Background: Logistic discriminant method was applied to differentiate malignant from benign in a group of patients with proved breast lesions on the basis of ultrasonic parameters. Materials and Methods: Our database include 273 patients' ultrasonographic pictures consisting of 14 quantitative variables. The measured variables were ultrasound propagation velocity, acoustic impedence and attenua...

Traditional sequence analysis depends on sequence alignment. In this study, we analyzed various functional regions of the human genome based on sequence features, including word frequency, dinucleotide relative abundance, and base-base correlation. We analyzed the human chromosome 22 and classified the upstream, exon, intron, downstream, and intergenic regions by principal component analysis an...

Received July 12 th , 2012 Accepted July 28 th , 2012 In this paper, a new Face Recognition method based on Discrete orthogonal Tchebichef moments with Linear Discriminant Analysis and Probabilistic Neural Network is proposed. Tchebichef moments are having good energy compaction property that made them useful in image compression and dimensionality reduction operations. Moreover the translation...

In this paper, we present an effective method to writer identification that is carried out using single Chinese character as script, which is very flexible and very easy to be used in practice. The directional element features are first extracted from the handwriting character scripts, then the dimensions of the features is reduced using PCA in order to cope with the small sample size problem. ...

this paper aims to propose an effective paroxysmal atrial fibrillation (paf) predictor which is based on the analysis of the heart rate variability (hrv) signal. predicting the onset of paf, based on non-invasive techniques, is clinically important and can be invaluable in order to avoid useless therapeutic intervention and to minimize the risks for the patients. this method consists of four st...

We previously developed noise robust Hierarchical SpectroTemporal (HIST) speech features. The learning of the features was performed in an unsupervised way with unlabeled speech data. In a final stage we deployed Principal Component Analysis (PCA) to reduce the feature dimensions and to diagonalize them. In this paper we investigate if a discriminant projection can further increase the performa...

We describe a new technique for the classification of motor imagery electroencephalogram (EEG) recordings in a brain computer interface (BCI) task. The technique is based on an adaptive time-frequency analysis of EEG signals computed using local discriminant bases (LDB) derived from local cosine packets (LCP). In an offline step, the EEG data obtained from the C(3)/C(4) electrode locations of t...