of Wind and Height Fields in the Tropics

The commollly used objective analysis scheme(Scheme-A) for the analysis Of wind and geopotential height smoothen the divergent component of the wind which is rather important in the tropics,specifically over convective regions.To overcome this deficiellcy, a new analysis SCheme in which divergent component is included in the statistical model of the wind forecast errors,has been proposed by Daley(1985).Following this scheme,a new set of correlahon functions of forecast errors for the indian region during monsoon season which are suitable for analysing the tropical wind are obtained.This analysis scheme(Scheme--B) as well as Scheme-A were used to make analyses for the period from 4 July to & July 1979(12 GMT) at 850,700 and 200 hpa levels over an area bounded by l.875'N to 39.375'N and 41.250'E to 108.750'E and subsequently divergent component,velocity potential are computed for both schemes.Results from both these schemes show that in the monsoon depression region the velocity potential and divergence have increased in the later case(Scheme-B).This suggests that the divergent component has been enhanced in Scheme-B and that the objechve of this study is realized to some extent.

OBTAINING EXACT INTERPOLATION MULTIVARIATE POLYNOMIAL BY APPROXIMATION

In some fields such as Mathematics Mechanization, automated reasoning and Trustworthy Computing, etc., exact results are needed. Symbolic computations are used to obtain the exact results. Symbolic computations are of high complexity. In order to improve the situation, exact interpolating methods are often proposed for the exact results and approximate interpolating methods for the ap- proximate ones. In this paper, the authors study how to obtain exact interpolation polynomial with rational coefficients by approximate interpolating methods.

ON AN EXTENSION OF ABEL-GONTSCHAROFF'S EXPANSION FORMULA

We present a constructive generalization of Abel-Gontscharoff＇s series expansion to higher dimensions. A constructive application to a problem of multivariate interpolation is also investigated. In addition, two algorithms for constructing the basis functions of the interpolants are given.

A Kind of Generalization of the Curve Type Node Configuration in R^S（S 〉 2）

A kind of generalization of the Curve Type Node Configuration is given in this paper, and it is called the generalized node configuration CTNCB in Rs(s > 2). The related multivariate polynomial interpolation problem is discussed. It is proved that the CTNCB is an appropriate node configuration for the polynomial space Pns(s > 2). And the expressions of the multivariate Vandermonde determinants that are related to the Odd Curve Type Node Configuration in R2 are also obtained.

Computing Sparse GCD of Multivariate Polynomials via Polynomial Interpolation

The problem of computing the greatest common divisor（GCD） of multivariate polynomials, as one of the most important tasks of computer algebra and symbolic computation in more general scope, has been studied extensively since the beginning of the interdisciplinary of mathematics with computer science. For many real applications such as digital image restoration and enhancement,robust control theory of nonlinear systems, L1-norm convex optimization in compressed sensing techniques, as well as algebraic decoding of Reed-Solomon and BCH codes, the concept of sparse GCD plays a core role where only the greatest common divisors with much fewer terms than the original polynomials are of interest due to the nature of problems or data structures. This paper presents two methods via multivariate polynomial interpolation which are based on the variation of Zippel＇s method and Ben-Or/Tiwari algorithm, respectively. To reduce computational complexity, probabilistic techniques and randomization are employed to deal with univariate GCD computation and univariate polynomial interpolation. The authors demonstrate the practical performance of our algorithms on a significant body of examples. The implemented experiment illustrates that our algorithms are efficient for a quite wide range of input.

THE ELLIPTIC TYPE NODE CONFIGURATION AND INTERPOLATION IN R^2

In this paper, we have obtained an expression of the bivariate Vandermonde determinant for the Elliptic Type Node Configuration in R-2, and discussed the possibility of the corresponding multivariate Lagrange, Hermite and Birkhoff interpolation.

On convergence analysis of a derivative-free trust region algorithm for constrained optimization with separable structure

In this paper,we propose a derivative-free trust region algorithm for constrained minimization problems with separable structure,where derivatives of the objective function are not available and cannot be directly approximated.At each iteration,we construct a quadratic interpolation model of the objective function around the current iterate.The new iterates are generated by minimizing the augmented Lagrangian function of this model over the trust region.The filter technique is used to ensure the feasibility and optimality of the iterative sequence.Global convergence of the proposed algorithm is proved under some suitable assumptions.

Error Formulas for Lagrange Projectors Determined by Cartesian Sets

This paper studies error formulas for Lagrange projectors determined by Cartesian sets. Cartesian sets are properly subgrids of tensor product grids. Given interpolated functions with all order continuous partial derivatives, the authors directly construct the good error formulas for Lagrange projectors determined by Cartesian sets. Owing to the special algebraic structure, such a good error formula is useful for error estimate.

ON THE DIVIDED DIFFERENCE FORM OF FAA DI BRUNO＇S FORMULA Ⅱ

In this paper, we consider the higher divided difference of a composite function f（g（t）） in which g（t） is an s-dimensional vector. By exploiting some properties from mixed partial divided differences and multivariate Newton interpolation, we generalize the divided difference form of Faà di Bruno＇s formula with a scalar argument. Moreover, a generalized Faà di Bruno＇s formula with a vector argument is derived.