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An improved grey wolf optimization algorithm for 3-D UWB indoor positioning. [PDF]

PLoS One
Zhou J, Li B, Yang S, Liu C.
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Convergence Analysis for Anderson Acceleration

SIAM Journal on Numerical Analysis, 2015
Summary: \(\mathrm{Anderson}(m)\) is a method for acceleration of fixed point iteration which stores \(m+1\) prior evaluations of the fixed point map and computes the new iteration as a linear combination of those evaluations. \(\mathrm{Anderson}(0)\) is fixed point iteration.
Alex Toth, C. T. Kelley
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Convergence Analysis of Stochastic Algorithms

Mathematics of Operations Research, 1996
This paper investigates asymptotic convergence to stationary points of gradient descent algorithms where the functions involved are not available in closed form but are approximated by sequences of random functions. The algorithms take large stepsizes and use progressively finer precision at successive iterations.
Alexander Shapiro 0001, Yorai Wardi
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Turbo-equalization: convergence analysis

2001 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.01CH37221), 2002
We investigate a sub-optimal iterative receiver for joint equalization and decoding called a turbo-equalizer. We view the evolution of the error variance of the transmitted symbols through iterative processing, obtaining the convergence analysis. This allows us to predict the asymptotic performance (when the turbo-equalizer has converged) but also the ...
Aline Roumy, Alex J. Grant, Inbar Fijalkow, Paul D. Alexander, Didier Pirez   +4 more
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Convergence analysis of cautious control

Science in China Series F, 2006
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Yanxia Zhang, Lei Guo 0001
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A bibliometric analysis on innovation convergence

Library Hi Tech, 2022
PurposeInnovation convergence is critical to national or regional economic growth patterns. This article provides a systematic review of innovation convergence research through qualitative discussions combined with bibliometric methods. Through this article, researchers interested in the field of innovation convergence can quickly understand the ...
Wenyue Cui, Jie Tang, Zhipeng Zhang, Xin Dai 0010   +3 more
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The Possibility of Analysis: Convergence and Proofs of Convergence

2018
We raise the issues of convergence and proofs of convergence for processes of philosophical analysis in the styles of Russell and early Wittgenstein. Here, ‘convergence’ means that the process results, once started on its inputs, in completely analyzed propositions.
David Fisher, David Charles McCarty
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On the Convergence Analysis of the MINLIP Estimator

IFAC Proceedings Volumes, 2012
Abstract This paper discusses convergence properties of the recently introduced MINimal LIPschitz (MINLIP) estimator for the identification of a monotone Wiener model from noiseless input-output measurements. This estimator is entirely build around the notion of complexity control, making the approach conceptual quite different from traditional ...
Pelckmans, K., Dai, L., Bai, E.
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Convergence Analysis of Metaheuristics

2009
In this tutorial, an overview on the basic techniques for proving convergence of metaheuristics to optimal (or sufficiently good) solutions is given. The presentation is kept as independent of special metaheuristic fields as possible by the introduction of a generic metaheuristic algorithm.
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Convergence analysis of the Hopmoc method

International Journal of Computer Mathematics, 2009
The Hopmoc method combines concepts of the modified method of characteristics (MMOC) and the Hopscotch method. First, Hopmoc resembles Hopscotch because it decomposes the set of grid points into two subsets. Namely, both subsets have their unknowns separately updated within one semi-step. Furthermore, each subset undergoes one explicit and one implicit
Oliveira, Simoni R. de, Oliveira, Sanderson L. Gonzaga de, Kischinhevsky, Mauricio   +2 more
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