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Characterization and decomposition of waveforms for Larsen 500 airborne system
IEEE Transactions on Geoscience and Remote Sensing, 1991The authors describe a method of accurately decomposing a Larsen waveform into the surface and bottom reflections, independently of the degree of their overlap. A mathematical model that can be used to characterize the Larsen waveforms received under diverse circumstances is established.
Henry C. Wong, Andreas Antoniou
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Elastic Full Waveform Inversion With Angle Decomposition and Wavefield Decoupling
IEEE Transactions on Geoscience and Remote Sensing, 2021Full waveform inversion (FWI) is a powerful tool to understand the real complicated earth model. As FWI is a highly nonlinear problem and depends strongly on the initial model, how to effectively retrieve the large-scale background model is critical for the success of FWI. For elastic FWI (EFWI), the inversion challenge increases because the P-wave and
Jingrui Luo +3 more
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Gaussian pulse decomposition: An intuitive model of electrocardiogram waveforms
Annals of Biomedical Engineering, 1997This study presents a novel approach to modeling the electrocardiogram (ECG): the Gaussian pulse decomposition. Constituent waves of the ECG are decomposed into and represented by Gaussian pulses using an iterative algorithm: the chip away decomposition (ChAD) algorithm. At each iteration, a nonlinear minimization method is used to fit a portion of the
S, Suppappola, Y, Sun, S A, Chiaramida
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Spectral Decomposition and Waveform Classification
2016Abstract Chapter 7 covers spectral decomposition, thin-bed analysis, and waveform classification.
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Generalized Gaussian decomposition for full waveform LiDAR processing
Measurement Science and Technology, 2022Abstract Waveform decomposition techniques are commonly used to extract attributes of targets from light detection and ranging (LiDAR) waveforms. Since the shape of a real LiDAR waveform varies for different systems, the conventional models (e.g.
Zhiyong Gu +5 more
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Efficient waveform decomposition on airborne laser bathymetry
IEEE Pacific Rim Conference on Communications, Computers, and Signal Processing. Proceedings, 2002A technique for the efficient processing of bathymetric data is presented. First, the characteristics of bathymetric signals are analyzed in the time domain. A bathymetric signal is characterized by three components that represent the blue-green surface reflection, volume backscatter, and bottom reflection.
W. Cheng, W.-S. Lu, A. Antoniou
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Decomposition of superimposed waveforms using the cross time frequency transform
2000 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.00CH37100), 2002The identification of the timing of the discharges of groups of muscle fibers (motor units) is of utmost importance in research into the strategies employed by the central nervous system in producing muscle force as well as in the clinical diagnosis of neuromuscular diseases.
Paolo Bonato, Z. Erim
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Haar wavelet-based decomposition of nonactive power for nonsinusoidal waveforms
2005 IEEE Russia Power Tech, 2005This paper deals with some key properties of the nonactive power resulting from non-sinusoidal periodical voltage and current waveforms represented by using discrete samples. The Haar wavelet-based decomposition of the waveforms, written in a form consistent with a multi-resolution approach, provides the transformed voltage and current vectors.
M. PETRESCU, CHICCO, GIANFRANCO
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Accurate Decomposition of Full Waveform Sonic Data
Middle East Oil, Gas and Geosciences Show (MEOS GEO)Abstract Full waveform sonic data is typically dominated by strong direct wave mode propagating along the borehole, which obscures the weak reflected signals of interest. Therefore, accurate wave mode decomposition is an essential step in enhancing the interpretability of full waveform sonic data, particularly for applications such as ...
Lu Liu, Thierry Tonellot, Hussain Salim
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Applied Optics, 2019
The light detection and ranging (LIDAR) full-waveform echo decomposition method based on empirical mode decomposition (EMD) and the local-Levenberg-Marquard (LM) algorithm is proposed in this paper. The proposed method can decompose the full-waveform echo into a series of components, each of which can be assumed as essentially Gaussian.
Wu, Qinqin +3 more
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The light detection and ranging (LIDAR) full-waveform echo decomposition method based on empirical mode decomposition (EMD) and the local-Levenberg-Marquard (LM) algorithm is proposed in this paper. The proposed method can decompose the full-waveform echo into a series of components, each of which can be assumed as essentially Gaussian.
Wu, Qinqin +3 more
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