in order to survey the evolutionary history and impact of historical events on the genetic structure of iranian people, the hv2 region of 141 mtdna sequences related to six iranian populations were analyzed. slight and non-significant fst distances among the central-western persian speaking populations of iran testify to the common origin of these populations from one proto-population. mismatch...

Recently, a large number of equivalences for probabilistic automata has been proposed in the literature. Except for the probabilistic bisimulation of Larsen & Skou, none of these equivalences has been characterized in terms of an intuitive testing scenario. In our view, this is an undesirable situation: in the end, the behavior of an automaton is what an external observer perceives. In this pap...

Functional turnover of transcription factor binding sites (TFBSs), such as whole-motif loss or gain, are common events during genome evolution. Conventional probabilistic phylogenetic shadowing methods model the evolution of genomes only at nucleotide level, and lack the ability to capture the evolutionary dynamics of functional turnover of aligned sequence entities. As a result, comparative ge...

Neural networks are widely used as classifiers in many pattern recognition problems because of good generalization abilities, what is a crucial issue in any practical application. However, vast majority of neural network architectures demands a huge computational effort for the training process, what in turn limits such solutions from application in one important domain of pattern recognition, ...

in this study, a multi-objective genetic algorithm (moga) is utilized to extract interpretable and compact fuzzy rule bases for modeling nonlinear multi-input multi-output (mimo) systems. in the process of non- linear system identi cation, structure selection, parameter estimation, model performance and model validation are important objectives. furthermore, se- curing low-level and high-level ...

nowadays, robots account for most part of our lives in such a way that it is impossible for usto do many of affairs without them. increasingly, the application of robots is developing fastand their functions become more sensitive and complex. one of the important requirements ofrobot use is a reliable software operation. for enhancement of reliability, it is a necessity todesign the fault toler...

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...

In this paper we propose a classification method based on a special class of feed-forward neural network, namely product-unit neural networks. Product-units are based on multiplicative nodes instead of additive ones, where the nonlinear basis functions express the possible strong interactions between variables. We apply an evolutionary algorithm to determine the basic structure of the product-u...

Fractal Image Compression is a well-known problem which is in the class of NP-Hard problems. Quantum Evolutionary Algorithm is a novel optimization algorithm which uses a probabilistic representation for solutions and is highly suitable for combinatorial problems like Knapsack problem. Genetic algorithms are widely used for fractal image compression problems, but QEA is not used for this kind o...

The determination of the number of groups in a dataset, their composition and the most relevant measurements to be considered in clustering the data, is a high-demanding task, especially when the a priori information on the dataset is limited. Some different genetic approaches are proposed as tools for automatic data clustering and features selection. They differ in the adopted codification of ...