for many years, researchers have studied high accuracy methods for recognizing the handwriting and achieved many significant improvements. however, an issue that has rarely been studied is the speed of these methods. considering the computer hardware limitations, it is necessary for these methods to run in high speed. one of the methods to increase the processing speed is to use the computer pa...

introduction: the accuracy of analyzing functional mri (fmri) data is usually decreases in the presence of noise and artifact sources. a common solution in for analyzing fmri data having high noise is to use suitable preprocessing methods with the aim of data denoising. some effects of preprocessing methods on the parametric methods such as general linear model (glm) have previously been evalua...

classes of‎ ‎abaffy-broyden-spedicato (abs) methods have been introduced for‎ ‎solving linear systems of equations‎. ‎the algorithms are powerful methods for developing matrix‎ ‎factorizations and many fundamental numerical linear algebra processes‎. ‎here‎, ‎we show how to apply the abs algorithms to devise algorithms to compute the wz and zw‎ ‎factorizations of a nonsingular matrix as well as...

classes of‎ ‎abaffy-broyden-spedicato (abs) methods have been introduced for‎ ‎solving linear systems of equations‎. ‎the algorithms are powerful methods for developing matrix‎ ‎factorizations and many fundamental numerical linear algebra processes‎. ‎here‎, ‎we show how to apply the abs algorithms to devise algorithms to compute the wz and zw‎ ‎factorizations of a nonsingular matrix as well as...

Feature selection is of great importance in Quantitative Structure-Activity Relationship (QSAR) analysis. This problem has been solved using some meta-heuristic algorithms such as: GA, PSO, ACO, SA and so on. In this work two novel hybrid meta-heuristic algorithms i.e. Sequential GA and LA (SGALA) and Mixed GA and LA (MGALA), which are based on Genetic algorithm and learning automata for QSAR f...

the vast use of linear prediction coefficients (lpc) in speech processing systems has intensified the importance of their accurate computation. this paper is concerned with computing lpc coefficients using evolutionary algorithms: genetic algorithm (ga), particle swarm optimization (pso), dif-ferential evolution (de) and particle swarm optimization with differentially perturbed velocity (pso-dv...

background: rna molecules play many important regulatory, catalytic and structuralroles in the cell, and rna secondary structure prediction with pseudoknots is one themost important problems in biology. an rna pseudoknot is an element of the rna secondary structure in which bases of a single-stranded loop pair with complementary basesoutside the loop. modeling these nested structures (pseudokno...