1998
DOI: 10.1023/a:1022646327085
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Convergence Analysis and Applications of the Glowinski–Le Tallec Splitting Method for Finding a Zero of the Sum of Two Maximal Monotone Operators

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Cited by 84 publications
(53 citation statements)
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“…1 Department of Mathematics, University of Lagos, Akoka, Yaba, Lagos, Nigeria. 2 General Studies Department, Federal School of Surveying, Oyo, Oyo, Nigeria.…”
Section: Competing Interestsmentioning
confidence: 99%
“…1 Department of Mathematics, University of Lagos, Akoka, Yaba, Lagos, Nigeria. 2 General Studies Department, Federal School of Surveying, Oyo, Oyo, Nigeria.…”
Section: Competing Interestsmentioning
confidence: 99%
“…The mature methods are least square method [6] and improved least square method [7]. Other methods include error prediction estimation method [8], IV estimation method [9] and the mathematical approximation method, such as the forward-backward method [10], Yule-Walker method, Burg method [11], the geometric lattice method [12]. Among them, IV estimation method is simple at some extent, and it can be used under many circumstances [13].The unbiased estimation value can be obtained, when the residuals are auto-regression [14,15].…”
Section: Estimation Of the Parametersmentioning
confidence: 99%
“…Glowinski and Le Tallec [9] used three-step iterative algorithms to find the approximate solutions of the elastoviscoplasticity problem, liquid crystal theory, and eigenvalue computation, and they showed that three-step approximations perform better numerically. Haubruge et al [11] studied the convergence analysis of three-step iterative algorithms of Glowinski and Le Tallec [9] and applied these algorithms to obtain new splitting-type algorithms for solving variational inequalities, separable convex programming, and minimization of a sum of convex functions. They also proved that three-step iterations lead to highly parallelized algorithms under certain conditions.…”
Section: Introductionmentioning
confidence: 99%
“…It has been shown in [11,21,22] that three step iterative algorithms are a natural generalization of the splitting methods for solving partial differential equations (inclusions). For applications of splitting and decomposition methods, see [9,11,21,22] and the references therein.…”
Section: Introductionmentioning
confidence: 99%
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