Intra-plaque hemorrhage (IPH) and lipid core, characteristics of rupture prone carotid plaques, are often visualized in vivo with MRI using T1 weighted gradient and spin echo, respectively. Increasing magnetic field strength may help to identify IPH and lipid core better. As a proof of concept, automatic segmentation of plaque components was performed with the Mahalanobis distance (MD) measure ...

A methodology for detecting the gradual health degradation of electronic products is presented by defining a health indicator to represent a product’s health state in a time interval. A health indicator is defined as the weighted sum of a histogram bin’s fractional contribution in a time interval that is based on the data collection rate, the likelihood of change in a product’s performance, and...

A health index, Mahalanobis distance (MD), is proposed to indicate the health condition of cooling fan and induction motor based on vibration signal. Anomaly detection and fault classification are accomplished by comparing MDs, which are calculated based on the feature data set extracted from the vibration signals under normal and abnormal conditions. Since MD is a non-negative and non-Gaussian...

The supervised self-organizing map consists in associating output vectors to input vectors through a map, after self-organizing it on the basis of both input and desired output given altogether. This paper compares the use of Euclidian distance and Mahalanobis distance for this model. The distance comparison is made on a data classification application with either global approach or partitionin...

The Mahalanobis-Taguchi System is a diagnosis and forecasting method for multivariate data. Mahalanobis distance is a measure based on correlations between the variables and different patterns that can be identified and analyzed with respect to a base or reference group. This paper presents a comparison of the Mahalanobis-Taguchi System and a standard statistical technique for defect detection ...

In this paper, drills wear monitoring method that based on the mahalanobis distance (MD) of spectrum energy features form cutting torque is proposed. The method consists of three steps. First, using the wavelet transform carried out separating cutting torque components from the original signals. Second, signals feature is adopted to Welch spectrum method extracted on wavelet coefficients of dif...

We propose to learn multiple local Mahalanobis distance metrics to perform knearest neighbor (kNN) classification of temporal sequences. Temporal sequences are first aligned by dynamic time warping (DTW); given the alignment path, similarity between two sequences is measured by the DTW distance, which is computed as the accumulated distance between matched temporal point pairs along the alignme...

Abstract One of the fundamental problems in speech engineering is phoneme segmentation. Approaches to phoneme segmentation can be divided into two categories: supervised and unsupervised segmentation. The approach of this paper belongs to the 2nd category, which tries to perform phonetic segmentation without using any prior knowledge on linguistic contents and acoustic models. In an earlier wor...

In previous work, semi-supervised Fuzzy c-means (ssFCM) was used as an automatic classification technique to classify the Nottingham Tenovus Breast Cancer (NTBC) dataset as no method to do this currently exists. However, the results were poor when compared with semi-manual classification. It is known that the NTBC data is highly non-normal and it was suspected that this affected the poor result...

This report describes a simulation model of sonar tracking, developed to explore the effect of networking sonars on tracking performance. The tracker is an extended Kalman filter with data association by nearest-neighbour in Mahalanobis distance. Data fusion algorithms also use Mahalanobis distance. Simulation outputs have been verified against analytical results where possible.