An efficient procedure is proposed for the realization of robust short-time Fourier transform (STFT) based on the recursive realization of the standard STFT. In the initial stage it uses the robust STFT calculated by iterative or sorting procedures and, after that, the recursive relation is applied. Basic difference from the standard STFT realization is in limiting samples in the next instants,...

In this paper, we present an algorithm to estimate a signal from its modified short-time Fourier transform (STFT). This algorithm is computationally simple and is obtained by minimizing the mean squared error between the STFT of the estimated signal and the modified STFT. Using this algorithm, we also develop an iterative algorithm to estimate a signal from its modified STFT magnitude. The iter...

Magnetoencephalography (MEG) has a high temporal resolution well-suited for studying perceptual learning. However, to identify where learning happens in the brain, one needs to apply source localization techniques to project MEG sensor data into brain space. Previous source localization methods, such as the short-time Fourier transform (STFT) method by Gramfort et al.([6]) produced intriguing r...

Shift and rotation invariance properties of linear time-frequency representations are investigated. It is shown that among all linear time-frequency representations, only the short-time Fourier transform (STFT) family with the Hermite–Gaussian kernels satisfies both the shift invariance and rotation invariance properties that are satisfied by the Wigner distribution (WD). By extending the time-...

A new estimator for evolutionary spectrum (ES) based on short time Fourier transform (STFT) and modified group delay function (MGDF) by signal decomposition (SD) is proposed. The STFT due to its built-in averaging, suppresses the cross terms and the MGDF preserves the frequency resolution of the rectangular window with the reduction in the Gibbs ripple. The present work overcomes the magnitude ...

Design of time-frequency distributions (TFDs) that are robust to the impulse noise influence is considered. The robust TFDs based on the robust short-time Fourier transform (STFT) are proposed. An efficient procedure to evaluate the robust STFT is given. Robust TFDs based on the robust STFT have better energy concentration around the signal instantaneous frequency (IF) than the robust STFT itse...

Magnetoencephalography (MEG) has a high temporal resolution well-suited for studying perceptual learning. However, to identify where learning happens in the brain, one needs to apply source localization techniques to project MEG sensor data into brain space. Previous source localization methods, such as the short-time Fourier transform (STFT) method by Gramfort et al.([6]) produced intriguing r...

For the past five decades there has been a substantial increase in the development of computer applications based on the STFT (Short-Time Fourier Transform) spectrograms. Amongst others, a relevant example of this kind of implementation is speech analysis. Indeed, if the audio signal is correctly filtered, it is possible to use STFT spectrogram techniques to recognize speech. This work investig...

We address the problem of recovering a signal (up to global phase) from its short-time Fourier transform (STFT) magnitude measurements. This problem arises in several applications, including optical imaging and speech processing. In this paper we suggest three interrelated algorithms. The first algorithm estimates the signal efficiently from noisy measurements by solving a simple least-squares ...

In this paper we propose a multichannel feature compensation approach for automatic speech recognition in reverberant and noisy environments. The proposed technique propagates the posterior of the clean signal estimated by a multichannel Wiener filter in short-time Fourier transform (STFT) domain into Mel-frequency cepstrum coefficients (MFCC) domain. The multichannel Wiener filter reduces both...