22 papers · ranked by Valyu relevance
Sabrine Arfaoui, Riadh Chteoui, Anouar Ben Mabrouk
For a large community, of non mathematicians, a wavelet may be defined as a wave function which decays rapidly and which has besides a zero mean. Wavelet analysis consists of breaking up a signal into parts relatively to approximating functions obtained as shifted and dilated versions of the wavelet [3].
Birsel Ayrulu-Erdem, Billur Barshan
We extract the informative features of gyroscope signals using the discrete wavelet transform (DWT) decomposition and provide them as input to multi-layer feed-forward artificial neural networks (ANNs) for leg motion classification. Since the DWT is based on correlating the analyzed signal with a prototype wavelet…
Jonathan M. Lilly
A method is derived for the quantitative analysis of signals that are composed of superpositions of isolated, time-localized ‘events’. Here, these events are taken to be well represented as rescaled and phase-rotated versions of generalized Morse wavelets, a broad family of continuous analytic functions. Analysing a…
Erdal Dinç, Zehra Yazan
In research and development laboratories, chemical or pharmaceutical analysis has been carried out by evaluating sample signals obtained from instruments. However, the qualitative and quantitative determination based on raw signals may not be always possible due to sample complexity. In such cases, there is a need for…
Malika Jallouli, Makerem Zemni, Anouar Ben Mabrouk, Mohamed Ali Mahjoub
'Mohamed Ali Mahjoub'] Biosignals are nowadays important subjects for scientific researches from both theory and applications especially with the appearance of new pandemics threatening the humanity such as the new Coronavirus. One aim in the present work is to prove that Wavelets may be a successful machinery to…
Ali. F. Almutairi, A. Krishna
Filtered-orthogonal frequency division multiplexing (F-OFDM) is one of the most protruding multicarrier modulation (MCM) techniques for fifth-generation and beyond wireless communication. However, it possesses a high peak-to-average power ratio (PAPR), which results in its poor performance. Thus, a novel wavelet based…
Jean Gaudart, Stanislas Rebaudet, Gaetan Texier, Robert Barrais + 2 more
The aim of the present study was to develop a method for multiscale analysis of non-stationary and non-periodic epidemic time series. Indeed, the epidemiologists may need to know the features, at different resolutions, of short duration outbreaks that did not exhibit periodic cycles. Among of the large number of…
Alexandre Barbosa de Lima
We investigate the historical series of the total number of deaths per month in Brazil since 2015 using the wavelet transform, in order to assess whether the COVID-19 pandemic caused any change point in that series. Our wavelet analysis shows that the series has a change point in the variance. However, it occurred long…
Parikshit Dutta, Debashis Ghoshal, Arindam Lala
Wavelet analysis has been extended to the p-adic line Qp. The p-adic wavelets are complex valued functions with compact support. As in the case of real wavelets, the construction of the basis functions is recursive, employing scaling and translation. Consequently, wavelets form a representation of the affine group…
Abhisek Ukil
Magnetoencephalography (MEG) is an important noninvasive, nonhazardous technology for functional brain mapping, measuring the magnetic fields due to the intracellular neuronal current flow in the brain. However, the inherent level of noise in the data collection process is large enough to obscure the signal(s) of…
Noah Shore
University of Galway School of Mathematical and Statistical Sciences This work presents a wavelet-based approach to time-frequency fingerprinting for time series feature extraction, with a focus on audio identification from live recordings of traditional Irish tunes. The challenges of identifying features in…
Victor Vermehren Valenzuela, H. M. de Oliveira
Many continuous wavelets are defined in the frequency domain and do not have analytical expressions in the time domain. Meyer wavelet is ordinarily defined in this way. In this note, we derive new straightforward analytical expressions for both the wavelet and scale function for the Meyer basis. The validity of these…
Helena A. Merker, Isabella Dalla Betta, Matthew A. Wilson, Francisco J. Flores + 1 more
Rapid and accurate detection of electrographic seizures is critical for both clinical diagnosis and neuroscience research. Although seizure identification is commonly performed in the time domain, analysis in the time-frequency domain provides a more comprehensive representation of seizure characteristics. In this…
Stefan Scholl
—In digital signal processing time-frequency transforms are used to analyze time-varying signals with respect to their spectral contents over time. Apart from the commonly used short-time Fourier transform, other methods exist in literature, such as the Wavelet, Stockwell or Wigner-Ville transform. Consequently…
Michael X Cohen
Morlet wavelets are frequently used for time-frequency analysis of non-stationary time series data, such as neuroelectrical signals recorded from the brain. The crucial parameter of Morlet wavelets is the width of the Gaussian that tapers the sine wave. This width parameter controls the trade-off between temporal…
Laurence Zsu-Hsin Chuang, Li-Chung Wu, Jong-Hao Wang
Accelerometers, which can be installed inside a floating platform on the sea, are among the most commonly used sensors for operational ocean wave measurements. To examine the non-stationary features of ocean waves, this study was conducted to derive a wavelet spectrum of ocean waves and to synthesize sea surface…
Jianhua Xu
Title: Graphical abstract
Y. Zhou, A. Sheremet, Y. Qin, J.P. Kennedy + 2 more
Local field potential (LFP) oscillations are the superposition of excitatory/inhibitory postsynaptic potentials. In the hippocampus, the 20-55 Hz range (‘slow gamma’) is proposed to support cognition independent of other frequencies. However, this band overlaps with theta harmonics. We aimed to dissociate the…
Malika Jallouli, Sabrine Arfaoui, Anouar Ben Mabrouk, Carlo Cattani + 2 more
Analysis of the fetal heart rate during pregnancy is essential for monitoring the proper development of the fetus. Current fetal heart monitoring techniques lack the accuracy in fetal heart rate monitoring and features acquisition, resulting in diagnostic medical issues. The challenge lies in the extraction of the…
Vasile V. Moca, Adriana Nagy-Dăbâcan, Harald Bârzan, Raul C. Mureşan
Time-frequency analysis is ubiquitous in many fields of science. Due to the Heisenberg-Gabor uncertainty principle, a single measurement cannot estimate precisely the localization of a finite oscillation in both time and frequency. Classical spectral estimators, like the short-time Fourier transform (STFT) or the…
Authors not listed
This report compares various simulation and data analysis methods for free induction decay (FID) signals in Nuclear Magnetic Resonance (NMR) Spectroscopy. The methods discussed include discrete fast Fourier transformation (FFT), least squares fitting (LSF), short-time Fourier transformation (STFT), and wavelet…
Authors not listed
Purpose: The transmission Fourier-transform infrared (FTIR) spectrum contains complexed signals for molecular structures and intermolecular interactions. Their interrelated signals were attempted to be recognized using the singular value decomposition (SVD) procedure. Methods: Cimetidine (CIM) and indomethacin (INM)…