Abstract. In this paper we consider the question of whether it is possible to classify n-back EEG data into different memory loads across subjects. To capture relevant information ...
Traditional programming languages are algorithmic: they are best suited to writing programs that acquire all their inputs before executing and only produce a result on termination...
This paper presents a new method that uses orthogonalized features for time series clustering and classification. To cluster or classify time series data, either original data or...
Document examiners use a variety of features to analyze a given handwritten document for writer verification. The challenge in the automatic classification of a pair of documents ...
A. Bhardwaj, A. Singh, Harish Srinivasan, Sargur N...
Background: Feature selection is a pattern recognition approach to choose important variables according to some criteria in order to distinguish or explain certain phenomena (i.e....