The Experts below are selected from a list of 7479 Experts worldwide ranked by ideXlab platform
Lalu Mansinha - One of the best experts on this subject based on the ideXlab platform.
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Time-local Fourier analysis with a scalable, phase-modulated analyzing function: the S -transform with a complex Window
Signal Processing, 2004Co-Authors: C. R. Pinnegar, Lalu MansinhaAbstract:The S-transform was originally defined as a method of determining the local spectrum of a time series, through the use of a translating, real Gaussian Window that dilates to accomodate the different cycle durations of different frequencies. The S-transform "wavelet" is obtained by multiplying this real Window with the complex Fourier sinusoid. Since the Fourier sinusoid has time-invariant frequency, the S-transform is consequently unsuitable for resolving waveforms whose frequency changes with time. This problem can be addressed by introducing a complex Gaussian Window, with a user designed, complex phase function. The phase function modulates the frequency of the Fourier sinusoid to give a specific waveform, leading to better time frequency localization of similar waveforms on the time series. The complex-Window S-transform is similar to a wavelet transform, but has the fixed phase reference of the Fourier transform.
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Localization of the complex spectrum: the S transform
IEEE Transactions on Signal Processing, 1996Co-Authors: R. G. Stockwell, Lalu Mansinha, R. P. LoweAbstract:The S transform, which is introduced in the present correspondence, is an extension of the ideas of the continuous wavelet transform (CWT) and is based on a moving and scalable localizing Gaussian Window. It is shown to have some desirable characteristics that are absent in the continuous wavelet transform. The S transform is unique in that it provides frequency-dependent resolution while maintaining a direct relationship with the Fourier spectrum. These advantages of the S transform are due to the fact that the modulating sinusoids are fixed with respect to the time axis, whereas the localizing scalable Gaussian Window dilates and translates.
Shih-gu Huang - One of the best experts on this subject based on the ideXlab platform.
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Adaptive STFT with Chirp-Modulated Gaussian Window
2018 IEEE International Conference on Acoustics Speech and Signal Processing (ICASSP), 2018Co-Authors: Shih-gu HuangAbstract:In this paper, we propose an adaptive STFT (ASTFT) with adaptive chirp-modulated Gaussian Window. The Window is obtained from rotating Gaussian function in time-frequency plane by fractional Fourier transform (FRFT). It is completely adaptive where the two parameters, FRFT rotation angle and Gaussian variance, are signal-dependent. The angle dependents on the chirp rate of the signal. The variance is determined by the chirp rate and its first derivative. Considering the input may be multicomponent, a chirp-modulated Gaussian Window with time-frequency-varying angle and variance is developed. The proposed ASTFT has very high energy concentration and less interference between components in noiseless and noisy environments.
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ICASSP - Adaptive STFT with Chirp-Modulated Gaussian Window
2018 IEEE International Conference on Acoustics Speech and Signal Processing (ICASSP), 2018Co-Authors: Soo-chang Pei, Shih-gu HuangAbstract:In this paper, we propose an adaptive STFT (ASTFT) with adaptive chirp-modulated Gaussian Window. The Window is obtained from rotating Gaussian function in time-frequency plane by fractional Fourier transform (FRFT). It is completely adaptive where the two parameters, FRFT rotation angle and Gaussian variance, are signal-dependent. The angle dependents on the chirp rate of the signal. The variance is determined by the chirp rate and its first derivative. Considering the input may be multicomponent, a chirp-modulated Gaussian Window with time-frequency-varying angle and variance is developed. The proposed ASTFT has very high energy concentration and less interference between components in noiseless and noisy environments.
Vitaliy Lomakin - One of the best experts on this subject based on the ideXlab platform.
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Gaussian-Windowed frame based method of moments formulation of surface-integral-equation for extended apertures
Journal of Computational Physics, 2016Co-Authors: Amir Shlivinski, Vitaliy LomakinAbstract:Scattering or coupling of electromagnetic beam-field at a surface discontinuity separating two homogeneous or inhomogeneous media with different propagation characteristics is formulated using surface integral equation, which are solved by the Method of Moments with the aid of the Gabor-based Gaussian Window frame set of basis and testing functions. The application of the Gaussian Window frame provides (i) a mathematically exact and robust tool for spatial-spectral phase-space formulation and analysis of the problem; (ii) a system of linear equations in a transmission-line like form relating mode-like wave objects of one medium with mode-like wave objects of the second medium; (iii) furthermore, an appropriate setting of the frame parameters yields mode-like wave objects that blend plane wave properties (as if solving in the spectral domain) with Green's function properties (as if solving in the spatial domain); and (iv) a representation of the scattered field with Gaussian-beam propagators that may be used in many large (in terms of wavelengths) systems.
Augustus J. E. M. Janssen - One of the best experts on this subject based on the ideXlab platform.
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Optimality property of the Gaussian Window spectrogram
IEEE Transactions on Signal Processing, 1991Co-Authors: Augustus J. E. M. JanssenAbstract:It is shown that for any signal x(t) the minimum of integral /sub - infinity //sup infinity / integral /sub - infinity //sup infinity / ((t-t/sub x/)/sup 2/+(f-f/sub x/)/sup 2/) S/sub x//sup (w)/(t, f) dt df over all normalized time-Windows w(t) is achieved by the Gaussian Window w(t)=2/sup 1/4/ exp (- pi t/sup 2/). Here (t/sub x/, f/sub x/) is the center of gravity of the signal x(t), S/sub x//sup (w)/ (t, f) is the spectrogram of x(t) due to the Window w(t), and the double integral is a measure of the spread of S/sub x//sup (w)/ (t, f) around (t/sub x/, f/sub X/) in the time-frequency plane. >
Peter D. Wentzell - One of the best experts on this subject based on the ideXlab platform.
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A modification to Window target-testing factor analysis using a Gaussian Window
Chemometrics and Intelligent Laboratory Systems, 2000Co-Authors: Christopher D. Brown, Peter D. WentzellAbstract:Abstract A procedure referred to as Window target-testing factor analysis (WTTFA) was recently proposed for confirming the presence of target analytes in complex spectrochromatographic applications. In this paper, a modification to the original method is proposed which uses a Gaussian mask to adapt the Window shape to that of the elution profile. It is shown that this alteration results in significant improvements in the performance of the WTTFA algorithm.
