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Local convergence analysis for Chebyshev’s method
Journal of Applied Mathematics and Computing, 2018zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Kumari, Chandni, Parida, P. K.
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The Local Convergence of Boolean Networks With Disturbances
IEEE Transactions on Circuits and Systems II: Express Briefs, 2019This brief is devoted to studying the local convergence of Boolean networks (BNs) with disturbances. On the one hand, the algebraic form of a BN with ${n}$ nodes and ${n}$ disturbances is obtained by semi-tensor product (STP) of matrices and, based on the algebraic expression, some conditions of the local convergence are presented.
Bowen Li 0006 +3 more
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Bornological Convergence in Locally Convex Cones
Mediterranean Journal of Mathematics, 2015La notion de cône (la multiplication y est associative, mais non nécessairement commutative) localement convexe est bien connue comme celle de partie d'un espace vectoriel de même nature. On adapte sur un tel cône une structure bornologique classique, dont les AA. développent toutes les caractérisques. -- On regrettera l'absence d'exemples.
Ayaseh, Davood, Ranjbari, Asghar
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2010
Proving convergence of the various optimization algorithms is a delicate exercise. In general, it is helpful to consider local and global convergence patterns separately. The local convergence rate of an algorithm provides a useful benchmark for comparing it to other algorithms. On this basis, Newton’s method wins hands down. However, the tradeoffs are
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Proving convergence of the various optimization algorithms is a delicate exercise. In general, it is helpful to consider local and global convergence patterns separately. The local convergence rate of an algorithm provides a useful benchmark for comparing it to other algorithms. On this basis, Newton’s method wins hands down. However, the tradeoffs are
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Convergence of Distributed Localization With Alternating Normals
IEEE Transactions on Robotics, 2016This paper presents the alternating-normal iterative method, a novel algorithm that uses angle-of-arrival (or bearing) measurements for relative positioning of networked collaborating robots moving in three dimensions. The method is decentralized, with robots exploiting communication to iteratively refine measurements and enforce geometric consistency.
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Convergence of Local Minimizers
2013The fundamental theorem of Γ-convergence can be generalized when we have strict local minimizers of the Γ-limit, in which case we are often able to deduce the existence and convergence of local minimizers of the converging sequence. This version of the fundamental theorem of Γ-convergence can be coupled with scaling arguments, which may give existence ...
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2022
Improvements in information and communication technologies have evolved the way of traditional broadcasting. This evolvement is currently being experienced in press, eliminating the specific and clear lines of every kind of medium. Changing news production/distribution process as well as readers' consumption tendencies have brought up some kind of
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Improvements in information and communication technologies have evolved the way of traditional broadcasting. This evolvement is currently being experienced in press, eliminating the specific and clear lines of every kind of medium. Changing news production/distribution process as well as readers' consumption tendencies have brought up some kind of
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On Convergence of Projections in Locally Convex Spaces
Canadian Mathematical Bulletin, 1966This note is concerned with the extension to locally convex spaces of a theorem of J. Y. Barry [ 1 ]. The basic assumptions are as follows. E is a separated locally convex topological vector space, henceforth assumed to be barreled. E' is its strong dual. For any subset A of E, we denote by w(A) the closure of A in the σ-(E, E')-topology. See [ 2 ] for
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On the global stabilization of locally convergent algorithms
Automatica, 1976There are a number of algorithms in the literature which both theoretically and empirically are known to be only locally convergent. These include such well known algorithms as secant, Newton, quasi-Newton and primal-dual algorithms. Locally, these algorithms tend to be highly efficient.
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Local convergence of the method of multipliers
Mathematische Operationsforschung und Statistik. Series Optimization, 1980openaire +2 more sources