The aim of discriminant feature analysis techniques in the signal processing of speech recognition systems is to find a feature vector transformation which maps a high dimensional input vector onto a low dimensional vector while retaining a maximum amount of information in the feature vector to discriminate between predefined classes. This paper points out the significance of the definition of ...

The World Wide Web (WWW) is a reservoir of enormous amount of data which is primarily embedded within unstructured text documents. E-commerce websites, social networking sites, and discussion forums have become a common place for writing informal opinions about products and other related information. A substantial amount of research has been directed towards mining these texts and concludes on ...

Feature Selection is the process of selecting the momentous feature subset from the original ones. This technique is frequently used as a preprocessing technique in data mining. In this study, a new feature selection algorithm is proposed and is called Modified Fisher Score Principal Feature Analysis (MFSPFA). The new algorithm is developed by combining the proposed Modified Fisher Score (MFS) ...

in this paper we propose a new method for classification of subjects into schizophrenia and control groups using functional magnetic resonance imaging (fmri) data. in the preprocessing step, the number of fmri time points is reduced using principal component analysis (pca). then, independent component analysis (ica) is used for further data analysis. it estimates independent components (ics) of...

We show that Integer Programming (IP) can be used as an optimization technique for the instantiation of products of feature models. This is done by showing that the constraints of feature models can be written in linear form. As particular IP technique, we use Gomory cutting planes. We have applied this technique to a test suite of feature models from the literature, and found that the Gomory c...

The rotating machinery is a common class of machinery in the industry. The root cause of faults in the rotating machinery is often faulty rolling element bearings. This paper presents a novel technique using artificial neural network learning for automated diagnosis of localized faults in rolling element bearings. The inputs of this technique are a number of features (harmmean and median), whic...