Due to its simple and parameter invariant nature, the proposed system is highly generic, and, thus, applicable to any ECG dataset.

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This paper presents a generic and patient-specific classification system designed for robust and accurate detection of ECG heartbeat patterns. The proposed feature extraction process utilizes morphological wavelet transform features, which are projected onto a lower dimensional feature space using principal component analysis, and temporal features from the ECG data. For the pattern recognition unit, feedforward and fully connected artificial neural networks, which are optimally designed for each patient by the proposed multidimensional particle swarm optimization technique, are employed. By using relatively small common and patient-specific training data, the proposed classification system can adapt to significant interpatient variations in ECG patterns by training the optimal network structure, and thus, achieves higher accuracy over larger datasets. The classification experiments over a benchmark database demonstrate that the proposed system achieves such average accuracies and sensitivities better than most of the current state-of-the-art algorithms for detection of ventricular ectopic beats (VEBs) and supra-VEBs (SVEBs). Over the entire database, the average accuracy-sensitivity performances of the proposed system for VEB and SVEB detections are 98.3%-84.6% and 97.4%-63.5%, respectively. Finally, due to its parameter-invariant nature, the proposed system is highly generic, and thus, applicable to any ECG dataset.

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Using the unprecedented observational capabilities deployed during the Cooperative Atmosphere-Surface Exchange Study-99 (CASES-99), we found three distinct turbulence events on the night of 18 October 1999, each of which was associated with different phenomena: a density current, solitary waves, and downward propagating waves from a low-level jet. In this study, we focus on the first event, the density current and its associated intermittent turbulence. As the cold density current propagated through the CASES-99 site, eddy motions in the upper part of the density current led to periodic overturning of the stratified flow, local thermal instability and a downward diffusion of turbulent mixing. Propagation of the density current induced a secondary circulation. The descending motion following the head of the density current resulted in strong stratification, a sharp reduction in the turbulence, and a sudden increase in the wind speed. As the wind surge propagated toward the surface, shear instability generated upward diffusion of turbulent mixing. We demonstrate in detail that the height and sequence of the local thermal and shear instabilities associated with the dynamics of the density current are responsible for the apparent intermittent turbulence.

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