This report describes our experience in implementing a non-parametric (distribution free) discriminant analysis module for use in a wide range of pattern recognition problems. Issues discussed include performance results on both real and simulated data sets, comparisons to other methods, and the computational environment. In some cases, this module performs betther than other existing methods. ...

This study investigated measurements related to average f0 level and f0 change over eight consecutive sections of the whole vocalic segment, for their roles as both acoustic and perceptual correlates of Cantonese lexical tones. Twenty-four CV Cantonese words, making up four sets of words that minimally contrasted in the six Cantonese tones (tones 55, 25, 33, 21, 23, and 22) were read by 10 spea...

This paper presents a word level confidence scoring technique based on a combination of multiple features extracted from the output of a phonetic classifier. The goal of this research was to develop a robust confidence measure based strictly on acoustic information. This research focused on methods for augmenting standard log likelihood ratio techniques with additional information to improve th...

When applying a statistical method in practice it often occurs that some observations deviate from the usual assumptions. However, many classical methods are sensitive to outliers. The goal of robust statistics is to develop methods that are robust against the possibility that one or several unannounced outliers may occur anywhere in the data. These methods then allow to detect outlying observa...

As a contribution to reproducible research, this paper presents a framework and a database to improve the development, evaluation and comparison of methods for gait recognition from motion capture (MoCap) data. The evaluation framework provides implementation details and source codes of state-of-the-art human-interpretable geometric features as well as our own approaches where gait features are...

A method of generating complementary eigenspaces optimised for inter-class and intra-class separability respectively is presented. The objective of creating these spaces is to improve the efficiency of eigenspace search algorithms. The inter-class optimised space may also be used to improve classification and a quantitative evaluation of this against conventional Principal Component Analysis an...

This paper considers sparse linear discriminant analysis of high-dimensional data. In contrast to the existing methods which are based on separate estimation of the precision matrix Ω and the difference δ of the mean vectors, we introduce a simple and effective classifier by estimating the product Ωδ directly through constrained l1 minimization. The estimator can be implemented efficiently usin...

Classes on creativity, innovation, and entrepreneurship are becoming quite popular at universities throughout the world. However, it is not easy for business students to get involved to innovative activities, especially patent application. The present study investigated how to enhance business students’ intention to participate in innovative activities and which incentives universities should c...

Abstract: This paper presents exploratory techniques for multivariate data, many of them well known to French statisticians and ecologists, but few well understood in North American culture. We present the general framework of duality diagrams which encompasses discriminant analysis, correspondence analysis and principal components, and we show how this framework can be generalized to the regre...