Harmonic inversion of semiclassical short time signals

1997 ◽  
Vol 279 (5-6) ◽  
pp. 355-360 ◽  
Author(s):  
Frank Grossmann ◽  
Vladimir A. Mandelshtam ◽  
Howard S. Taylor ◽  
John S. Briggs
Author(s):  
DARIAN M. ONCHIŞ ◽  
ESPERANZA M. SÚAREZ SÁNCHEZ

This paper is concerned with the spectral decomposition and the adaptive analysis of data coming from car crash simulations. The mathematical ingredient of the proposed signal processing technique is the flexible Gabor-wavelet transform or the α-transform that reliably detects both high and low frequency components of such complicated short-time signals. We go from the functional treatment of this wavelet-type transform to its numerical implementation and we show how it can be used as an improved tool for spectral investigations compared to the short-time Fourier transform or the classical wavelet transform.


2009 ◽  
Vol 2009 ◽  
pp. 1-3
Author(s):  
Iwan Yahya

An analytical expression for measuring of sound transmission loss (TL) has been developed by using two microphones, an impedance tube and an impulse sound source as a proposed improvement to the existing procedure after Singh and Katra (1978). The calculation procedure is based on the autospectrum of short-time signals captured by the two microphones placed on two opposite positions from test sample while the sound source is on its surface. No spectral decomposition is required and the TL is calculated directly from the autospectrums of captured signals.


2005 ◽  
Vol 04 (02) ◽  
pp. 357-372
Author(s):  
JOHN JAIRO ZULUAGA ◽  
JORGE MAHECHA ◽  
EUGENE CHULKOV

A semi-classical propagator method combined with harmonic inversion of short time signals is used to find the resonant states of an electron interacting with a hydrogen atom near a metallic surface. The atom-electron interaction corresponds to one electron in the presence of a neutral compact core, which can be described by a simple local potential proposed by Cohen. On the other hand, the electron-surface interaction is described by a model proposed by Jennings, the so-called Jelly Model, or by a more realistic local potential that takes into account the shell structure of the metal. A semi-classical propagator approach, proposed by Herman and Kluk, is used to calculate an approximation to the autocorrelation function A(t) = <ψt|ψ0> entirely in terms of classical trajectories. A filter-diagonalization method for harmonic inversion of the complex time signal A(t) is applied to extract the resonances. We verified that the spectral analysis of the signal obtained by semi-classical methods gives satisfactory numerical results for the position and width of the lowest lying resonances.


1997 ◽  
Vol 107 (17) ◽  
pp. 6756-6769 ◽  
Author(s):  
Vladimir A. Mandelshtam ◽  
Howard S. Taylor

Author(s):  
Dževad Belkić ◽  
Karen Belkić

AbstractThe theme of this study is within the realm of basic nuclear magnetic resonance (NMR) spectroscopy. It relies upon the mathematics of signal processing for NMR in analytical chemistry and medical diagnostics. Our objective is to use the fast Padé transform (both derivative and nonderivative as well as parametric and nonparametric) to address the problem of multiplets from J-coupling appearing in total shape spectra as completely unresolved resonances. The challenge is exacerbated especially for short time signals (0.5 KB, no zero filling), encoded at a standard clinical scanner with the lowest magnetic field strengths (1.5T), as is the case in the present investigation. Water has partially been suppressed in the course of encoding. Nevertheless, the residual water content is still more than four times larger than the largest among the other resonances. This challenge is further sharpened by the following question: Can the J-coupled multiplets be resolved by an exclusive reliance upon shape estimation alone (nonparametric signal processing)? In this work, the mentioned parametric signal processing is employed only as a gold standard aimed at cross-validating the reconstructions from nonparametric estimations. A paradigm shift, the derivative NMR spectroscopy, is at play here through unprecedentedly parametrizing total shape spectra (i.e. solving the quantification problem) by sole shape estimators without fitting any envelope.


Author(s):  
Dževad Belkić ◽  
Karen Belkić

AbstractThe topic of this work is on reliable resolving of J-coupled resonances in spectral envelopes from proton nuclear magnetic resonance (NMR) spectroscopy. These resonances appear as multiplets that none of the conventional nonderivative shape estimators can disentangle. However, the recently formulated nonconventional shape estimator, the derivative fast Padé transform (dFPT), has a chance to meet this challenge. In the preceding article with a polyethylene phantom, using the time signals encoded with water suppressed, the nonparametric dFPT was shown to be able to split apart the compound resonances that contain the known J-coupled multiplets. In the present work, we address the same proton NMR theme, but with sharply different initial conditions from encodings. The goal within the nonparametric dFPT is again to accurately resolve the J-coupled resonances with the same polyethylene phantom, but using raw time signals encoded without water suppression. The parallel work on the same problem employing two startlingly unequal time signals, encoded with and without water suppression in the preceding and the current articles, respectively, can offer an answer to a question of utmost practical significance. How much does water suppression during encoding time signals actually perturb the resonances near and farther away from the dominant water peak? This is why it is important to apply the same dFPT estimator to the time signals encoded without water suppression to complement the findings with water suppression. A notable practical side of this inquiry is in challenging the common wisdom, which invariably takes for granted that it is absolutely necessary to subtract water from the encoded time signals in order to extract meaningful information by way of NMR spectroscopy.


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