Prototype Waveforms Research Articles

Performance of a novel DC-DC low voltage stress boost converter for fuel-cell vehicle

Air pollution, global warming, depletion of fossil fuels and the lack of access to them due to potential political conflicts are some of the challenges that have forced governments to take necessary measures to promote and invest in the development of electric vehicles (EVs). One of the most important parts of EVs is dc-dc converter. A novel step-up single-switch unidirectional topology for a dc-dc converter is proposed in this paper. Some of the advantages of the proposed topology are the use of single-switch, ground switching, low input current ripple, wide range of voltage gain (VG), high level of VG, low stress level for semiconductor components, low input current ripple, small number of semiconductor and passive elements, high efficiency, and no need for high frequency transformer or coupled inductors. Topology analysis is done in continuous current mode (CCM) and calculations related to efficiency and appropriate design are performed to select the converter parameter values. Also, the proposed topology is compared with other similar topologies to show its high performance and superiority. To confirm the theoretical basis, laboratory prototype waveforms are evaluated and an efficiency of 93.2% is obtained.

Non-linear primary-multiple separation with directional curvelet frames

SUMMARY Predictive multiple suppression methods consist of two main steps: a prediction step, during which multiples are predicted from seismic data, and a primary-multiple separation step, during which the predicted multiples are ‘matched’ with the true multiples in the data and subsequently removed. This second separation step, which we will call the estimation step, is crucial in practice: an incorrect separation will cause residual multiple energy in the result or may lead to a distortion of the primaries, or both. To reduce these adverse effects, a new transformed-domain method is proposed where primaries and multiples are separated rather than matched. This separation is carried out on the basis of differences in the multiscale and multidirectional characteristics of these two signal components. Our method uses the curvelet transform, which maps multidimensional data volumes into almost orthogonal localized multidimensional prototype waveforms that vary in directional and spatio-temporal content. Primaries-only and multiples-only signal components are recovered from the total data volume by a non-linear optimization scheme that is stable under noisy input data. During the optimization, the two signal components are separated by enhancing sparseness (through weighted l1-norms) in the transformed domain subject to fitting the observed data as the sum of the separated components to within a user-defined tolerance level. Whenever, during the optimization, the estimates for the primaries in the transformed domain correlate with the predictions for the multiples, the recovery of the coefficients for the estimated primaries will be suppressed while for regions where the correlation is small the method seeks the sparsest set of coefficients that represent the estimation for the primaries. Our algorithm does not seek a matched filter and as such it differs fundamentally from traditional adaptive subtraction methods. The method derives its stability from the sparseness obtained by a non-parametric (i.e. not depending on a parametrized physical model) multiscale and multidirectional overcomplete signal representation. This sparsity serves as prior information and allows for a Bayesian interpretation of our method during which the log-likelihood function is minimized while the two signal components are assumed to be given by a superposition of prototype waveforms, drawn independently from a probability function that is weighted by the predicted primaries and multiples. In this paper, the predictions are based on the data-driven surface-related multiple elimination method. Synthetic and field data examples show a clean separation leading to a considerable improvement in multiple suppression compared to the conventional method of adaptive matched filtering. This improved separation translates into an improved stack.

A Clean Four-Quadrant Sinusoidal Power Rectifier Using Multistage Converters for Subway Applications

A special 27-level four-quadrant rectifier for subway applications is analyzed. The arrangement uses only three H-bridges per phase, common dc bus, and independent input transformers for each H-bridge. The transformers allow galvanic isolation and power escalation to obtain high-quality voltage waveforms, with total harmonic distortion of less than 1%. Some advantages of this 27-level rectifier are: 1) only one of the three H-bridges, called the main converter, manages more than 80% of the total active power in each phase and 2) it switches at fundamental frequency, reducing the switching losses at a minimum value. The rectifier analyzed in this paper is a current-controlled voltage-source type, with a conventional feedback control loop. Some simulations in a rectifier substation, including power reversal at full load are displayed (750 Vdc, 1200 A). The rectifier shows the ability to produce clean ac and dc waveforms without any ripple, and fast reversal of power. Some experimental results with a small prototype, showing voltage and current waveforms, are finally displayed.

Synthesis of speech from pitch prototype waveforms by time-synchronous waveform interpolation

In a method of synthesizing voiced speech from pitch prototype waveforms by time-synchronous waveform interpolation (TSWI), one or more pitch prototypes is extracted from a speech signal or a residue signal. The extraction process is performed in such a way that the prototype has minimum energy at the boundary. Each prototype is circularly shifted so as to be time-synchronous with the original signal. A linear phase shift is applied to each extracted prototype relative to the previously extracted prototype so as to maximize the cross-correlation between successive extracted prototypes. A two-dimensional prototype-evolving surface is constructed by unsampling the prototypes to every sample point. The two-dimensional prototype-evolving surface is re-sampled to generate a one-dimensional, synthesized signal frame with sample points defined by piecewise continuous cubic phase contour functions computed from the pitch lags and the phase shifts added to the extracted prototypes. A pre-selection filter may be applied to determine whether to abandon the TSWI technique in favor of another algorithm for the current frame. A post-selection performance measure may be obtained and compared with a predetermined threshold to determine whether the TSWI algorithm is performing adequately.

Robust waveform interpolation for the entire speech signal

In waveform interpolation (WI), a speech signal is reconstructed by the concatenation of infinitesimal segments of an evolving characteristic waveform, which is obtained by interpolation over time [W. B. Kleijn, IEEE Trans. Speech Audio Process. 1, 386–399 (1993)]. WI leads to efficient coding of voiced speech, but current implementations switch to CELP for nonperiodic signals. The WI paradigm is extended to provide an effective basis for the coding of voiced and unvoiced speech and background noise. Prototype waveforms are extracted every 2.5 ms. At this high rate the WI analysis–synthesis system results in transparent speech quality. Each prototype waveform is decomposed into a slowly evolving waveform (SEW), obtained by convolution in time with a 40-ms smoothing window, and a remainder, the rapidly evolving waveform (REW). Because of its low bandwidth, a low bit rate suffices for the SEW (additional processing lowers the bit rate further), while the REW requires only a rough statistical description (e.g., its phase spectrum can be randomized). The new paradigm facilitates efficient, robust speech coding in the range 2–8 kb/s.

Encoding speech using prototype waveforms

Voiced speech is interpreted as a concentration of slowly evolving pitch-cycle waveforms. This signal can be reconstructed by interpolation from a downsampled sequence of pitch-cycle waveforms with a rate of one prototype waveform per 20-30 ms interval. The prototype waveform is described by a set of linear-prediction (LP) filter coefficients describing the formant structure and a prototype excitation waveform, quantized with analysis-by-synthesis procedures. The speech signal is reconstructed by filtering an excitation signal consisting of the concatenation of (infinitesimal) sections of the instantaneous excitation waveforms. To obtain the correct level of periodicity, the short-term and the long-term correlations between the instantaneous excitation waveforms can be controlled explicitly. Thus, distortions such as noise, reverberation, and buzziness can be prevented. The coding method is easily combined with existing LP-based speech coders, such as CELP, for unvoiced signals. Excellent voiced speech quality is obtained at rates between 3.0 and 4.0 kb/s. >

Generation of ECG prototype waveforms by piecewise correlational averaging

Describes a novel approach to the processing of ECG data. The procedure constructs a prototype waveform and generates timing statistics on the waveform components within the beats. Individual segments, defined heuristically to separate the <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">P</i> , <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">QRS</i> , and <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">T</i> waves in each recorded waveform, are aligned by correlation and averaged independently. The individual segment averages are subsequently concatenated to form the prototype. The new prototype is shown to correlate better with the ensemble of data waveforms than does the conventional time-locked average. The process also generates intrabeat statistics that describe the relative latency fluctuations within the waveform population.

Estimation of laryngeal control parameters from glottal waveforms

Clinical assessment of phonatory skills and laryngeal abnormalities would be facilitated ff a method of relating laryngeal muscular control and glottal configuration to glottal waveforms could be found. A computer model of the vocal folds, described earlier, which uses control parameters closely related to laryngeal muscular contractions, and which allows for sufficient flexibility in tissue properties and configuration, has been used to generate prototype waveforms of glottal transconductance and glottal volume velocity. The relationship between model control parameters and the resultant waveforms is determined by multiple regression. Success in predicting model control parameters from waveform parameters is demonstrated, and the applicability of this method to clinical situations is discussed.