Computational experience with globally convergent descent methods for large sparse systems of nonlinear equations

This paper is devoted to globally convergent Armijo-type descent methods for solving large sparse systems of nonlinear equations. These methods include the discrete Newtcin method and a broad class of Newton-like methods based on various approximations of the Jacobian matrix. We propose a general th...

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Veröffentlicht in:	Optimization methods & software 1998-01, Vol.8 (3-4), p.201-223
Hauptverfasser:	Luksan, L, Vlcek, J
Format:	Artikel
Sprache:	eng
Schlagworte:	Armijo-Type Descent Methods Computational Experiments Conjugate Gradient Type Methods Global Convergence Newton-Like Methods Inexact Methods Nonlinear Equations Nonsymmetric Linear Systems Residual Smoothing
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