This paper presents the results of time (autocorrelation) and time-frequency (spectrogram) analyses of radar signals returned from the moving human targets. When a radar signal falls on the human target which is moving toward or from the radar, the signals reflected from different parts of his body produce a Doppler shift that is proportional to the velocity of those parts. Moving parts of the ...

This paper concerns the mean square error optimal weighting factors for multiple window spectrogram of different stationary and nonstationary processes. It is well known that the choice of multiple windows is important, but here we show that the weighting of the different multiple window spectrograms in the final average is as important to consider and that the equally averaged spectrogram is n...

The reliability of data transmission in Wireless Sensor Networks (WSN) is always an issue in harsh industrial environments and sets specific challenges for performance optimization. Short-term signal disturbances, in the form of multipath fading and destructive radio interference, are of major concern due to signal path conditions (large concrete and metal surfaces), related line-of-sight (LOS)...

Improving speech system performance in noisy environments remains a challenging task, and speech enhancement (SE) is one of the effective techniques to solve the problem. Motivated by the promising results of generative adversarial networks (GANs) in a variety of image processing tasks, we explore the potential of conditional GANs (cGANs) for SE, and in particular, we make use of the image proc...

The main goal of the present work is to study the coherent phonon in strongly confined CdSe quantum dots (QDs) under varied pump fluences. The main characteristics of coherent phonons (amplitude, frequency, phase, spectrogram) of CdSe QDs under the red-edge pump of the excitonic band [1S(e)-1S3/2(h)] are reported. We demonstrate for the first time that the amplitude of the coherent optical long...

In this paper, we present a novel texture image feature for Emotion Sensing in Speech (ESS). This idea is based on the fact that the texture images carry emotion-related information. The feature extraction is derived from time-frequency representation of spectrogram images. First, we transform the spectrogram as a recognizable image. Next, we use a cubic curve to enhance the image contrast. The...

Nonnegative matrix factorization (NMF) is a popular linear regression technique in the fields of machine learning and signal/image processing. Much research about this topic has been driven by applications in audio. NMF has been for example applied with success to automatic music transcription and audio source separation, where the data is usually taken as the magnitude spectrogram of the sound...

In radar high-resolution range profile (HRRP)-based statistical target recognition, one of the most challenging task is the feature extraction. This article utilizes spectrogram feature of HRRP data for improving the recognition performance, of which the spectrogram is a two-dimensional feature providing the variation of frequency domain feature with time domain feature. And then, a new radar H...

A recent approach to signal segmentation in additive noise [1, 2] uses features of small spectrogram sub-units accrued over the full spectrogram. The original work considered chirp signals in additive white Gaussian noise. This paper extends this work first by considering similar signals at different signal-to-noise ratios and then in the context of speech recognition. For the chirp case, a cos...

We describe a new technique called Pipeline Spectroscopy that allows us to precisely measure the cost of each cache miss. The cost of a miss is displayed (graphed) as a histogram, which represents a precise readout showing a detailed visualization of the cost of each cache miss throughout all levels of the memory hierarchy. We call the graphs ‘spectrograms’ because they reveal certain signature...