Waveform Boundaries Research Articles

Comprehensive Analysis and Gain Derivation of Phase-Shifted Dual-Input LLC Converter

This paper presents a comprehensive time-domain analysis of the dual-input LLC converter. By utilizing PSM and FSM, the converter power stage interfaces two photovoltaic (PV) panels to achieve maximum power point tracking (MPPT). The detailed mode-by-mode operation and steady-state analysis are derived using three parameters: the switching frequency, phase shift, and load weight. Furthermore, the DC gain equations of each PV panel and their characteristic curves are derived. In addition, the waveform boundaries and ZVS analysis are discussed as well. Moreover, an extended perturbation & observation (P&O) algorithm that guarantees achieving MPPT for each panel is proposed. Finally, the theoretical analysis has been tested and verified by a 450-W prototype of dual-input LLC converter.

Time-scaling nonvibrato musical tones while preserving timbral texture

Sounds produced by linear stretching of nonvibrato single tones fail to preserve their original microvariations. While looping is commonly used for elongation with wavetable synthesis, this method requires careful attention to periodic waveform boundaries. Time extension by time reversal ensures continuity in the time domain, but this method causes audible clicks due to waveform phase reversals. This problem is overcome by using a pitch-synchronous phase vocoder method that generates time-varying harmonic amplitude and frequency envelopes. Applying the time-reversal looping method to these envelopes and converting to the time domain via sinusoidal additive synthesis can generate elongated versions of the original sound without audible clicks. To retain realism, original attack and decay time data are preserved. For shortening, envelopes are cross-faded between the attack-end and decay-begin points. As an application, the algorithm has been implemented in a score-processing music synthesis program.

K-nearest neighbour-based algorithm for P- and T-waves detection and delineation

The aim of an automated Electrocardiogram (ECG) delineation system is the reliable detection of the characteristic waveforms and determination of peaks and limits of individual QRS-complex, P- and T-waves. In this paper, a classical statistical pattern recognition algorithm characterized with high accuracy and stability, i.e., K-Nearest Neighbour (KNN) has been proposed for locating the fiducial points along with their waveform boundaries in ECG signals. First, the QRS-complex along with its onset and offset points of each beat is detected from the ECG signal. After that P- and T-wave, relative to each QRS-complex along with their onset and offset points, are then identified using this algorithm. The feature extraction is done using the gradient of the ECG signals. The performance of the proposed algorithm has been evaluated on two standard manually annotated databases, (i) CSE and (ii) QT, and also on ECG data acquired using BIOPAC®MP100 system in laboratory settings. The results in terms of accuracy, i.e., 92.8% for CSE database obtained, clearly indicate a high degree of agreement with the manual annotations made by the referees of CSE dataset-3. Further, the delineation results of the CSE and QT database are compared with the accepted tolerances as recommended by the CSE working party. The results for ECG records acquired using the BIOPAC®MP100 system, in terms of QRS duration, heart rate, QT-interval, P-wave duration and PR-interval using KNN algorithm have also been computed.

Methodology of QT‐Interval Measurement in the Modular ECG Analysis System (MEANS)

QT prolongation as can be induced by drugs, signals the risk of life-threatening arrhythmias. The methodology of QT measurement in the modular ECG analysis system (MEANS) is described. In the simultaneously recorded leads of the standard 12-lead electrocardiogram (ECG), the QRS complexes are detected by a spatial velocity function. They are typed as dominant or nondominant, and a representative complex per lead is obtained by averaging over the dominant complexes. QRS onset and T end are determined by a template technique, and QT is measured. MEANS performance was evaluated on the 125 ECGs of the common standards for quantitative electrocardiography (CSE) multilead database, of which the waveform boundaries have been released. MEANS detected correctly all 1445 complexes of the CSE library, with one false-positive detection due to a sudden baseline jump. All dominant complexes were correctly typed. The average of the differences between MEANS and reference was less than 2 ms (=1 sample) for both QRS onset and T end, and 2.1 ms for QT duration. The standard deviation of the differences was 3.8, 8.4, and 10.4 ms, respectively. A standard deviation of 10.4 ms for QT measurement seems large when related to the regulatory requirement that a prolongation as small as 5 ms should be detected. However, QT variabilities as encountered in different individuals will be larger than when measured in one individual during pharmacological intervention. Finally, if the U wave is part of the total repolarization, then T and U form a continuum and the end of T becomes questionable.

Robust Fourier descriptors for characterizing amplitude-modulated waveform shapes

Fourier descriptors (FD's) have traditionally been used to characterize the boundary shape of closed curves in computer-based images. This study examines the usefulness of FD's for characterizing the shape of amplitude-modulated waveform boundaries. Twenty-eight bioacoustic waveforms representing 7 species-specific sound groups were examined. Nearest-neighbor classification using 32-point waveform envelopes yielded 85.7% recognition rates when Euclidean distances with 8 or 12 FD's were employed. With 4 or 16 FD's, recognition was 82.1% but dropped to 71.4% when the number of FD's was reduced to 3. Evidently only the low-order 4 or 5 FD's are required to characterize most signals examined. Four FD's were adequate representation for linear discriminant analysis, wherein 27 (96.1%) of the samples were classified correctly, and for hierarchical cluster analysis, wherein 26 (92.9%) of the samples clustered into dendrogram subtrees corresponding to the known sound groups. Two sounds accounted for many errors in the classification experiments, and these differed from typical sounds for their respective species groups. In such cases, more than a single FD reference pattern may be required to adequately represent the sounds of a given species.

Automatic Detection of Wave Boundaries in Multilead ECG Signals: Validation with the CSE Database

This paper presents an algorithm for automatically locating the waveform boundaries (the onsets and ends of P, QRS, and T waves) in multilead ECG signals (the 12 standard leads and the orthogonal XYZ leads). Given these locations, features of clinical importance (such as the RR interval, the PQ interval, the QRS duration, the ST segment, and the QT interval) may be measured readily. First, a multilead QRS detector locates each beat, using a differentiated and low-pass filtered ECG signal as input. Next, the waveform boundaries are located in each lead. The leads in which the detected electrical activity is of longest duration are used for the final determination of the waveform boundaries. The performance of our algorithm has been evaluated using the CSE multilead measurement database. In comparison with other algorithms tested by the CSE, our algorithm achieves better agreement with manual measurements of the T-wave end and of interval values, while its measurements of other waveform boundaries are within the range of the algorithm and manual measurements obtained by the CSE.