Many short-time Fourier transform (STFT) based singlechannel speech enhancement algorithms are focused on estimating clean speech spectral amplitude from the noisy observed signal in order to suppress the additive noise. To this end, the state-of-the-art speech enhancement algorithms, employ noisy amplitude information and correspondingly a priori and a posteriori SNRs while they use no informa...

This paper describes the design and development of new graphical software for spectral audio processing. There are three phases to accomplish the audio processing. First, spectrograms are generated from an input audio signal using Short-Time Fourier Transform (STFT) analysis, and the sonogram image is continually shifting from right to left. Secondly, the sonogram is transformed by placing prep...

Time-frequency analysis is commonly used for fault detection in induction motors. A variety of signal decomposition techniques have been proposed the literature, such as Wavelet transform, Empirical Mode Decomposition (EMD), Multiple Signal Classification (MUSIC), among others. They successfully many works related with topic. Nevertheless, studied signals present amplitude changes and chirp-typ...

Vibration problems in rotors can be extremely frustrating and may lead to greatly reduced reliability. By utilizing the proper data collection and analysis techniques, the faults because of vibration can be discovered and predicted. The signal analysis is important in extracting fault characteristics in fault diagnosis of machinery. The traditional signal analysis can not settle for non-station...

The modification of magnitude spectrograms is at the core of many audio signal processing methods, from source separation to sound modification or noise canceling, and reconstructing a natural sounding signal in such situations is thus a very important issue. This article presents recent theoretical and experimental developments on the application to signal reconstruction from a modified magnit...

In this paper, the authors attempt to automatic generation of drum beats using generative adversarial networks (GAN). The generator GAN is trained with short-time Fourier transform (STFT) from a diversified dataset, while discriminator challenges generator. generator, once trained, able produce close real-time sequences. Also, we propose do subjective evaluation generated beats. simulation resu...

This paper proposes a new estimator for evolutionary spectrum (ES) based on short time Fourier transform (STFT) and modified group delay function (GDFM). The STFT due to its built-in averaging suppresses the crossterms and the GDFM preserves the frequency resolution of the rectangular window as it reduces the Gibbs ripple without using any window function. The new estimator is applicable to ran...

In this paper, we analyze the performance of cross-band adaptation in the short-time Fourier transform (STFT) domain for the application of acoustic echo cancellation. The band-to-band lters and the cross-band lters considered in each frequency-band are all estimated by adaptive lters, which are updated by the LMS algorithm. We derive explicit expressions for the transient and steady-state mean...

Many short-time Fourier transform (STFT) based singlechannel speech enhancement algorithms are focused on estimating clean speech spectral amplitude from the noisy observed signal in order to suppress the additive noise. To this end, the state-of-the-art speech enhancement algorithms, employ noisy amplitude information and correspondingly a priori and a posteriori SNRs while they use no informa...

A novel approach is proposed for Electroencephalogram signal classification using Artificial Neural Network based on Independent Component Analysis and Short Time Fourier Transform. The source EEG signals contain the electrical activity of the brain produced in the background by the cerebral cortex nerve cells. EEG is one of the most utilized methods for effective analysis of the brain function...