To prove that a polynomial is nonnegative on R one can try to show that it is a sum of squares of polynomials (SOS). The latter problem is now known to be reducible to a semidefinite programming (SDP) computation much faster than classical algebraic methods (see, e.g., [Par03]), thus enabling new speed-ups in algebraic optimization. However, exactly how often nonnegative polynomials are in fact...

This research proposes a computation approach to address the evaluation of end product machining accuracy in elliptical surfaced helical pipe bending using 6dof parallel manipulator as a pipe bender. The target end product is wearable metal muscle supporters used in build-to-order welfare product manufacturing. This paper proposes a product testing model that mainly corrects the surface directi...

a new approach utilizing newton method and homotopy analysis method (ham) is proposed for solving nonlinear system of equations. accelerating the rate of convergence of ham, and obtaining a global quadratic rate of convergence are the main purposes of this approach. the numerical results demonstrate the efficiency and the performance of proposed approach. the comparison with conventional homoto...

one of the most valuable and important application of artificial satellites in geodetic sciences is recovery of the earth's gravity field. orbits of satellites either gravimetric or nongravimetric are analyzed to improve the earth's gravity field. gravimetric satellites are launched at low altitudes to observe gravity field in more detail. grace twin satellites are the second spacecra...

The Helmert transformation is used in geodesy. It transforms a set of points into another by rotation, scaling and translation. When both sets of points are given, then least squares can be used to solve the inverse problem of determining the parameters. In particular, the parameters of the so-called 7 parameter transformation can be obtained by standard methods. In this note, it is shown how a...

This paper is concerned with estimating the solutions of numerically ill-posed least squares problems through Tikhonov regularization. Given a priori estimates on the covariance structure of errors in the measurement data b, and a suitable statistically-chosen σ, the Tikhonov regularized least squares functional J(σ) = ‖Ax − b‖2Wb + 1/σ 2‖D(x − x0)‖2, evaluated at its minimizer x(σ), approximat...

Résumé. Les algorithmes de boosting de Newton Support Vector Machine (NSVM), Proximal Support Vector Machine (PSVM) et Least-Squares Support Vector Machine (LS-SVM) que nous présentons visent à la classification de très grands ensembles de données sur des machines standard. Nous présentons une extension des algorithmes de NSVM, PSVM et LS-SVM, pour construire des algorithmes de boosting. A cett...

The purpose of this paper is two-fold. Firstly, we explore some of the intimate connections between discrete least squares processes and quadratures. Secondly, we present an algorithm to construct Gauss-type integration formulas, and consider briefly the method proposed by Gautschi [2].

It is known that the norm of the solution to a weighted linear least-squares problem is uniformly bounded for the set of diagonally dominant symmetric positive definite weight matrices. This result is extended to weight matrices that are nonnegative linear combinations of symmetric positive semidefinite matrices. Further, results are given concerning the strong connection between the boundednes...