Concept

Shanks transformation

Related publications (7)

On Preconditioning of Decentralized Gradient-Descent When Solving a System of Linear Equations

This article considers solving an overdetermined system of linear equations in peer-to-peer multiagent networks. The network is assumed to be synchronous and strongly connected. Each agent has a set of local data points, and their goal is to compute a line ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2022

Decentralized Proximal Gradient Algorithms With Linear Convergence Rates

Ali H. Sayed, Kun Yuan, Sulaiman A S A E Alghunaim

This article studies a class of nonsmooth decentralized multiagent optimization problems where the agents aim at minimizing a sum of local strongly-convex smooth components plus a common nonsmooth term. We propose a general primal-dual algorithmic framewor ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2021

Analysis of a Plane Wave-Excited Subwavelength Circular Aperture in a Planar Conducting Screen Illuminating a Multilayer Uniaxial Sample

Juan Ramon Mosig, Krzysztof Michalski

A spectral domain analysis is presented of a plane wave-excited subwavelength circular aperture in a planar perfectly conducting screen in close proximity to a multilayer stack, which may comprise uniaxially anisotropic slices. The formulation employs the ...

Institute of Electrical and Electronics Engineers2015

Sufficient Conditions for Feasibility and Optimality of Real-Time Optimization Schemes - II. Implementation Issues

Dominique Bonvin, Grégory François, Gene Bunin

The idea of iterative process optimization based on collected output measurements, or "real-time optimization" (RTO), has gained much prominence in recent decades, with many RTO algorithms being proposed, researched, and developed. While the essential goal ...

arXiv:1308.26252013

Unsupervised image segmentation using a telegraph parameterization of Pickard random fields

Andrea Ridolfi

This communication presents a nonsupervised three-dimensional segmentation method based upon a discrete-level unilateral Markov field model for the labels and conditionally Gaussian densities for the observed voxels. Such models have been shown to yield nu ...

Springer Verlag2001

Maximum Likelihood Estimation of Hidden Markov Model Parameters, with Application to Medical Image Segmentation

Andrea Ridolfi

We address the problem of a non-supervised bidimensional segmentation method based upon a discrete-level unilateral Markov field model for the labels and conditionaly Gaussian densities for the observed voxels. Such models have been shown to yield numerica ...

1997

A subspace forward iteration method for solving the quadratic eigenproblem associated with the FDE formulation

Thomas Gmür

This paper presents the development of an efficient and numerically stable algorithm for accurately computing the eigensolutions of the quadratic real symmetric eigenproblem arising in the finite dynamic element (FDE) formulation. Closely related to the su ...

1990

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