The aim of this paper is to review the most important results on the hybrid procedures 7] for solving systems of linear equations. Starting from two iterative methods for solving a system of linear equations, the hybrid procedure consists of constructing a new sequence of iterates with better convergence properties. For a more complete treatment, see 4]. Hybrid procedures were extended to syste...

Protein complexes are essential components in many cellular processes. In this study, a procedure to determine the protein-complex structure from a partial molecular-replacement (MR) solution is demonstrated using a direct-method-aided dual-space iterative phasing and model-building program suite, IPCAS (Iterative Protein Crystal structure Automatic Solution). The IPCAS iteration procedure invo...

In this work we devise eecient algorithms for nding the search directions for interior point methods applied to linear programming problems. There are two innovations. The rst is the use of updating of preconditioners computed for previous barrier parameters. The second is an adaptive automated procedure for determining whether to use a direct or iterative solver, whether to reinitialize or upd...

The Levenberg-Marquardt algorithm is considered as the most effective one for training Artificial Neural Networks but its computational complexity and the difficulty to compute the trust region have made it very difficult to develop a true iterative version to use in on-line training. The algorithm is frequently used for off-line training in batch versions although some attempts have been made ...

| A simple receiver structure recently proposed by the authors [1] for convolutional coded M{ary di erential phase shift keying (MDPSK) transmission over at Rayleigh fading channels without channel state information is analyzed in detail. We present a thorough discussion of the iterative decoding procedure, which is referred to as iterative decision{feedback di erential demodulation (iterative ...

In this paper, a new procedure for decoding cyclic and BCH codes up to their actual minimum distance is presented. Previous algebraic decoding procedures for cyclic and BCH codes such as the Peterson decoding procedure and our procedure using nonrecurrent syndrome dependence relations can be regarded as special cases of this new decoding procedure. With the aid of a computer prokram, it has bee...

Termination proving has traditionally been based on the search for (possibly lexicographic) ranking functions. In recent years, however, the discovery of termination proof techniques based on Ramsey’s theorem have led to new automation strategies, e.g. size-change, or iterative reductions from termination to safety. In this paper we revisit the decision to use Ramsey-based termination arguments...

This paper introduces a general formulation of constrained iterative restoration algorithms in which deterministic and/or statistical information about the undistorted signal and statistical information about the noise are directly incorporated into the iterative procedure. This a priori information is incorporated into the restoration algorithm by what we call "soft" or statistical constraints...

Inference models, which replace an optimization-based inference procedure with a learned model, have been fundamental in advancing Bayesian deep learning, the most notable example being variational auto-encoders (VAEs). In this paper, we propose iterative inference models, which learn how to optimize a variational lower bound through repeatedly encoding gradients. Our approach generalizes VAEs ...

Abstract. In this paper, we propose iterative regularization for image denoising problems, based on the total variation minimizing models proposed by Rudin, Osher, and Fatemi(ROF). Besides, considering the staircase occuring in the process of denoising, we combine the higher order derivatives, and use iterative scheme. The fourth order dual method is used to solve the minimization problems. The...