Model selection is one of the most important tasks in the identification of blackbox systems. In this paper, we give a novel model selection method from the viewpoint of functional analysis. We formulate the system identification problem as a function approximation problem in a reproducing kernel Hilbert space (RKHS), where the approximation error is measured by the RKHS norm. Within this frame...

In many contexts the predictive validation of models or their associated prediction strategies is of greater importance than model identification which may be practically impossible. This is particularly so in fields involving complex or high dimensional data where model selection, or more generally predictor selection is the main focus of effort. This paper suggests a unified treatment for pre...

This paper discusses sign language recognition using linguistic sub-units. It presents three types of sub-units for consideration; those learnt from appearance data as well as those inferred from both 2D or 3D tracking data. These sub-units are then combined using a sign level classifier; here, two options are presented. The first uses Markov Models to encode the temporal changes between sub-un...

Sex differences in academic achievement have often been observed but have usually been attributed to inherent differences between men and women students rather than to differential marking by examiners. The present study indicates that this may not be the case. Sex bias was shown to occur in the evaluation of students’ projects. These results cannot be attributed to actual differences in achiev...

Over the years, the feasibility of using Electrocardiogram (ECG) signal for human identification issue has been investigated, and some methods have been suggested. In this research, a new effective intelligent feature selection method from ECG signals has been proposed. This method is developed in such a way that it is able to select important features that are necessary for identification usin...

the success of artificial recharge schemes requires the identification of suitable site. the use of fuzzy set theory in site selection projects allows the decision-makers to incorporate unquantifiable information into decision model. in this paper, site selection of artificial groundwater recharges using an integrated method of fuzzy topsis and ahp has been done in raster environment of gis. th...

The identification of molecular markers linked to leaf curl virus (CLCuV) disease resistance in cotton has the potential to improve both the efficiency and the efficacy of selection in cotton breeding programs. Genetic analysis suggested that CLCuV resistance is controlled by a single dominant gene. In this study, an interspecific F2 population derived from a cross of Gossypium barbadense and G...