The issue of financial integration, at the country level, is a well-documented phenomenon in the area of International Portfolio Diversification (IPD). Despite the increasing degree of financial integration, it is important to investigate the global integration at industry level to capture the potential benefits of IPD. Thus, this study attempts to evaluate the potential advantages of IPD for i...

blind source separation technique separates mixed signals blindly without any information on the mixing system. in this paper, we have used two evolutionary algorithms, namely, genetic algorithm and particle swarm optimization for blind source separation. in these techniques a novel fitness function that is based on the mutual information and high order statistics is proposed. in order to evalu...

this paper presents the hardware simulation (based on vhdl code) of a multiple-fault tolerant cellular genetic algorithm. this study aims to increase the immunity of cellular genetic algorithm in multiple-fault situation. here, multiple-fault refers to the situation that seu (single event upset) occurs simultaneously at two or more bits of the chromosome and fitness registers. the fault model i...

Blind source separation technique separates mixed signals blindly without any information on the mixing system. In this paper, we have used two evolutionary algorithms, namely, genetic algorithm and particle swarm optimization for blind source separation. In these techniques a novel fitness function that is based on the mutual information and high order statistics is proposed. In order to evalu...

Blind source separation technique separates mixed signals blindly without any information on the mixing system. In this paper, we have used two evolutionary algorithms, namely, genetic algorithm and particle swarm optimization for blind source separation. In these techniques a novel fitness function that is based on the mutual information and high order statistics is proposed. In order to evalu...

clustering is the process of dividing a set of input data into a number of subgroups. the members of each subgroup are similar to each other but different from members of other subgroups. the genetic algorithm has enjoyed many applications in clustering data. one of these applications is the clustering of images. the problem with the earlier methods used in clustering images was in selecting in...

A genetic algorithm is one of a class of algorithms that searches a solution space for the optimal solution to a problem. First part of this work consists of basic information about Genetic algorithm like what are Individual, Population, Crossover, Genes, Binary Encoding, Flipping, Crossover probability, Mutation probability. What is it used for, what is their aim. In this article the methods o...

A genetic algorithm is one of a class of algorithms that searches a solution space for the optimal solution to a problem. First part of this work consists of basic information about Genetic algorithm like what are Individual, Population, Crossover, Genes, Binary Encoding, Flipping, Crossover probability, Mutation probability. What is it used for, what is their aim. In this article the methods o...