Outlier is attached importance in statistics and engineering, because it might result misleading identification results. However, there significant uncertainty the outlier detection, when an outlying observation lies close to boundary between outliers regular data or are sparse observations. The associated of mostly results from statistical parameters, such as mean value standard deviation. unk...

Mahalanobis distance metric takes feature weights and correlation into account in the distance computation, which can improve the performance of many similarity/dissimilarity based methods, such as kNN. Most existing distance metric learning methods obtain metric based on the raw features and side information but neglect the reliability of them. Noises or disturbances on instances will make cha...

This paper presents the person identification system developed at Athens Information Technology and its performance in the CLEAR 2007 evaluations. The system operates on the audiovisual information (speech and faces) collected over the duration of gallery and probe videos. It comprises of an audio-only (speech), a video-only (face) and an audiovisual fusion subsystem. Audio recognition is based...

In this article we compare 14 distance measures and their modifications between feature vectors with respect to the recognition performance of the principal component analysis (PCA)-based face recognition method and propose modified sum square error (SSE)-based distance. Recognition experiments were performed using the database containing photographies of 423 persons. The experiments showed, th...

Bistable perception emerges when a stimulus under continuous view is perceived as the alternation of two mutually exclusive states. Such a stimulus provides a unique opportunity for understanding the neural basis of visual perception because it dissociates the perception from the visual input. In this paper we analyze the dynamic activity of local field potential (LFP), simultaneously collected...

The objective of this research is to investigate the feasibility of utilizing the multi-scale analysis and support vector machine (SVM) classification scheme to diagnose the bearing faults in rotating machinery. For complicated signals, the characteristics of dynamic systems may not be apparently observed in a scale, particularly for the fault-related features of rotating machinery. In this res...

Objective in this paper, we have done Mahalanobis Discriminant analysis to EEG data of experiment objects which are recorded impersonally come up with a relatively accurate method used in feature extraction and classification decisions. Methods In accordance with the strength of  wave, the head electrodes are divided into four species. In use of part of 21 electrodes EEG data of 63 people, we ...

This study aims to evaluate the feasibility and effectiveness of a modified adaptive genetic algorithm (AGA) with Universal Distinct Element Code (UDEC) simulation in analyzing fracture surface feature points an anticline rocky slope. Using coordinate data from 30 points, traditional GA AGA methods were compared, mean value normalized Mahalanobis distance indicating reliability results. The fou...

Applying existing feature selection algorithms to video classification is impractical. A novel algorithm called Basic Sort-Merge Tree (BSMT) is proposed to choose a very small subset of features for video classification in linear time in the number of features. We reduce the cardinality of the input data by sorting the individual features by their effectiveness in categorization, and then mergi...

Structural vibration monitoring has received a lot of attention from the research community in the past few years. The objective is to create automatic structural assessment techniques that can be realized through programmed vibration analysis. Till now many vibration-based damage features have been proposed, yet to truly automate the damage identification process, reliable damage threshold con...