Results 171 to 180 of about 318 (192)
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Newton-Type Methods in Array Processing
IEEE Signal Processing Letters, 2004Despite their good features, Newton-type methods are not usually employed in array processing due to the lack of appropriate formulas for the first- and second-order differentials. One specific property of most array processing models is that each column of the signal matrix depends only on the corresponding element of one or more parameter vectors. In
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Newton-type method for solving generalized inclusion
Numerical Algorithms, 2021zbMATH Open Web Interface contents unavailable due to conflicting licenses.
P. S. M. Santos +2 more
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Infinite-Dimensional Newton-Type Method
2019This chapter presents two numerical verification methods which are based on some infinite-dimensional fixed-point theorems. The first approach is a technique using sequential iteration. Although this method is simple and can be applied to general nonlinear functional equations in Banach spaces, the relevant compact map has to be retractive in some ...
Mitsuhiro T. Nakao +2 more
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Newton—type methods under regular smoothness
Numerical Functional Analysis and Optimization, 1996Convergence analysis of iterative methods for solving operator equations in Banach spaces depends on the smoothness degree of operators involved. A new smoothness assumption, more general and more flexible than the traditional Lipschitz smoothness, is used to carry out convergence analysis of Newton—type methods.
A. Galperin, Z. Waksman
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Newton-Type Minimization via the Lanczos Method
SIAM Journal on Numerical Analysis, 1984This paper discusses the use of the linear conjugate-gradient method (developed via the Lanczos method) in the solution of large-scale unconstrained minimization problems. It is shown how the equivalent Lanczos characterization of the linear conjugate-gradient method may be exploited to define a modified Newton method which can be applied to problems ...
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A note on Newton type iterative methods
Computing, 1984Some particular real functions are related to the so called Newton type iterative processes, i.e. iterations of the form \(x_{n+1}=x_ n-A(x_ n)^{-1}F(x_ n),\) which solve nonlinear operator equations in Banach spaces. This allows to obtain, at the same time, convergence conditions and a posteriori error estimates.
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Two-sided approximation for some Newton’s type methods
Applied Mathematics and Computation, 2014zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Zhanlav, T. +2 more
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Weak convergence conditions for Inexact Newton-type methods
Applied Mathematics and Computation, 2011zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Argyros, Ioannis K., Hilout, Saïd
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A Newton-Type Method and Applications
2018The framework of asymptotic analysis in singularly perturbed geometrical domains can be employed to produce two-term asymptotic expansions for a class of shape functionals. In Chap. 6 one-term expansions of functionals are required for algorithms of shape-topological optimization.
Antonio André Novotny +2 more
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A special newton-type optimization method
Optimization, 1992The Kuhn–Tucker conditions of an optimization problem with inequality constraints are transformed equivalently into a special nonlinear system of equations T 0(z) = 0. It is shown that Newton's method for solving this system combines two valuable properties: The local Q-quadratic convergence without assuming the strict complementary slackness condition
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