A comparative study on different machine learning approaches with periodic items for the forecasting of GPS satellites clock bias by Longjiang Song, Jiahao Liu, Leilei Wang, Ziyi Wang, Yibo Yuan

“…Specifically, we utilize precision satellite clock bias data from the International GNSS Service forecast experiments and assess the predictive effects of various models including backpropagation neural network (BPNN), wavelet neural network (WNN), long short-term memory (LSTM), and gated recurrent units (GRUs). …”
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Spiking Neural Networks for Energy-Efficient Acoustic Emission-Based Monitoring by Federica Zonzini, Wenliang Xiang, Luca de Marchi

“…In this work, a novel processing flow which shifts the identification process from the time to the time-frequency domain via wavelet transform (WT) is proposed, allowing to better capture transient behaviors typical of the originated AE signals. …”
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Resnet-1DCNN-REA bearing fault diagnosis method based on multi-source and multi-modal information fusion by Xu Chen, Wenbing Chang, Yongxiang Li, Zhao He, Xiang Ma, Shenghan Zhou

“…The one-dimensional vibration signals were converted into two-dimensional time-frequency images by continuous wavelet transform (CWT), and then they were fed into the Resnet network for fault diagnosis. …”
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Single-channel attention classification algorithm based on robust Kalman filtering and norm-constrained ELM by Jing He, Zijun Huang, Yunde Li, Jiangfeng Shi, Yehang Chen, Chengliang Jiang, Jin Feng

“…This study proposes a robust Kalman filtering method combined with a norm-constrained extreme learning machine (ELM) to address these challenges.MethodsThe proposed method integrates Discrete Wavelet Transformation (DWT) and Independent Component Analysis (ICA) for noise removal, followed by a robust Kalman filter enhanced with convex optimization to preserve critical EEG components. …”
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An Improved ConvNeXt With Multimodal Transformer for Physiological Signal Classification by Jiajian Zhu, Yue Feng, Qichao Liu, Hong Xu, Yuan Miao, Zhuosheng Lin, Jia Li, Huilin Liu, Ying Xu, Fufeng Li

“…The proposed ICMT-Net utilizes continuous wavelet transform to partition 5-second ECG and WPS segments into spectrograms. …”
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Predicting Screening Efficiency of Probability Screens Using KPCA-GRNN with WP-EE Feature Reconstruction by Qingtang Chen, Yijian Huang

“…Subsequently, empirical mode decomposition energy entropy (EMD-EE), variational mode decomposition energy entropy (VMD-EE), and wavelet packet energy entropy (WP-EE) features are extracted from the time series vibration signals, and three single input energy entropy-generalized regressive neural network (GRNN) prediction accuracy models are established and compared. …”
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Features and Source Current of Long‐Period Induced Geoelectric Field During Magnetic Storms: A Case Study by S. Y. Wu, S. Yao, X. D. Feng, W. B. Wei, Y. T. Yin, L. T. Zhang, H. Dong, G. W. Wang, J. L. Liu, Y. Q. Yu, D. Wei

“…Besides, Space Weather Modeling Framework is adopted to calculate the global geomagnetic field disturbances and the contribution from different current systems. The wavelet power spectra analysis reveals that the long‐period geoelectric field disturbance appears only during magnetic storms. …”
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DMPNet: dual-path and multi-scale pansharpening network by Gurpreet Kaur, Manisha Malhotra, Dilbag Singh, Dilbag Singh, Sunita Singhal

“…Finally, to achieve optimal spatial and spectral reconstruction, the IRM decomposes the fused features into low- and high-frequency components using discrete wavelet transform (DWT).ResultsThe proposed DMPNet outperforms competitive models in terms of ERGAS, SCC (WR), SCC (NR), PSNR, Q, QNR, and JQM by approximately 1.24%, 1.18%, 1.37%, 1.42%, 1.26%, 1.31%, and 1.23%, respectively.DiscussionExtensive experimental results and evaluations reveal that the DMPNet is more efficient and robust than competing pansharpening models.…”
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Dynamic Response of Graphitic Targets with Tantalum Cores Impacted by Pulsed 440-GeV Proton Beams by Pascal Simon, Philipp Drechsel, Peter Katrik, Kay-Obbe Voss, Philipp Bolz, Fiona J. Harden, Michael Guinchard, Yacine Kadi, Christina Trautmann, Marilena Tomut

“…Using advanced post-processing techniques, such as fast Fourier transformation and continuous wavelet transformation, different pressure wave components are identified and their contribution to the overall dynamic response of a two-body target and their failure mode are discussed. …”
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Mechanical Properties of Bump-Prone Coal with Different Porosities and Its Acoustic Emission-Charge Induction Characteristics under Uniaxial Compression by Xin Ding, Xiaochun Xiao, Xiangfeng Lv, Di Wu, Jun Xu

“…Both of them originated from cracks and belong to homologous signals, crack development bound to be accompanied by stress wavelet, not necessarily free charge; meanwhile, charge pulse being emerged means there must be cracks interaction and the acoustic emission signals are generated prior to charge induction.…”
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A 1.5D Spectral Kurtosis-Guided TQWT Method and Its Application in Bearing Fault Detection by Xiong Zhang, Ming Zhang, Shuting Wan, Rujiang Hao, Yuling He, Xiaolong Wang

“…In this paper, the signal is processed by the tunable Q-factor wavelet transform (TQWT), the midfrequency band of the signal is tightly divided by selecting different Q-values, and the 1.5D spectral kurtosis defined in frequency domain is used to select the optimal subband. …”
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Revealing Novel Connections Between Space Weather and the Power Grid: Network Analysis of Ground‐Based Magnetometer and Geomagnetically Induced Currents (GIC) Measurements by Joseph Hughes, Ryan Mcgranaghan, Adam C. Kellerman, Jacob Bortnik, Robert F. Arrit, Karthik Venkataramani, Charles H. Perry, Jackson McCormick, Chigomezyo M. Ngwira, Morris Cohen

“…The magnetometer data are analyzed using wavelet analysis. This new analysis method shows deviations to be more likely for equatorial stations close to water, which may be caused by the coast effect. …”
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Altered Brain Activity and Effective Connectivity within the Nonsensory Cortex during Stimulation of a Latent Myofascial Trigger Point by Xinglou Li, Meiling Luo, Yan Gong, Ning Xu, Congcong Huo, Hui Xie, Shouwei Yue, Zengyong Li, Yonghui Wang

“…The data investigated the latent MTrP-induced changes in brain activity and effective connectivity (EC) within the nonsensory cortex. The parameter wavelet amplitude (WA) was used to describe cortical activation, EC to show brain network connectivity, and main coupling direction (mCD) to exhibit the dominant connectivity direction in different frequency bands. …”
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Characteristics of Extreme Runoff in Beijiang River Basin during Dry Season from 1954 to 2020 by ZENG Zhiping, ZHENG Yanhui, ZHOU Yueying, GU Xihui, HE Yanhu

“…It also employed indicators of hydrological alteration (IHA), heuristic segmentation algorithms, Mann-Kendall trend test, and wavelet analysis to examine the distribution characteristics, trends, variability, and cycle of extreme runoff in the Beijiang River Basin during dry season across various time scales. …”
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Estimating the safe mud weight window for drilling operations through pre-stack seismic inversion, a case study in one of the Southwestern Iran oil fields by Mohammad Sadegh Mahmoudian, Yousef Shiri, Ahmad Vaezian

“…The pre-stack seismic inversion is conducted by constructing a velocity model and utilizing angle gather aggregation, statistical wavelet extraction, and initial model creation. Seismic inversion analysis revealed that the studied sandstone reservoir layer, known as the Ghar formation, possesses lower P-wave or S-wave acoustic impedance (P-/S-AI) and density compared to adjacent layers, likely due to the presence of porosity and potentially intra-formational fluids. …”
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The Theory and Applications of Hölder Widths by Man Lu, Peixin Ye

“…The fact that Hölder widths are smaller than the known widths implies that the nonlinear approximation represented by deep neural networks can provide a better approximation order than other existing approximation methods, such as adaptive finite elements and <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>n</mi></mrow></semantics></math></inline-formula>-term wavelet approximation. In particular, we show that Hölder widths for Sobolev and Besov classes, induced by deep neural networks, are <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi mathvariant="script">O</mi><mo>(</mo><msup><mi>n</mi><mrow><mo>−</mo><mn>2</mn><mi>s</mi><mo>/</mo><mi>d</mi></mrow></msup><mo>)</mo></mrow></semantics></math></inline-formula> and are much smaller than other known widths and entropy numbers, which are <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi mathvariant="script">O</mi><mo>(</mo><msup><mi>n</mi><mrow><mo>−</mo><mi>s</mi><mo>/</mo><mi>d</mi></mrow></msup><mo>)</mo></mrow></semantics></math></inline-formula>.…”
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Trends and Spatiotemporal Patterns of the Meteorological Drought in the Ili River Valley from 1961 to 2023: An SPEI-Based Study by Su Hang, Alim Abbas, Bilal Imin, Nijat Kasim, Zinhar Zunun

“…The SPEI drought index, along with Sen’s trend analysis, the Mann–Kendall test, the cumulative departure method, and wavelet analysis, were employed to assess drought patterns. …”
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Enhanced Fetal Arrhythmia Classification by Non-Invasive ECG Using Cross Domain Feature and Spatial Differences Windows Information by Gede Angga Pradipta, Putu Desiana Wulaning Ayu, Made Liandana, Dandy Pramana Hostiadi

“…First, the original waveform signals from six sensors were transformed into a multi-level decomposition using the HAAR wavelet. Subsequently, a sample expansion was applied using a various-sized window sliding approach to each ARR and normal signal. …”
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Recognition and Classification of 3D Objects of Different Details by Islam A. Alexandrov, Maxim S. Mikhailov, Alexander N. Muranov, Vladimir Zh. Kuklin

“…We propose the use of three spectral descriptors – Heat Kernel Signature (HKS), Weave Kernel Signature (WKS) and the wavelet descriptor (SGWT). Then, we develop a high-accuracy recognition method based on spectral and topological invariants processed using a convolutional neural network. …”
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Application of Video Processing Technology Based on Diffusion Equation Model in Basketball Analysis by Yafeng Feng, Xianguo Liu

“…This paper studies the anisotropic diffusion method for coherent speckle noise removal and proposes a video image denoising method that combines anisotropic diffusion and stationary wavelet transform. This paper proposes an anisotropic diffusion method based on visual characteristics, which adds a factor of video image detail while smoothing, and improves the visual effect of diffusion. …”
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