In a recent paper, the authors have proved results characterizing convexity-preserving maps deened on a subset of a not-necessarily nite dimensional real vector space as projective maps. The purpose of this note is threefold. First, we state a theorem characterizing continuous, injective, convexity-preserving maps from a relatively open, connected subset of an aane subspace of R m into R n as p...

1. This note summarizes a paper [4] to appear in full elsewhere. It presents an algorithm for the minimization of a general (not necessarily differentiable) convex function. Its central idea is the construction of descent directions as projections of the origin onto the convex hull of previously calculated subgradients as long as satisfactory progress can be made. Using projection to obtain a d...

<p style='text-indent:20px;'>Memoryless quasi–Newton updating formulas of BFGS (Broyden–Fletcher–Goldfarb–Shanno) and DFP (Davidon–Fletcher–Powell) are scaled using well-structured diagonal matrices. In the scaling approach, elements as well eigenvalues memoryless play significant roles. Convergence analysis given diagonally methods is discussed. At last, performance numerically tested on...

In this paper we construct C continuous piecewise quadratic hierarchical bases on Powell–Sabin triangulations of arbitrary polygonal domains in R. Our bases are of Lagrange type instead of the usual Hermite type and we prove that they form strongly stable Riesz bases for the Sobolev spaces Hs(Ω) with s ∈ (1, 5 2 ). Especially the case s = 2 is of interest, because we can use the corresponding h...

In many engineering applications, it is often the case that observations are only available in interval form. this note, by using expectation-maximization (EM) algorithm, parameter estimation of Weibull distribution with interval-censored data considered. The estimates obtained EM algorithm compared those conventional Newton-type methods, including Davidon–Fletcher–Powell (DFP) and Berndt–Hall–...

In matrix analysis, the scaling technique reduces chances of an ill-conditioning matrix. This article proposes a one-parameter memoryless Davidon–Fletcher–Powell (DFP) algorithm for solving system monotone nonlinear equations with convex constraints. The measure function that involves all eigenvalues DFP is minimized to obtain parameter’s optimal value. resulting and derivative-free low memory ...

In tackling the problem of minimizing the deformation of a loaded structure, by varying the shape of the original structure, past second order optimization efforts have focused on general Newton techniques like the Davidon-Fletcher-Powell (DFP) update formula and the BroydenFletcher-Goldfarb-Shanno (BFGS) formula which iteratively build estimates of the structure's Hessian. This thesis bypasses...