The effectiveness of several iterative techniques for solving matrix equations resulting from finite-difference approximations to self-adjoint parabolic and elliptic partial differential equations is investigated: the strongly implicit procedure ( sip), the incomplete Cholesky conjugate-gradient method ( iccg)...
In graphical construction techniques, the optimization functions along with their contours are drawn in the same graph. By focusing on the possible area of implementation, the techniques can generate the solution to the optimization problem (Bhandari et al., 2015; Borowy and Salameh, 1996; Markvar...
The convergence rate of the '2 脳 2' algorithm for determining the dominant eigenstate of a Hermitian matrix may be significantly improved using relaxation techniques. A simple operational method for determining an optimal choice of the relaxation parameter at any given iteration step is presented. ...
The Gibbs sampler, Metropolis' algorithm, and simi- lar iterative simulation methods are related to rejection sampling and importance sampling, two methods which have been traditionally thought of as non-iterative. We explore connections between importance sampling, iter- ative simulation, and importance...
defined by the algorithm (1.3) converges in norm to the unique minimizer of (1.2). however, if the gradient ∇ g fails to be strongly monotone, the operator w defined by (1.5) would fail to be contractive; consequently, the sequence { x n } generated by the algorithm (1.3) may ...
standard recursive nonlinear estimators iterated extended Kalman filter quadratic cost function basis cost function minimization Gauss-Newton algorithm/ C1220 Simulation, modelling and identification C4130 Interpolation and function approximation (numerical analysis) C1180 Optimisation techniques C1260 Information ...
The pseudocode for the preconditioned CG iterative method is shown in Algorithm 1.2.1. Algorithm 1 Conjugate Gradient (CG) 1: \(\text{Letting initial guess be }\mathbf{x}_{0}\text{, compute }\mathbf{r}\leftarrow\mathbf{f} - A\mathbf{x}_{0}\) 2: \(\textbf{for }i\left...
In this correspondence, the relationship between iterative decoding and techniques for minimizing cross-entropy is explained. It is shown that minimum cross-entropy (MCE) decoding is an optimal lossless decoding algorithm but its complexity limits its practical implementation. Use of a maximum a posteri...
Z. Elsherbeni, "The iterative multi-region algorithm using a hybrid finite difference frequency domain and method of moment techniques," Progress In Electromagnetics Research, PIER 57, 19-32, 2006.Al Sharkawy, M. H., V. Demir, and A. Z. Elsherbeni, "The iterative multi-region algorithm ...
The algorithm requires minimal human intervention and also incorporates angular refinement to reduce the tilt angle error. We demonstrate that GENFIRE can produce superior results relative to several other popular tomographic reconstruction techniques through numerical simulations and by experimentally ...