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An appropriate pre-processing algorithm in classification is not only of great importance with respect to classifier choice, but also would be more crucial. In this paper, a pre-processing step is proposed in order to increase accuracy of classification. The aim of this approach is finding a transformation matrix causes classes to be more discriminable by(More)
Recently, there has been great interest in Bioinformatics among researches from various disciplines such as computer science, mathematics, statistics and artificial intelligence. Bioinformatics mainly deals with solving biological problems at molecular levels. One of the classic problems of bioinformatics which has gain a lot attention lately is(More)
An appropriate pre-processing algorithm in classification is important and crucial with respect to classifier type. In this paper, two pre-processing methods are suggested to be applied before classification in order to increase classification accuracy. The aim of this approach is finding a transformation matrix to discriminate between classes by(More)
Selection of a classifier is only one aspect of the problem of data classification. Equally important (if not, more so) is the pre-processing strategy to be employed. In this paper, a pre-processing step is proposed in order to increase accuracy of classification. The aim of this approach is finding a transformation matrix to discriminate between classes by(More)
Linear Discriminant Analysis (LDA) is a feature selection method in speech recognition. LDA finds transformations that maximizes the between-class scatter and minimizes within-class scatter. This transformation can be obtained in a class-dependent or class independent manner. In this paper, we propose a method to improve LDA and also we use it instead of(More)
Reduced ordered binary decision diagram (ROBDD) is a memory-efficient data structure which is used in many applications such as synthesis, digital system, verification, testing and VLSI-CAD. The size of an ROBDD for a function can be increased exponentially by the number of independent variables of the function that is called “memory explosion(More)
Reduced Ordered Binary Decision Diagrams (ROBDDs) are frequently used as the representation of choice to solve various CAD problems such as synthesis, digital-system verification and testing. The size of an ROBDD for a function can be increased exponentially by the number of independent variables of the function that is called "memory explosion problem".(More)
Modern electrocardiography (ECG) uses a constructed reference potential for the majority of leads. This reference potential, named after its inventor as the Wilson central terminal, is assumed to have negligible value and to be stationary during the cardiac cycle. However, the problem of its variability during the cardiac cycle has been known almost since(More)