20 papers · ranked by Valyu relevance
Shanfeng Gao, Lei Xu, Yongkang Li, Jiwen Ji + 1 more
To meet the high thickness accuracy requirements in cold-rolling processes, a roll eccentricity signal extraction method based on modified particle swarm optimization and wavelet threshold denoising (MPSO-WTD) with intrinsic time-scale decomposition (ITD) is proposed. The strong denoising ability of the wavelet is…
Yanwen Wang, Peng Chen, Yongmei Zhao, Yanying Sun + 1 more
'Manuel José Cabral dos Santos Reis'] When the pulse current method is used for partial discharge (PD) monitoring of mining cables, the detected PD signals are seriously disturbed by the field noise, which are easily submerged in the noise and cannot be extracted. In order to realize the effective separation of the PD…
Jing Zhao, Longhui Chen, Hongyin Yang, Zhuo Hu + 3 more
Highlights A novel improved wavelet threshold function is proposed for denoising deformation monitoring data, addressing the discontinuity of hard thresholding and the constant bias of soft thresholding. What are the main findings?1. Effective elimination of noise from metro deep excavation monitoring data is achieved…
Shuxun Li, Qian Zhao, Jinwei Liu, Xuedong Zhang + 2 more
'Jiawei Xiang'] The performance of steam traps plays an important role in the normal operation of steam systems. It also contributes to the improvement of thermal efficiency of steam-using equipment and the rational use of energy. As an important component of the steam system, it is crucial to monitor the state of the…
Ananias Pereira Neto, Fabrício J. B. Barros
Introduction Wavelet thresholding techniques are crucial in mitigating noise in data communication and storage systems. In image processing, particularly in medical imaging like MRI, noise reduction is vital for improving visual quality and accurate analysis. While existing methods offer noise reduction, they often…
Kim C. Raath, Katherine B. Ensor, Alena Crivello, David W. Scott + 1 more
'Marco Riani'] Over the past few years, we have seen an increased need to analyze the dynamically changing behaviors of economic and financial time series. These needs have led to significant demand for methods that denoise non-stationary time series across time and for specific investment horizons (scales) and…
Cameron Khanpour
Image Enhancement Authors: ['Cameron Khanpour'] Abstract—This paper presents a comprehensive analysis of image denoising techniques, primarily focusing on Non-local Means (NLM) and Daubechies Soft Wavelet Thresholding, and their efficacy across various datasets. These methods are applied to the CURE-OR, CURE-TSD…
Hongxin Ji, Xinghua Liu, Jianwen Zhang, Liqing Liu + 1 more
Because large oil-immersed transformers are enclosed by a metal shell, the on-site localization means it is difficult to achieve the accurate location of the patrol micro-robot inside a given transformer. To address this issue, a spatial ultrasonic localization method based on wavelet decomposition and PHAT-β-γ…
X.J. Li, Peng Ge, Yu-Ting Shen, Feng Gao + 1 more
Photoacoustic imaging (PAI) has been applied to many biomedical applications over the past decades. However, the received PA signal usually suffers from poor signal-to-noise ratio (SNR). Conventional solution of employing higher-power laser, or doing long-time signal averaging, may raise the system cost, time…
Priyalakshmi Sheela, Indrakshi Dey
Wavelet denoising suppresses nonstationary, impulsive, and interference-like disturbances in communication signals, but its effectiveness depends on jointly selecting the transform family, mother wavelet, decomposition level, thresholding rule, and shrinkage function. This review synthesises studies published during…
Clément Flint, Philippe Helluy
This paper presents a new solution to address the challenge of increasing memory usage in high-performance computing simulations of Lattice-Bolzmann or Finite-Volume schemes. Our approach utilises a lossy compression scheme based on the Discrete Wavelet Transform (DWT) to achieve high compression ratios while…
Bowen Ni, Fei Song, Liguo Zhao, Zhipeng Fu + 1 more
To address the noise issue in fiber optic monitoring signals in frozen soil areas, this study employs wavelet denoising techniques to process the fiber optic signals. Since existing parameter choices for wavelets are typically based on conventional environments, selecting suitable parameters for frozen soil regions…
Neil D. Dizon, Jeffrey A. Hogan
Recently, novel quaternion-valued wavelets on the plane were constructed using an optimisation approach. These wavelets are compactly supported, smooth, orthonormal, nonseparable and truly quaternionic. However, they have not been tested in application. In this paper, we introduce a methodology for decomposing and…
Matteo Dora, Stéphane Jaffard, David Holcman
Wavelet quantile normalization (WQN) is a nonparametric algorithm designed to efficiently remove transient artifacts from single-channel EEG in real-time clinical monitoring. Today, EEG monitoring machines suspend their output when artifacts in the signal are detected. Removing unpredictable EEG artifacts would thus…
Zheng Zhang, Timothy G. Constandinou
This paper assesses and challenges whether commonly used methods for defining amplitude thresholds for spike detection are optimal. This is achieved through empirical testing of single amplitude thresholds across multiple recordings of varying SNR levels. Our results suggest that the most widely used…
Daria Kleeva, Gurgen Soghoyan, Ilia Komoltsev, Mikhail Sinkin + 1 more
Epilepsy is a widely spread neurological disease, whose treatment often requires resection of the pathological cortical tissue. Interictal spike analysis observed in the non-invasively collected EEG or MEG data offers an attractive way to localize epileptogenic cortical structures for surgery planning purposes.…
Ambra Ferrari, Luca Filippin, Marco Buiatti, Eugenio Parise
Electroencephalography (EEG) is an established method for investigating neurocognitive functions during human development. In cognitive neuroscience, time-frequency analysis of the EEG is a widely used analytical approach. This paper introduces WTools, a new MATLAB-based toolbox capable of performing time-frequency…
Luke A. Shaheen, Brad N. Buran, Kirupa Suthakar, Seth D. Koehler + 1 more
The auditory brainstem response (ABR) is an essential diagnostic indicator of overall cochlear health, used extensively in both basic research and clinical studies. A key quantification of the ABR is threshold, the lowest sound level that elicits a response. Because the morphology of ABR waveforms shift with stimulus…
Mauro Silberberg, Hernán E. Grecco
Quantitative analysis of high-throughput microscopy images requires robust automated algorithms. Background estimation is usually the first step and has an impact on all subsequent analysis, in particular for foreground detection and calculation of ratiometric quantities. Most methods recover only a single background…
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…