The second iterative steps leads to discrete 0 or 1 distribution of material. The algorithm solves the problem for the same model boundary during the iterative process.doi:10.1002/zamm.19980781551T. KasprzakR. KutylowskiK. MysleckiJohn Wiley & Sons, Ltd.ZAMM - Journal of Applied Mathematics ...
Smith, and Vetta. This technique has proven very useful for achieving a number of recent breakthroughs in the development of fixed-parameter algorithms for NP-hard minimization problems. There is a clear potential for further applications as well as a further development...
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 ...
In this paper, we introduce a new iterative algorithm for solving a generalized Sylvester matrix equation of the formwhich includes a class of linear matrix equations. The objective of the algorithm is to minimize an error at each iteration by the idea of gradient-descent. We show that the pr...
We describe these methods in more detail in the next section.In practice, we often use a variety of preconditioning techniques to improve the convergence of the iterative methods. In this white paper we focus on the incomplete-LU and Cholesky preconditioning [11], which is one of the most ...
Ab initio calculation of the macroscopic dielectric constant in silicon Payne, et al., Iterative minimization techniques for ab initio total-energy calculations: molecular dynamics and conjugate gradients, Rev. Mod. Phys 64 (... S Baroni,R Resta - 《Physical Review B》 被引量: 0发表: 1986年...
A classifier SVM and four different combination techniques were used by considering the CEDAR (handwritten digit) database. It is shown how results depend by the iterations on the feedback process, as well as by the specific combination decision schema and by data distribution....
We describe these methods in more detail in the next section. In practice, we often use a variety of preconditioning techniques to improve the convergence of the iterative methods. In this white paper we focus on the incomplete-LU and Cholesky preconditioning [11], which is one of the most...
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.M. A. Sharkawy and A. Z. Elsherbeni, "The iterative multi-region algorithm using a hybrid ...
Since we assumed that all models were equally important a priori, our algorithm sampled each model type within its bounds. To achieved a non-informative prior as much as possible, each model type was sampled from a uniform distribution within its bounds. Models were then randomly drawn from eac...