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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Study on the Noise Reduction of Vehicle Exhaust NOX Spectra Based on Adaptive EEMD Algorithm by Kai Zhang, Yujun Zhang, Kun You, Ying He, Qiankun Gao, Guohua Liu, Chungui He, Yibing Lu, Boqiang Fan, Qixing Tang, Wenqing Liu

“…But in the conventional methods for noise reduction and baseline correction, such as wavelet transform, derivative, interpolation, polynomial fitting, and so forth, the basic functions of these algorithms, the number of decomposition layers, and the way to reconstruct the signal have to be adjusted according to the characteristics of different components in the transmission spectra. …”
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A multiresolution approach with method-informed statistical analysis for quantifying lymphatic pumping dynamics by Mohammad S. Razavi, Katarina J. Ruscic, Elizabeth G. Korn, Marla Marquez, Timothy T. Houle, Dhruv Singhal, Lance L. Munn, Timothy P. Padera

“…Here, we address this unmet need by integrating near-infrared fluorescence lymphangiography imaging with an innovative analytical workflow that combines data acquisition, signal processing, and statistical analysis to integrate traditional peak-and-valley analysis with advanced wavelet time-frequency analyses. Variance component analysis was used to evaluate the drivers of variance attributable to each experimental variable for each lymphangiography measurement type. …”
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A Pervasive Approach to EEG-Based Depression Detection by Hanshu Cai, Jiashuo Han, Yunfei Chen, Xiaocong Sha, Ziyang Wang, Bin Hu, Jing Yang, Lei Feng, Zhijie Ding, Yiqiang Chen, Jürg Gutknecht

“…After denoising using the Finite Impulse Response filter combining the Kalman derivation formula, Discrete Wavelet Transformation, and an Adaptive Predictor Filter, a total of 270 linear and nonlinear features were extracted. …”
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EEG alpha/beta features as a biomarker for quantifying pain in patients with lumbar disk herniation by Rumei Li, Wanqi Shao, Shumei Zhao, Lingli Wang, Chao Yu, Lanying Liu, Kuiying Yin

“…Following the spectral analysis of the EEG signals with continuous wavelet transform, power ratios were extracted for four frequency bands (θ, α, β and γ). …”
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An Experimental Investigation on the Relationship between MS Frequency Response and Coal and Gas Outburst by Quanjie Zhu, Qingsong Li, Yu Feng, Xianwei Heng, Shaoquan Li, Tao Yang

“…Based on these laws, CGOB experiments were carried out using a large CGOB physical simulation system with a MS monitoring system. Notching filter and wavelet packet transform technique were used in the denoising and feature extraction of six typical MS events (signals). …”
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Multiwavelength Variability Analysis of the Blazar PKS 0727-11: An ~ 168 day Quasiperiodic Oscillation in the γ-Ray by Yuncai Shen, Tingfeng Yi, Vinit Dhiman, Lisheng Mao, Liang Dong

“…It is the first time that periodic variations have been detected in this source, and further supported by other methods: weighted wavelet z -transform, phase dispersion minimization, REDFIT, autoregressive integrated moving average model, and structure function analysis. …”
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The use of low-density EEG for the classification of PPA and MCI by Panteleimon Chriskos, Panteleimon Chriskos, Kyriaki Neophytou, Christos A. Frantzidis, Christos A. Frantzidis, Jessica Gallegos, Alexandros Afthinos, Chiadi U. Onyike, Argye Hillis, Panagiotis D. Bamidis, Kyrana Tsapkini, Kyrana Tsapkini

“…Utilizing the Relative Wavelet Entropy method, we derived (i) functional connectivity, (ii) graph theory metrics and extracted (iii) various energy rhythms. …”
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Classification of Epileptic Seizures by Simple Machine Learning Techniques: Application to Animals’ Electroencephalography Signals by Illia Pidvalnyi, Anna Kostenko, Oleksandr Sudakov, Dmytro Isaev, Oleksandr Maximyuk, Oleg Krishtal, Olena Iegorova, Ievgen Kabin, Zoya Dyka, Steffen Ortmann, Peter Langendorfer

“…Hjorth’s parameters and Daubechies discrete wavelet transform coefficients were found to be the most informative features of EEG data. …”
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A Resource-Efficient Multi-Entropy Fusion Method and Its Application for EEG-Based Emotion Recognition by Jiawen Li, Guanyuan Feng, Chen Ling, Ximing Ren, Xin Liu, Shuang Zhang, Leijun Wang, Yanmei Chen, Xianxian Zeng, Rongjun Chen

“…Based on electroencephalography (EEG), the biomedical signals naturally generated by the brain, this work proposes a resource-efficient multi-entropy fusion method for classifying emotional states. First, Discrete Wavelet Transform (DWT) is applied to extract five brain rhythms, i.e., delta, theta, alpha, beta, and gamma, from EEG signals, followed by the acquisition of multi-entropy features, including Spectral Entropy (PSDE), Singular Spectrum Entropy (SSE), Sample Entropy (SE), Fuzzy Entropy (FE), Approximation Entropy (AE), and Permutation Entropy (PE). …”
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A Hybrid Dynamic Principal Component Analysis Feature Extraction Method to Identify Piston Pin Wear for Binary Classifier Modeling by Hao Yang, Yubin Zhai, Mengkun Zheng, Tan Wang, Dongliang Guo, Jianhui Liang, Xincheng Li, Xianliang Liu, Mingtao Jia, Rui Zhang

“…For each round, two binary classifier models are trained by features extracted by the proposed method and the empirical mode decomposition (EMD)–auto regressive (AR) spectrum method, fast Fourier transform (FFT) and continuous wavelet transform (CWT), respectively; the classification precision, recall ratio, accuracy and F1 ratio are obtained on the testing set by contrasting the overall performances of the five-round cross-validation, and the proposed method is proved to be more effective in noise reduction and significant feature extraction, which is able to improve the accuracy and efficiency of binary classification for piston pin wear identification.…”
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Delta-radiomics analysis based on magnetic resonance imaging to identify radiation proctitis in patients with cervical cancer after radiotherapy by Jing Xue, Menghan Wu, Jing Zhang, Jiayang Yang, Guannan Lv, Baojun Qu, Yanping Zhang, Xia Yan, Xia Yan, Jianbo Song, Jianbo Song

“…Key features associated with RP included D1cc, T1_wavelet-LLL_glcm_MCC, D2cc, and T2_original_firstorder_90 Percentile.ConclusionsThe MRI-based delta radiomics model shows significant promise in predicting RP severity in cervical cancer patients following radiotherapy, with enhanced predictive performance when combined with clinical features.…”
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Historical snow measurements in the central and southern Apennine Mountains: climatology, variability, and trend by V. Capozzi, F. Serrapica, A. Rocco, C. Annella, C. Annella, G. Budillon

“…In addition, using a cross-wavelet analysis, we found a close in-phase linkage on a decadal timescale between the investigated snow indicators and the Eastern Mediterranean teleconnection Pattern. …”
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Hippocampal Functional Radiomic Features for Identification of the Cognitively Impaired Patients from Low-Back-Related Pain: A Prospective Machine Learning Study by Yang Z, Liang X, Ji Y, Zeng W, Wang Y, Zhang Y, Zhou F

“…Additionally, radiomic wavelet features were correlated with Montreal Cognitive Assessment (MoCA) and Hamilton Anxiety Scale, present pain intensity scores in cognitively impaired LBLP patients (P < 0.05, with Bonferroni correction).Conclusion: Hippocampal functional radiomic features are valuable for diagnosing cognitively impaired patients from LBLP.Keywords: cognitive impairment, resting-state functional MRI, low-back-related leg pain, radiomic, logistic regression algorithm…”
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Evolution mechanisms of the scratch-induced elastoplastic stress fields and crack damage in γ-TiAl alloys by Zhaoqing Zhang, Kaining Shi, Yaoyao Shi, Huhu Li, Danni Lu, Yujie Kuang, Jiacheng Liu

“…In this study, scratch experiments were conducted to simulate the material removal process during grinding. The discrete wavelet transform (DWT) was applied to analyze load signals during the scratching process, enabling the precise identification of the plastic-to-brittle transition domain and the critical cutting depth for γ-TiAl alloys, and clarifying the damage mechanisms under different cutting depths. …”
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Developing a multivariate drought index to assess drought characteristics based on the SWAT-Copula method in the Poyang Lake basin, China by Liping Guo, Fusheng Chen, Bin Wang, De Li Liu, Xiulong Chen, Hongsheng Huang, Hua Bai, Kaitao Liao, Zhiming Xia, Keyu Xiang, Linchao Li, Taihui Zheng, Qiang Yu

“…We found that (1) The SWAT can simulate monthly streamflow well with NS being 0.76–0.92 for validation data over the sub-basins in the PLB. (2) The MSDI index indicated that there were more drought events during 1960–1979 and 2000–2019, highlighting a cyclical pattern of drought events in the PLB. (3) The Xiushui River Basin encountered the most extreme drought conditions since 2000, indicating the basin faced a high risk of dry conditions. Additionally, our wavelet period analysis showed an increase in drought frequency after the year 2000, with less distinct periodicity. …”
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Temporal and Spatial Patterns of Wind Erosion Climate Indices and Their Responses to Atmospheric and Oceanic Circulation Patterns in the Chinese Mollisol Region over the Past 61 Ye... by HU Wentao, ZHENG Fenli, GAO Xiaoyu, ZHENG Runhe, FU Jinxia, LI Zhi, ZHANG Jiaqiong

“…The research methods included the moving average, Mann-Kendall test and multiple wavelet coherence. [Results] The occurrence frequency of ≥ 5 m/s threshold wind speed of transporting sand varied from 5 to 30 times per season, daily maximum wind velocity varied from 6.1 to 8.7 m/s, daily extreme wind velocity varied from 9.8 to 12.2 m/s, and wind erosion climatic erosivity varied from 19.5 to 101.1 in the Chinese Mollisol region form 1960 to 2020. …”
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Function spaces on the Koch curve by Maryia Kabanava

“…We compare these spaces and give their characterization in terms of Daubechies wavelets.…”
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