Regarding to the high between-band correlation and large volumes of hyperspectral data, feature reduction (either feature selection or extraction) is an important part of classification process for this data type. A variety of feature reduction methods have been developed using spectral and spatial domains. In this paper, a feature extracting technique is proposed based on rational function cur...

Cancer classification is one of the major applications of the microarray technology. When standard machine learning techniques are applied for cancer classification, they face the small sample size (SSS) problem of gene expression data. The SSS problem is inherited from large dimensionality of the feature space (due to large number of genes) compared to the small number of samples available. In...

Feature extraction and feature normalization is an important preprocessing technique, usually employed before classification. Feature normalization is a useful step to restrict the values of all features within predetermined ranges. However, appropriate choice of normalization technique and normalization range is an important issue, since, applying normalization on the input could change the st...

A behavioral testability analysis technique is proposed for early prediction of testability by analyzing behavioral specifications written in VHDL. The technique extracts functional properties by an analysis of variable range, statement hardness and dependency relation between variables of the specification. It predicts the testability for the whole design with a low computational cost. Another...

Multi-view feature learning is an attractive research topic with great practical success. Canonical correlation analysis (CCA) has become an important technique in multi-view learning, since it can fully utilize the inter-view correlation. In this paper, we mainly study the CCA based multi-view supervised feature learning technique where the labels of training samples are known. Several supervi...

The Internet provides easy access to a kind of library resources. However, classification of documents from a large amount of data is still an issue and demands time and energy to find certain documents. Classification of similar documents in specific classes of data can reduce the time for searching the required data, particularly text documents. This is further facilitated by using Artificial...

For over two decades feature modelling techniques are used in the software research community for domain analysis and modelling of variable software. However, feature modelling has not found its way to the industry. In this paper we present a new feature modelling technique, developed in the context of a new approach called Feature Assembly, which overcomes some of the limitations of the curren...

Current techniques available for the characterization of membrane are destructive, including scanning electron microscopy, mercury intrusion porosimetry and size exclusion of particles. An alterative technique based on ultrasonic frequency domain reflectometry (UTDR) that allows easy, non-invasive and real-time analysis of membrane morphology would be of significant value to the membrane indust...