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In this paper we present a sequential expectation maximiza-tion algorithm to adapt in an unsupervised manner a Gaussian mixture model for a classification problem. The goal is to adapt the Gaussian mixture model to cope with the non-stationarity in the data to classify and hence preserve the classification accuracy. Experimental results on synthetic data(More)
—In this paper, a new scheme for constructing parsimonious fuzzy classifiers is proposed based on the L2-support vector machine (L2-SVM) technique with model selection and feature ranking performed simultaneously in an integrated manner, in which fuzzy rules are optimally generated from data by L2-SVM learning. In order to identify the most influential(More)
This paper presents a novel hands-free control system for an electric-powered wheelchair, which is based on EMG (Electromyography) signals recorded from eyebrow muscle activity. By using a simple CyberLink [1] device, one-dimensional continuous EMG signals are obtained, analysed, and then translated into multi-directional control commands (forward, left,(More)
This paper investigates manifestation of fatigue in myoelectric signals during dynamic contractions produced whilst playing PC games. The hand's myoelectric signals were collected in 26 independent sessions with 10 subjects. Two methods, spectral analysis and time-scale analysis, were applied to compute signal frequency and least-square linear regression(More)
Parsimony is very important in system modeling as it is closely related to model interpretability. In this paper, a scheme for constructing accurate and parsimonious fuzzy models by generating distinguishable fuzzy sets is proposed, in which the distin-guishability of input space partitioning is measured by a so-called " local " entropy. By maximizing this(More)
—This paper proposes a robust algorithm to adapt a model for EEG signal classification using a modified Extended Kalman Filter (EKF). By applying Bayesian conjugate priors and marginalis-ing the parameters, we can avoid the needs to estimate the covariances of the observation and hidden state noises. In addition, Laplace approximation is employed in our(More)