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...

due to project evaluation complexity and resource constraints, the project portfolio optimization is numerous decision making challenges. hence, many researches have been done to introduce model and methods for portfolio optimization. but most of them have not considered the interaction between projects. considering the interactions between projects increase complexity of portfolio optimization...

measurement of magnitude and frequency of the voltage flicker is very important for monitoring andcontrolling voltage flicker efficiently to improve the network power quality. this paper presents twonew methods for measurement of flicker signal parameters using shuffled frog leaping algorithm(sfla) and imperialist competitive algorithm (ica). this paper estimates fundamental voltage andflicker ...

In this paper a new method is proposed based on the combination of ICA (Imperial Competitive Algorithm) and GA (Genetic Algorithm) which improves the convergence speed and accuracy of the optimization results. The new algorithm, which is named R-ICA-GA (RecursiveICA-GA), runs ICA and GA consecutively. It is shown that a fast decrease occurs while the proposed algorithm switches from ICA to GA. ...

The spatial distribution of petrophysical properties within the reservoirs is one of the most important factors in reservoir characterization. Flow units are the continuous body over a specific reservoir volume within which the geological and petrophysical properties are the same. Accordingly, an accurate prediction of flow units is a major task to achieve a reliable petrophysical description o...

This thesis is about convolutive ICA with application to EEG. Two methods for convolutive ICA are proposed. One method, the CICAP algorithm, uses a linear predictor in order to formulate the convolutive ICA problem in two steps: linear deconvolution followed by instantaneous ICA. The other method, the CICAAR algorithm, generalizes Infomax ICA to include the case of convolutive mixing. One advan...

Independent component analysis (ICA) aims to recover a set of unknown mutually independent source signals from their observed mixtures without knowledge of the mixing coefficients. In some applications, it is preferable to extract only one desired source signal instead of all source signals, and this can be achieved by a one-unit ICA technique. ICA with reference (ICA-R) is a one-unit ICA algor...

microarray data have an important role in identification and classification of the cancer tissues. having a few samples of microarrays in cancer researches is always one of the most concerns which lead to some problems in designing the classifiers. for this matter, preprocessing gene selection techniques should be utilized before classification to remove the noninformative genes from the microa...

We present a method to deal with adaptive noise cancelling based on independent component analysis (ICA). Although popular least-mean-squares (LMS) algorithm removes noise components based on second-order correlation, the proposed ICA-based algorithm can utilize higher-order statistics. Additionally, extending to transform-domain adaptive filtering (TDAF) methods, normalized ICA-based algorithm...

the purpose of this study is to demonstrate the potential of imperialist competitivealgorithm (ica) for solving blasius dierential equation. this algorithm is inspiredby competition mechanism among imperialists and colonies and has demonstrated excellentcapabilities such as simplicity, accuracy, faster convergence and better global optimumachievement in contrast to other evolutionary algorithms...