Results 181 to 190 of about 10,051 (219)
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On the interpretation of Wigner distribution by STFT
Proceedings of Third International Conference on Signal Processing (ICSP'96), 2002A new relation between the Wigner distribution (WD) and the short-time Fourier transform (STFT) is given in this paper. Based on this relation, we interpreted the time-frequency resolution, producing and distributing the cross terms of the WD in the view of the windows of STFT.
null Xiaobing Sun, null Zheng Bao
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From the STFT to the Wigner Distribution [Lecture Notes]
IEEE Signal Processing Magazine, 2014The analysis, processing, and parameters estimation of signals whose spectral content changes in time are of crucial interest in many applications, including radar, acoustics, biomedicine, communications, multimedia, seismic, and the car industry [1]? [11]. Various signal representations have been introduced to deal with this kind of signals within the
Ljubisa Stankovic +2 more
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A fast recursive STFT algorithm
Proceedings of 8th Mediterranean Electrotechnical Conference on Industrial Applications in Power Systems, Computer Science and Telecommunications (MELECON 96), 2002The short-time Fourier transform (STFT) of a signal maps a one-dimensional signal, into a two-dimensional signal in the time-frequency plane. The combination of time-domain and frequency-domain analysis yields a more revealing picture of the signal, showing which spectral components are presented in the signal at a given time.
S. Tomazic, S. Znidar
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Spectral broadening of lower extremity venous Doppler signals using STFT and AR modeling
, 2008 This study researches the behaviour of spectral broadening index (SBI) obtained from spectra achived using short-time Fourier transform (STFT) analysis compared to that of SBI based on autoregressive (AR) modeling of clinical Doppler lower extremity vein
Sadik Kara
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Realization of arbitrary filters in the STFT domain
2009 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, 2009It is well known that FIR filters can be efficiently realized in the short-time Fourier transform domain, namely using sliding windows and FFTs. In some scenarios, however, the standard overlap-add or overlap-save block convolution algorithms may be impractical due to the need for large transforms to implement long filters.
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An adaptive STFT using energy concentration optimization
2015 10th International Conference on Information, Communications and Signal Processing (ICICS), 2015This work is inspired by a kind of S-transforms which employ a window width optimization strategy. Since the main objective of their methods is to adjust the window width passively by controlling the standard deviation function of the Gaussian window, we realize it in a way more straightly.
Mingzhe Zhu, Xinliang Zhang, Yue Qi
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STFT-based denoising of biomechanical impact signals
2010 Annual International Conference of the IEEE Engineering in Medicine and Biology, 2010We present an advanced denoising method for non-stationary biomechanical signals with the aim of accurately estimating their second derivative (acceleration). The proposed algorithm is based on the short-time Fourier transform (STFT) representation of the signal and its subsequent modification by means of a suitable time-varying filtering function. The
Hon, Tsz K. +2 more
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Adaptive STFT with Chirp-Modulated Gaussian Window
2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2018In 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
Soo-Chang Pei, Shih-Gu Huang
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Adaptive interference removal based on concentration of the STFT
Digital Signal Processing, 2006We propose a new method for adaptively removing noise and interference from a signal. In this method unwanted components are removed from the short time Fourier transform (STFT) surface, and the clean signal is estimated by integrating the modified STFT with respect to frequency.
Douglas J. Nelson, David C. Smith
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The STFT-Based Estimator of Micro-Doppler Parameters
IEEE Transactions on Aerospace and Electronic Systems, 2017A two-stage technique for estimating micro-Doppler signal parameters has been proposed. In the first stage, rough parameter estimations are performed by regression of instantaneous frequency estimate obtained from the short-time Fourier transform. Afterwards, rough estimates are refined in the second stage. The proposed technique has better performance
Igor Djurovic +2 more
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