Ú Ú Ú Spatial Modelling using the Mahalanobis Statistic:Two Examples from the Discipline of Plant Geography R. J. DeVries Ph.D. Student, School of Environmental and Life Sciences, University of Newcastle E-Mail: [email protected]

This paper describes a method for automatically generating diagnostic programs for mixed-signal load boards. This procedure employs a statistical method of computing Mahalanobis Distance to find defects in load board traces and components

An automatic method to create CV forrnantsource templates from continuous speech corpus is proposedfor speechsynthesis,where the boundaries of the CV templates are decided on the basis of the Mahalanobis distance. The synthetic experiments have proved the methodto be useful.

Video has become an important element of multimedia computing and communication environments, with applications as varied as broadcasting, education, publishing and military intelligence. In Video Retrieval system, each video that is stored in the database has its features extracted and compared to the features of the query image. Proposed work is to retrieve video from the database by giving q...

We present a method allowing a signiicant speed-up of the eigen-detection method (detection based on principle component analysis). We derive a formula for an upper bound on the class-conditional probability (or, equivalently, a lower bound on the Mahalanobis distance) on which detection is based. Often, the lower bound of Mahalanobis distance (MD) reaches a preset threshold after computation o...

Most distance metric learning (DML) approaches focus on learning a Mahalanobis metric for measuring distances between examples. However, for particular feature representations, e.g., histogram features like BOW and SPM, Mahalanobis metric could not model the correlations between these features well. In this work, we define a nonMahalanobis distance for histogram features, via Expected Hitting T...

Autonomy requires robustness. The use of unmanned (autonomous) vehicles is appealing for tasks which are dangerous or dull. However, increased reliance on autonomous robots increases reliance on their robustness. Even with validated software, physical faults can cause the controlling software to perceive the environment incorrectly, and thus to make decisions that lead to task failure. We prese...

Semi-supervised clustering is an important method which can improve clustering performance by introducing partial supervised information. This paper mainly studies the semi-supervised fuzzy clustering based on Mahalanobis distance and Gaussian Kernel for SCAPC algorithm. Here, we give a new semi-supervised fuzzy clustering objective function. By solving the optimization problem with above objec...

With increasing complexity in electronic systems there is a need for system level anomaly detection and fault isolation. Anomaly detection based on vector similarity to a training set is used in this paper through two approaches, one the preserves the original information, Mahalanobis Distance (MD), and the other that compresses the data into its principal components, Projection Pursuit Analysi...