A comparison of two smoothing methods as pre-processing for iterative deconvolution.

A Comparison of Two Smoothing Methods for Word Bigram Models

Word bigram models estimated from text corpora require smoothing methods to estimate the probabilities of unseen bigrams. The deleted estimation method uses the formula: Pr(i j j) = fi + (1 )fijj ; where fi and fijj are the relative frequency of i and the conditional relative frequency of i given j, respectively, and is an optimized parameter. MacKay (1994) proposes a Bayesian approach using Di...

Improvements of two preconditioned AOR iterative methods for Z-matrices

‎In this paper‎, ‎we propose two preconditioned AOR iterative methods to solve systems of linear equations whose coefficient matrices are Z-matrix‎. ‎These methods can be considered as improvements of two previously presented ones in the literature‎. ‎Finally some numerical experiments are given to show the effectiveness of the proposed preconditioners‎.‎

Algorithmic Optimisations for Iterative Deconvolution Methods

We investigate possibilities to speed up iterative algorithms for nonblind image deconvolution. We focus on algorithms in which convolution with the point-spread function to be deconvolved is used in each iteration, and aim at accelerating these convolution operations as they are typically the most expensive part of the computation. We follow two approaches: First, for some practically importan...

Deficit irrigation for corn: a comparison of two methods

Residual Smoothing Techniques for Iterative Methods

An iterative method for solving a linear system Ax b produces iterates {xk with associated residual norms that, in general, need not decrease "smoothly" to zero. "Residual smoothing" techniques are considered that generate a second sequence {Yk via a simple relation yk (1 0k)yk-+ r/kxk. The authors first review and comment on a technique of this form introduced by Sch6nauer and Weiss that resul...