Results 11 to 20 of about 11,641,221 (293)
The conjugate gradient method [PDF]
The Leading Edge, 2018 The conjugate gradient method can be used to solve many large linear geophysical problems — for example, least-squares parabolic and hyperbolic Radon transform, traveltime tomography, least-squares migration, and full-waveform inversion (FWI) (e.g., Witte et al., 2018).
Karl Schleicher
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The Limited Memory Conjugate Gradient Method [PDF]
SIAM Journal on Optimization, 2013 In theory, the successive gradients generated by the conjugate gradient method applied to a quadratic should be orthogonal. However, for some ill-conditioned problems, orthogonality is quickly lost due to rounding errors, and convergence is much slower than expected. A limited memory version of the nonlinear conjugate gradient method is developed.
William W. Hager, Hongchao Zhang
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A feed forward neural network approach for matrix computations [PDF]
, 2001 This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.A new neural network approach for performing matrix computations is presented. The idea of this approach is to construct a feed-forward neural network (FNN)
Al-Mudhaf, Ali F
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Improvement of conjugate gradient methods for removing impulse noise images [PDF]
, 2023 Optimization problems occur in most disciplines like engineering, physics, mathematics, economics, administration, commerce, social sciences, and even politics.
Ahmed A. Abdullah, Ali +3 more
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Block Preconditioning for the Conjugate Gradient Method [PDF]
SIAM Journal on Scientific and Statistical Computing, 1985 Different block preconditionings for the conjugate gradient methods are investigated for solving positive definite block tridiagonal systems. These preconditionings are based on different sparse approximate matrix inverses. The proposed methods are compared with other well-known preconditionings as for example the point incomplete Cholesky ...
Concus, P., Golub, G.H., Meurant, G.
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Moving force identification based on modified preconditioned conjugate gradient method [PDF]
, 2018 This paper develops a modified preconditioned conjugate gradient (M-PCG) method for moving force identification (MFI) by improving the conjugate gradient (CG) and preconditioned conjugate gradient (PCG) methods with a modified Gram-Schmidt algorithm. The
Zhen Chen +5 more
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Performance Gains in Conjugate Gradient Computation with Linearly Connected GPU Multiprocessors [PDF]
, 2014 Conjugate gradient is an important iterative method used for solving least squares problems. It is compute-bound and generally involves only simple matrix computations.
Lin, Tsung-Han, Tarsa, Stephen, Kung, H.
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Conjugate gradient algorithms for conic functions [PDF]
, 1986 summary:The paper contains a description and an analysis of two modifications of the conjugate gradient method for unconstrained minimization which find a minimum of the conic function after a finite number of steps.
Lukšan, Ladislav
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Spectral CG Algorithm for Solving Fuzzy Non-linear Equations
Iraqi Journal for Computer Science and Mathematics, 2022 The non-linear conjugate gradient method is a very effective technique for addressing Large-Scale minimization problems, and it has a wide range of applications in Mathematics, Chemistry, Physics, Engineering, and Medicine, etc.
Mezher M. Abed +2 more
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On Meinardus’ examples for the conjugate gradient method [PDF]
Mathematics of Computation, 2007 The conjugate gradient (CG) method is widely used to solve a positive definite linear system A x = b
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