Results 221 to 230 of about 9,063 (254)

Quasi-Newton Methods

2019
The Quasi-Newton methods do not compute the Hessian of nonlinear functions. The Hessian is updated by analyzing successive gradient vectors instead. The Quasi-Newton algorithm was first proposed by William C. Davidon, a physicist while working at Argonne National Laboratory, United States in 1959.
Shashi Kant Mishra, Bhagwat Ram
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A frequency domain quasi-Newton algorithm

Signal Processing, 1995
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Kostas Berberidis, Jacques Palicot
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Sparse quasi‐Newton LDU updates

International Journal for Numerical Methods in Engineering, 1987
AbstractNumerical solution of a given non‐linear algebraic system of equations by a quasi‐Newton type method requires updating the approximation to the Jacobian at each step. Two methods for large sparse systems are described. The approximation for the Jacobian is factored into an LDU form at the first step, then all the subsequent updates are made to ...
Tewarson, R. P., Yin, Zhang
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Relaxation of Crystals with the Quasi-Newton Method

Journal of Computational Physics, 1997
The authors present a relaxation scheme for crystals with the quasi-Newton method. The method preserves the crystal structure during relaxation. The efficiency of the method is demonstrated for silicon test problems.
Pfrommer, Bernd G., Côté, Michel, Louie, Steven G., Cohen, Marvin L.   +3 more
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Quasi-Newton-Verfahren

1989
In diesem Abschnitt soll ein mathematisch besonders interessanter Weg der Nullstellenbestimmung beschrieben werden. Wir haben bereits in 3.2 gesehen, das die Q-superlinear konvergenten Iterationsverfahren Newton-ahnlich sind. Mit dem gedampften Newtonverfahren haben wir ein global und schnell konvergentes Minimierungsverfahren kennengelernt, bei dem ...
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Cancellation Errors in Quasi-Newton Methods

SIAM Journal on Scientific and Statistical Computing, 1986
Using a probabilistic estimate, the author gives the effect of cancellation on the performance of quasi-Newton methods. First, the author describes and shows that the size of the low rank correction can be measured for the BFGS method. This BFGS method is used to find a local solution \(x^*\) of the problem: minimize f(x), \(x\in {\mathbb{R}}^ n ...
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A quasi-Newton trust-region method

Mathematical Programming, 2004
For nonlinear multivariate unconstrained optimization the quasi-Newton technique is used quite often, especially in those cases where the Hessian is either not known analytically or expensive to compute. E. Michael Gertz offers an approach which is based on the quasi-Newton method, but augmented with a line-search method to find a point that satisfies ...
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Long vectors for quasi-Newton updates

Mathematical Programming, 1986
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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The analysis of consolidation by a quasi‐Newton technique

International Journal for Numerical and Analytical Methods in Geomechanics, 1988
AbstractA quasi‐Newton algorithm is implemented for the solution of multi‐dimensional, linear consolidation problems. The study is motivated by the need to implement an efficient equation‐solving technique for the solution of large systems of equations typical in problems of consolidation of saturated porous media.
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A quasi-Newton method with Cholesky factorization

Computing, 1980
A quasi-Newton method for unconstrained minimization is presented, which uses a Cholesky factorization of an approximation to the Hessian matrix. In each step a new row and column of this approximation matrix is determined and its Cholesky factorization is updated. This reduces storage requirements and simplifies the calculation of the search direction.
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