Tool wear prediction based on XGBoost feature selection combined with PSO-BP network by Zhangwen Lin, Yankun Fan, Jinling Tan, Zhen Li, Peng Yang, Hua Wang, Weiwei Duan

“…Initially, vibration and cutting force signals from CNC machining are preprocessed using time-domain segmentation, Hampel filtering, and wavelet denoising. Subsequently, time-domain, frequency-domain, and time–frequency domain features are extracted from the preprocessed data using FFT and wavelet packet decomposition, followed by feature screening for tool wear mapping via Pearson correlation and XGBoost feature importance analysis as model input. …”
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An overlapping sliding window and combined features based emotion recognition system for EEG signals by Shruti Garg, Rahul Kumar Patro, Soumyajit Behera, Neha Prerna Tigga, Ranjita Pandey

“…Two features are extracted using Fourier and Wavelet transforms: normalised band power (NBP) and normalised wavelet energy (NWE), respectively. …”
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Artificial Neural Network-Based System for PET Volume Segmentation by Mhd Saeed Sharif, Maysam Abbod, Abbes Amira, Habib Zaidi

“…This paper presents a novel application of ANNs in the wavelet domain for PET volume segmentation. ANN performance evaluation using different training algorithms in both spatial and wavelet domains with a different number of neurons in the hidden layer is also presented. …”
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CMB Map Restoration by J. Bobin, J.-L. Starck, F. Sureau, J. Fadili

“…In this paper, we introduce a novel noise reduction framework coined LIW-Filtering for Linear Iterative Wavelet Filtering which is able to account for the noise spatial variability thanks to a wavelet-based modeling while keeping the highly desired linearity of the Wiener filter. …”
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Evaluation of an Information Flow Gain Algorithm for Microsensor Information Flow in Limber Motor Rehabilitation by Naiqiao Ning, Yong Tang

“…The EMG signals were processed by the trap and filter combination denoising method and wavelet denoising method, respectively, the signal-to-noise ratio was used to evaluate the noise reduction effect, and finally, the wavelet denoising method with a better noise reduction effect was selected to process all the EMG signals. …”
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Application of Deep Learning to Identify Flutter Flight Testing Signals Parameters and Analysis of Real F-18 Flutter Flight Test Data by Sami Abou-Kebeh, Roberto Gil-Pita, Manuel Rosa-Zurera

“…Although the results with the networks trained show less accuracy than the PRESTO algorithm, they are more accurate than the Laplace Wavelet estimation, and the results are promising enough to justify extended investigation on this area. …”
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Aircraft Actuator Performance Analysis Based on Dynamic Neural Network by Wathiq Rafa Abed

“…The proposed method starts with the current and vibration signal as failure indicators and a dual-tree complex wavelet transformation (DTCWT) to generate the necessary features. …”
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Backpropagation Neural Network Implementation for Medical Image Compression by Kamil Dimililer

“…An ideal image compression system must yield high-quality compressed image with high compression ratio. In this paper, Haar wavelet transform and discrete cosine transform are considered and a neural network is trained to relate the X-ray image contents to their ideal compression method and their optimum compression ratio.…”
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Reliability of radiomics features as imaging biomarkers for evaluating brain aging: A study based on myelin protein and diffusion tensor imaging by Yuting Yan, Mengmeng Hu, Xiaodong He, Yuyun Xu, Xiaojun Sun, Jiaxuan Peng, Fanfan Zhao, Yuan Shao

“…The four most relevant features with the top four correlation coefficients were selected to compare their diagnostic performances with the DTI parameters, including fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AxD), and radial diffusivity (RD). Wavelet-HLL_glszm_ZoneEntropy, wavelet-HLL_gldm_DependenceEntropy, wavelet-LHL_glszm_ZoneEntropy, and log-sigma-2-0-mm-3D_gldm_DependenceEntropy were the four most relevant features, which had moderately significant correlations with PLP. …”
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All-or-none activity as a correlate of object awareness in monkey visual cortex by Anne‑Claire Collet, Roger Koenig‑Robert, Denis Fize, Rufin VanRullen

“…Here we used an innovative technique called Semantic Wavelet-Induced Frequency-Tagging (SWIFT), where cyclic wavelet-scrambling allowed us to isolate neural correlates of the semantic extraction from low-level features processing of the image. …”
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Monitoring of ball bearings via vibration analysis and envelope technique for predictive maintenance purposes by Adiel Pessoa, Paulo Cezar Büchner

“…Current techniques, such as envelope and wavelet analysis, are effective but have limitations. …”
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EMD-GM-ARMA Model for Mining Safety Production Situation Prediction by Menglong Wu, Yicheng Ye, Nanyan Hu, Qihu Wang, Huimin Jiang, Wen Li

“…Finally, aiming to predict the mining safety production situation, the EMD-GM-ARMA model was constructed via superimposing the prediction results of each subsequence, thereby compared to the ARIMA model, wavelet neural network model, and PSO-SVM model. The results demonstrated that the EMD-GM-ARMA model and the PSO-SVM model hold the highest prediction accuracy in the short-term prediction, and the wavelet neural network has the lowest prediction accuracy. …”
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In Situ Investigation of the 3D Mechanical Microstructure at Nanoscale: Nano-CT Imaging Method of Local Small Region in Large Scale Sample by Bo Dong, Feng Xu, Xiao-fang Hu, Hong-yan Qu, Dan Kang, Ti-qiao Xiao

“…To investigate the local micro-/nanoscale region in a large scale sample, an image reconstruction method for nanometer computed tomography (nano-CT) was proposed in this paper. In the algorithm, wavelets were used to localize the filtered-backprojection (FBP) algorithm because of its space-frequency localization property. …”
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Determining Planetary Boundary Layer Height by Micro-pulse Lidar with Validation by UAV Measurements by Yueh-Chen Wang, Sheng-Hsiang Wang, Jasper R. Lewis, Shuenn-Chin Chang, Stephen M. Griffith

“…Furthermore, the Haar wavelet and the Hybrid image processing can detect the PBL development comparably well, but both methods are dependent on their initial conditions and optimized algorithm settings. …”
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Hybridization of stochastic hydrological models and machine learning methods for improving rainfall-runoff modeling by Sianou Ezéckiel Houénafa, Olatunji Johnson, Erick K. Ronoh, Stephen E. Moore

“…HyMoLAP) model with machine learning techniques, including Wavelet-based eXtreme Gradient Boosting (WXGBoost) and Wavelet-based Gated Recurrent Unit (WGRU). …”
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Data-Driven Learning-Based Fault Tolerant Stability Analysis by Lei Ge, Shun Chen

“…A regularized regression wavelet (RRW) approach is proposed to optimize the learning result for the system fault. …”
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Ultrasonic Guided Waves-Based Monitoring of Rail Head: Laboratory and Field Tests by Piervincenzo Rizzo, Marcello Cammarata, Ivan Bartoli, Francesco Lanza di Scalea, Salvatore Salamone, Stefano Coccia, Robert Phillips

“…The prototype includes an algorithm based on wavelet transform and outlier analysis. The discrete wavelet transform is utilized to denoise ultrasonic signals and to generate a set of relevant damage sensitive data. …”
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Letter and Person Recognition in Freeform Air-Writing Using Machine Learning Algorithms by Huseyin Kunt, Zeki Yetgin, Furkan Gozukara, Turgay Celik

“…To the best of the authors’ knowledge, there is no study for person recognition from freeform air-writing letters through IMU sensors, and also there is no study using the Fourier and Wavelet features in this context. Furthermore, the study is also original due to its publicly available air-writing dataset on the Turkish alphabet and also applying various machine learning algorithms. …”
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Temporal shifts in dengue epidemic in Guangdong Province before and during the COVID-19 pandemic: a Bayesian model study from 2012 to 2022. by Jiaqing Xu, Xiaohua Tan, Yi Quan, Dexin Gong, Hui Deng, Jianguo Zhao, Xing Huang, Yingtao Zhang, Zhoupeng Ren, Zuhua Rong, Weilin Zeng, Xing Li, Wenyuan Zheng, Shu Xiao, Jianpeng Xiao, Meng Zhang

“…<h4>Methods</h4>Based on the data of dengue reported cases, meteorological factors, and mosquito vector density in Guangdong Province from 2012 to 2022, wavelet analysis was applied to investigate the relationship between the dengue incidence in Southeast Asian (SEA) countries and the local dengue incidence in Guangdong Province. …”
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Components and predictability of pollutants emission intensity by Z. Farajzadeh, M.A. Nematollahi

“…For this purpose, two well-known artificial neural networks, multilayer perceptron, and wavelet-based neural network were applied to forecast the emission intensity of the selected pollutants and their components.FINDINGS: The emission intensity of nitrogen oxides and sulphur dioxide illustrated a decreasing trend. …”
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