BACKGROUND The differentiation of hypertrophic cardiomyopathy (HCM) from hypertensive left ventricular hypertrophy (H-LVH) on the basis of morphological information obtained by conventional echocardiography is occasionally problematic. We investigated whether strain rate (SR) imaging derived from tissue Doppler imaging (TDI) is able to discriminate HCM from H-LVH. METHODS AND RESULTS Conventi...

This paper analyzes the higher order asymptotic properties of Generalized Method of Moments (GMM) estimators for linear time series models using many lags as instruments. A data dependent moment selection method based on minimizing the approximate mean squared error is developed. In addition, a new version of the GMM estimator based on kernel weighted moment conditions is proposed. It is shown ...

This paper studies the interlinked relationship between globalisation and technological upgrading in affecting employment and wages of skilled and unskilled workers in a middle income developing country. It exploits a unique longitudinal firm‐level database that covers all manufacturing firms in Turkey over the 1992‐2001 period. Turkey is taken as an example of a developing economy that, in tha...

This paper presents some experiments on discriminative training for GMM/UBM based speaker recognition systems. We propose two MMIE adaptation methods for GMM component weights suitable for speaker recognition. The impact on performance of this training methods is compared to the standard weight estimation/adaptation criterion, MLE and MAP on standard GMM based systems and on SVM based systems. ...

We compare the performance of ve algorithms for vector quan-tisation and clustering analysis: the Self-Organising Map (SOM) and Learning Vector Quantization (LVQ) algorithms of Kohonen, the Linde-Buzo-Gray (LBG) algorithm, the MultiLayer Perceptron (MLP) and the GMM/EM algorithm for Gaussian Mixture Models (GMM). We propose that the GMM/EM provides a better representation of the speech space an...

Skill-Biased Technological Change and Skill-Enhancing Trade in Turkey: Evidence from Longitudinal Microdata This paper explores the causes of skill-based employment differentials within the Turkish manufacturing sector over the period 1980-2001. Turkey is taken as an example of a developing economy that, in that period, had been technologically advancing and becoming increasingly integrated wit...

Gaussian Mixture Model (GMM) with Fuzzy c-means attempts to classify signals into speech and music. Feature extraction is done before classification. The classification accuracy mainly relays on the strength of the feature extraction techniques. Simple audio features such as Time domain and Frequency domain are adopted. The time domain features are Zero Crossing Rate (ZCR) and Short Time Energy...

Gaussian mixture models (GMM) have been widely and successfully used in speaker recognition during the last decade. However, they are generally trained using the generative criterion of maximum likelihood estimation. In this paper, we propose a simple and efficient discriminative approach to learn GMM with a large margin criterion to solve the classification problem. Our approach is based on a ...

SUMMARY The impact of a Pseudomonas fluorescens strain, genetically modified for kanamycin resistance and lactose utilisation (the GMM), could be enhanced by soil amendment with lactose and kanamycin. Lactose addition decreased the shoot to root ratio of pea, and both soil amendments increased the populations of total culturable bacteria and the inoculated GMM. Only kanamycin perturbed the bact...

Gaussian Mixture Model (GMM) is an efficient method for parametric clustering. However, traditional GMM can’t perform clustering well on data set with complex structure such as images. In this paper, kernel trick, successfully used by SVM and kernel PCA, is introduced into EM algorithm for solving parameter estimation of GMM, which is so called kernel GMM (kGMM). The basic idea of kernel GMM is...