BACKGROUND Independent Component Analysis (ICA) has been widely applied to the analysis of fMRI data. Accurate estimation of the number of independent components of fMRI data is critical to reduce over/under fitting. Although various methods based on Information Theoretic Criteria (ITC) have been used to estimate the intrinsic dimension of fMRI data, the relative performance of different ITC in...

wireless communication is the major form of connection nowadays. in most cases it exploits the benefits of the spread spectrum techniques to overcome channel introduced corruptions like doppler residual frequency, noise, interference and jamming. these techniques also enhance the security and quality of the link. using long spreading pseudo-noise codes provides further security for the link tho...

Two main classes of theories have been proposed regarding range effects in unidimensional absolute-identification tasks. One class posits that as range is increased, .criterial noise increases but stimulus noise remains constant. Another class posits increasing stimulus noise but constant criterial noise. In this study, an effort is made to help decide this issue. Multiple observations are used...

To build good models, we need to know the appropriate model size. To handle this problem, a variety of information criteria have already been proposed, each with a different background. In this paper, we consider the problem of model selection and investigate the performance of a number of proposed information criteria and whether the assumption to obtain the formulae that fitting errors are no...

With advancing semiconductor technology and exponentially growing design complexities, predictability of design tools becomes an important part of a stable top-down design process. Prediction of individual tool solution quality enables designers to use tools to achieve best solutions within prescribed resources, thus reducing design cycle time. However, as EDA tools become more complex, they be...

 Edge Detection is an important task for sharpening the boundary of images to detect the region of interest. This paper applies a linear cellular automata rules and a Mamdani Fuzzy inference model for edge detection in both monochromatic and the RGB images. In the uniform cellular automata a transition matrix has been developed for edge detection. The Results have been compared to the ...

Noisy training data have a huge negative impact on machine learning algorithms. Noise-filtering algorithms have been proposed to eliminate such noisy instances. In this work, we empirically show that the most popular noise-filtering algorithms have a large False Positive (FP) error rate. In other words, these noise filters mistakenly identify genuine instances as outliers and eliminate them. Th...

Wireless communication is the major form of connection nowadays. In most cases it exploits the benefits of the spread spectrum techniques to overcome channel introduced corruptions like Doppler residual frequency, noise, interference and jamming. These techniques also enhance the security and quality of the link. Using long spreading pseudo-noise codes provides further security for the link tho...