18 papers · ranked by Valyu relevance
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…
Yash Paul
Epilepsy is a chronic chaos of the central nervous system that influences individual’s daily life by putting it at risk due to repeated seizures. Epilepsy affects more than 2% people worldwide of which developing countries are affected worse. A seizure is a transient irregularity in the brain’s electrical activity that…
Irina Pugach, Rostislav Matveyev, Andreas Wollstein, Manfred Kayser + 1 more
'Mark Stoneking'] We describe a PCA-based genome scan approach to analyze genome-wide admixture structure, and introduce wavelet transform analysis as a method for estimating the time of admixture. We test the wavelet transform method with simulations and apply it to genome-wide SNP data from eight admixed human…
Lukas P. A. Arts, Egon. L. van den Broek
The spectral analysis of signals is currently either dominated by the speed-accuracy trade-off or ignores a signal’s often non-stationary character. Here we introduce an open-source algorithm to calculate the fast continuous wavelet transform (fCWT). The parallel environment of fCWT separates scale-independent and…
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…
Lukasz Wiklendt, Simon J. H. Brookes, Marcello Costa, Lee Travis + 2 more
'Nick J. Spencer' 'Phil G. Dinning'] In electrophysiology, many methods have been proposed for the analysis of action potential firing frequencies. The aim of this study was to present an algorithm developed for a continuous wavelet transform that enables the filtering out of frequencies contributing to the shapes of…
M. S. Priyadarshini, Mohit Bajaj, Lukas Prokop, Milkias Berhanu
Electric power utilities must ensure a consistent and undisturbed supply of power, with the voltage levels adhering to specified ranges. Any deviation from these supply specifications can lead to malfunctions in equipment. Monitoring the quality of supplied power is crucial to minimize the impact of fluctuations in…
Yuvraj V. Parkale, Sanjay L. Nalbalwar
Background Compressed sensing is a novel signal compression technique in which signal is compressed while sensing. The compressed signal is recovered with the only few numbers of observations compared to conventional Shannon-Nyquist sampling, and thus reduces the storage requirements. In this study, we have proposed…
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…
Tanya L Leise
We review time-frequency methods that can be useful in quantifying circadian and ultradian patterns in behavioral records. These records typically exhibit details that may not be captured through commonly used measures such as activity onset and so may require alternative approaches. For instance, activity may involve…
Eric Rawls
Time-frequency (TF) analysis of M/EEG data enables rich understanding of cortical dynamics underlying cognition, health, and disease. There are many algorithms for time-frequency decomposition of M/EEG neural data, but they are implemented in an inconsistent manner and most existing toolboxes either 1) contain only one…
Richard Harang, Guillaume Bonnet, Linda R Petzold
Background Wavelets have proven to be a powerful technique for the analysis of periodic data, such as those that arise in the analysis of circadian oscillators. While many implementations of both continuous and discrete wavelet transforms are available, we are aware of no software that has been designed with the…
Miguel A. Rodriguez-Hernandez
The Undecimated Wavelet Transform is commonly used for signal processing due to its advantages over other wavelet techniques, but it is limited for some applications because of its computational cost. One of the methods utilized for the implementation of the Undecimated Wavelet Transform is the one known as Cycle…
Johann Issartel, Thomas Bardainne, Philippe Gaillot, Ludovic Marin
This article sheds light on a quantitative method allowing psychologists and behavioral scientists to take into account the specific characteristics emerging from the interaction between two sets of data in general and two individuals in particular. The current article outlines the practical elements of the…
Alexander Muacevic, John R Adler, Hassan Kesserwani
The mathematization of nature is an age-old concept. The Greeks sought harmony in the celestial spheres. The Arab geometers constructed a spherical geometry of the heavens. Later, Galileo Galilei arithmetized kinematics. As the centuries advanced, polymaths like the Dutchman Christiaan Huygens applied more advanced…
Marta Walenczykowska, Adam Kawalec, Ksawery Krenc, Janusz Dudczyk + 2 more
'Piotr Samczyński' 'Ram M. Narayanan'] This article analyses the possibility of using the Analytic Wavelet Transform (AWT) and the Convolutional Neural Network (CNN) for the purpose of recognizing the intrapulse modulation of radar signals. Firstly, the possibilities of using AWT by the algorithms of automatic signal…
Basile Hurat, Zariluz Alvarado, Jérôme Gilles
The empirical wavelet transform is an adaptive multi-resolution analysis tool based on the idea of building filters on a data-driven partition of the Fourier domain. However, existing 2D extensions are constrained by the shape of the detected partitioning. In this paper, we provide theoretical results that permits us…
Ruchira Purohit, Satish Kumar, Sameer Sayyad, Ketan Kotecha
Detection of anomalies in network traffic is critical to mitigating cyber threats. This study integrates continuous wavelet transform (CWT), discrete-time Fourier transform (DTFT), short-time Fourier transform (STFT), and autoencoders to identify anomalous network behaviour. It conducts time- frequency analysis of…