The guaranteed performance (including convergence) of the proposed algorithms is shown in terms of suitable choices of the algorithmic parameters and the restricted isometry property (RIP) of the sensing matrix which has been widely used in the analysis of compressive sensing algorithms. The simulation...
These papers establish the fact that inexact algorithms maintain the convergence rates of and in the non-strongly convex case, subject to certain summability conditions on the sequence of errors . If the objective function is strongly convex, then these inexact methods attain the same linear ...
We have tested the performance of inexact Newton-type algorithms to solve nonlinear systems of equations arising from the SUPG/PSPG finite element formulation of steady incompressible viscoplastic flows. We employed a numerically approximated Jacobian based on Taylor’s expansion of the nonlinear convectiv...
In terms of computational costs, the Newton-type algorithms require about 20 times fewer objective function evaluations than the SCE search for SIMHYD and 50 times fewer evaluations for FUSE-536. Considering the chance of converging to the global optimum and the computational cost, we suggest that...
Quadratic Convergence of Newton-type Algorithms for Mix-complementarity Problems 混合互补问题牛顿型算法的二阶收敛性 168.160.184.82:8080 5. The selection of the horizon vector in the quasi-newton type trust region method based on the conic model 锥模型的拟牛顿型信赖域方法中的水平向量的选取 service....
Bonnans JF (1989) Local study of Newton-type algorithms for constrained problems. Proc 5th Franco-German Conf on Optimization, Dolecki S, ed. Lectures Notes in Mathematics, vol 1405. Springer-Verlag, Berlin, pp 13–24 5. Bonnans JF, Launay G (1992) An implicit trust region algorithm for...
Simplified Newton-type adaptive estimation algorithms 来自 Semantic Scholar 喜欢 0 阅读量: 24 作者: Panagiotis P. Mavridis,George V. Moustakides 摘要: A new adaptive estimation algorithm is presented. It is the result of a combination of the LMS and the fast Newton transversal filters (FNTF...
We consider a class of interior point algorithms for minimizing a twice continuously differentiable function over a closed convex set with nonempty interior. On one hand, our algirothms can be viewed as an approximate version of the generalized proximal point methods and, on the other hand, as ...
More importantly, our ID-TV algorithms serve as building blocks for solving the harder task of computing 2- (and higher)-dimensional TV proximity. We illustrate the computational benefits of our methods by applying them to several applications: (i) image de-noising; (ii) image deconvolution (...
Unlike the traditional guidance, the process to determine guidance commands by computational guidance does not require significant premission planning, gain tuning, or extensive offline design [1] but completely depends on online algorithms to cope with complex missions or dynamically evolving scenarios. ...