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An effective feature extraction technique for speaker recognition is presented in this paper. It uses multiresolution property of wavelet transform and Mel-Frequency Cepstral Coefficients (MFCCs) for analyzing the speech signal. For individual speaker, first the speech signal is decomposed using Discrete Wavelet Transform (DWT) into approximations and details coefficients. Approximation coefficients...
In this paper, pruned fuzzy k-nearest neighbor (PFKNN) classifier is proposed to classify different types of arrhythmia beats present in the MIT-BIH Arrhythmia database. We have tested our classifier on ~103100 beats for six beat types present in the database. Fuzzy KNN (FKNN) can be implemented very easily but large number of training examples used for classification which can be very time consuming...
This paper presents a comparison of different approaches for performing baseline removal in the electrocardiogram (ECG) signal for use in an ECG based decision support system for diagnosis of coronary heart disease. Our implementations of seven different algorithms for removal of baseline from the ECG signal have been compared which include methods based on use of linear Digital filters, Adaptive...
This paper renders a fuzzy nearest neighbor classifier with data pruning to reduce the number of stored prototypes to minimize memory and computational time requirements. The incorporation of fuzzy set theory into nearest neighbor classification makes the decision process more flexible and adaptable to noise in the data. We have also embodied an efficient approach for nearest neighbor search in our...
This paper presents a robust technique for classification of six types of heart beats through ECG. Wavelet domain analysis is used for feature extraction from the ECG data along with instantaneous RR interval. Only 11 features are being used for this classification with a classification accuracy of ~99.5% through a 1-NN classifier. The main advantage of this method is its robustness to noise, which...
In this paper we describe a technique for the automatic detection of ST segment deviations for the diagnosis of coronary heart disease (CHD) using ambulatory ECG recordings through the application of lead-dependent Karhunen-Loeve Transform (KLT) bases for dimensionality reduction of ST segment data. Preprocessing is carried out prior to the extraction of the ST Segment which involves noise and artifact...
Fingerprint image segmentation is an integral part of an automatic fingerprint recognition system. In this paper an effective algorithm for fingerprint image segmentation is presented. This technique is based on the fusion of multiple features for segmentation that are projected onto a one dimensional feature space using Fisher discriminant analysis. The classification of the fingerprint regions as...
This paper presents an efficient algorithm for an online signature verification system that is based on the extraction of global features from the spatial coordinates obtained during the online acquisition of a signature using one dimensional wavelet transform. A k-NN classifier is used for classification purposes. Low error rates obtained for both random and skilled forgeries datasets illustrate...
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