Enhanced Hyperspectral Forest Soil Organic Matter Prediction Using a Black-Winged Kite Algorithm-Optimized Convolutional Neural Network and Support Vector Machine by Yun Deng, Lifan Xiao, Yuanyuan Shi

“…Three denoising methods (no denoising, Savitzky–Golay filter denoising, and discrete wavelet transform denoising) were combined with nine mathematical transformations (original spectral reflectance (R), first-order differential (1DR), second-order differential (2DR), MSC, SNV, logR, (logR)′, 1/R, ((1/R)′) to form 27 combinations. …”
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Prediction and Fitting of Nonlinear Dynamic Grip Force of the Human Upper Limb Based on Surface Electromyographic Signals by Zixiang Cai, Mengyao Qu, Mingyang Han, Zhijing Wu, Tong Wu, Mengtong Liu, Hailong Yu

“…After preprocessing the data, including outlier removal, wavelet denoising, and baseline drift correction, the NARX model was used for fitting analysis. …”
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Learning to Detect Traffic Incidents from Data Based on Tree Augmented Naive Bayesian Classifiers by Dawei Li, Xiaojian Hu, Cheng-jie Jin, Jun Zhou

“…A simulation dataset on the section of the Ayer Rajah Expressway (AYE) in Singapore is used to demonstrate the development of proposed algorithm, including wavelet denoising, normalization, entropy-based discretization, and structure learning. …”
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Steel Surface Defect Detection Based on Improved GCHS-YOLO Algorithm by Ruiqiang Guo, Peiyong Ji, Yapin Zhang, Jingqi Hu, Wenlong Liu, Xuejian Li, Min Li

“…Additionally, the Haar Wavelet Downsampling (HWD) module is incorporated to reduce the spatial resolution of feature maps while retaining important information. …”
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EXPERIMENTAL RESEARCH ON ULTRASONIC GUIDED WAVES DEFECT CLASSIFICATION BASED ON FRACTIONAL DIMENSION AND BP NEURAL NETWORK by WU Jing, RAO ZiYu, SHEN YuChi, LIAO Bin, Zhang WeiWei, ZOU HouDe, MA HongWei

“…By extracting the fractal dimension、 wavelet cocfficient and time domain signal parameters of the Duffing oscillator after inputting the defect signal to be tested as the characteristic parameters of the echo signal, inputting the BP neural network to complete the construction of the BP neural network, realizing the learning of the weak ultrasonie guided wave signal, classification. …”
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Classification of ECG signals using deep neural networks by Nadour Mohamed, Cherroun Lakhmissi, Hadroug Nadji

“…To achieve this classification, 2D Scalogram images obtained through the continuous wavelet transform (CWT) are utilized as input for the models. …”
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A Hybrid Short-Term Traffic Flow Multistep Prediction Method Based on Variational Mode Decomposition and Long Short-Term Memory Model by Qichun Bing, Fuxin Shen, Xiufeng Chen, Weijian Zhang, Yanran Hu, Dayi Qu

“…The experiment results show that (1) VMD algorithm could effectively avoid the problems of endpoint effects and modal aliasing, and the decomposition effect is better than empirical mode decomposition algorithm and wavelet decomposition algorithm; (2) among all the involved methods, the proposed hybrid model is more effective and robust in extracting the trend information, which has the best multistep prediction performance.…”
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Multistage Fault Feature Extraction of Consistent Optimization for Rolling Bearings Based on Correlated Kurtosis by Long Zhang, Binghuan Cai, Guoliang Xiong, Jianmin Zhou, Wenbin Tu, Yinquan Yu

“…To solve these problems, a multistage fault feature extraction method of consistent optimization for rolling bearings based on correlated kurtosis (CK) is proposed where maximum correlated kurtosis deconvolution (MCKD) is employed to attenuate the influence of transmission path followed by tunable Q factor wavelet transform (TQWT) to further enhance fault features by decomposing the preprocessed signals into multiple subbands under different Q values. …”
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Variations of the Reference Evapotranspiration and Aridity Index Over Northeast China: Changing Properties and Possible Causes by Liguo Cao, Zhengchao Zhou

“…Thus, in this work, we comprehensively investigated 71 meteorological stations in Northeast China from 1965 to 2017 to analyze the spatial-temporal variation and trend of ET0 and AI using the nonparametric Mann–Kendall test, the linear regression, and the Morlet wavelet methods. The results elucidated that ET0 for Northeast China as a whole exhibited a decrease at a rate of −1.97 mm/yr, AI declined at a rate of −0.01/yr during 1965–2017, and approximately 94% stations showed a decrease trend. …”
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Large-Scale Linkages of Socioeconomic Drought with Climate Variability and Its Evolution Characteristics in Northwest China by Siyuan Liu, Jianfeng Zhang, Ni Wang, Na Wei

“…The results showed that (1) the drought intensity in the up-midstream region is stronger than that in the downstream region; in view of the hysteresis in the downstream region, the occurrence of drought in the up-midstream region could be regarded as an early warning to implement preventive measures in the downstream region; (2) an increasing trend in socioeconomic drought throughout the basin exists on both monthly and annual scales, which indicates that the increasing possibility of drought should be effectively addressed; (3) cross wavelet analysis indicated that the large-scale climate indices contribute to the variations in the socioeconomic droughts throughout the basin, indicating that climate variability may provide a reference for managers to deal with socioeconomic drought in the HRB.…”
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A Novel Improved Threshold Adaptive Forgetting Variable Step Size Blind Separation Model for Weak Signal Detection by Tianyi Yu, Houming Wang, Shunming Li, Jiantao Lu, Siqi Gong, Yanfeng Wang, Guangrong Teng

“…Firstly, an improved lifting wavelet transform (ILWT) is proposed to reduce the noise of weak signals. …”
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Deep Learning-Based Post-Stroke Myoelectric Gesture Recognition: From Feature Construction to Network Design by Tianzhe Bao, Zhiyuan Lu, Ping Zhou

“…In this paper, we delve into the potential of deep learning (DL) for post-stroke hand gesture recognition by collecting the sEMG signals of eight chronic stroke subjects, focusing on three primary aspects: feature domains of sEMG (time, frequency, and wavelet), data structures (one or two-dimensional images), and neural network architectures (CNN, CNN-LSTM, and CNN-LSTM-Attention). …”
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Hybrid Simulated Annealing-Evaporation Rate-Based Water Cycle Algorithm Application for Medical Image Enhancement by Eyob Mersha Woldamanuel

“…The findings of the present study showed that the proposed strategy outperforms all of the compared methods in terms of objective function fitness and perceptual visual IQA metrics such as the Harr wavelet-based perceptual similarity index (HaarPSI), visual signal-to-noise ratio (VSNR), and information content weighted structural similarity index measure (IW-SSIM). …”
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Statistical Downscaling and Projection of Future Air Temperature Changes in Yunnan Province, China by Jiaxu Liu, Sujing Chen, Lijuan Li, Jiuyi Li

“…Periodic features were obtained by wavelet analysis. The results showed the following. (1) The pattern of change and the numerical values of the air temperature could be reasonably simulated, with the average R2 between observed and generated data being 0.963 for calibration and 0.964 for validation. (2) All scenarios projected increases of different degrees of temperature in all seasons, except for spring in the 2020s. …”
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Mathematical model and nanoindentation properties of the claws of Cyrtotrachelus buqueti Guer (Coleoptera: Curculionidae) by Longhai Li, Wei Sun, Ce Guo, Huafeng Guo, Liu Lili, Ping Yu

“…After comparison and analysis of five classical edge‐detection algorithms, the boundaries of the structural features of the claw were extracted based on a B‐spline wavelet algorithm, and the results showed that the variable curvature of the beetle claw enhances its adhesion force and improves its strength. …”
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Double Security Level Protection Based on Chaotic Maps and SVD for Medical Images by Conghuan Ye, Shenglong Tan, Jun Wang, Li Shi, Qiankun Zuo, Bing Xiong

“…First, three different random sequences are used to encrypt the LL subband in the discrete wavelet transform (DWT) domain; then, HL and LH sub-bands are embedded with watermark information; in the end, we obtain the watermarked and encrypted image with the inverse DWT (IDWT) transform. …”
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Analysis of Vibration Response Law of Multistory Building under Tunnel Blasting Loads by Runke Huo, Shuguang Li, Zhanping Song, Yoshiaki Fujii, Shan Lei, Jianchao Mao, Sisi Tian, Zizhen Miao

“…Combined with the on-site monitoring data, the wavelet packet program based on MATLAB was compiled to study the vibration response of the four-story masonry building in a typical southwestern mountainous area of China under the blasting load. …”
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Spatiotemporal Variation Characteristics of Dry/Wet Spells in Longitudinal Range-Gorge Region of the Tropic of Cancer by JIN Hanyu, CHENG Qingping, REN Yitong

“…Under the background of global warming,extreme climate events occur frequently.Understanding the change in precipitation from multiple perspectives is of great significance to the utilization of water resources.Specifically,the daily precipitation data at 24 stations along the Tropic of Cancer in the Longitudinal Range-Gorge Region (LRGR) from 1961 to 2019 are used to calculate 14 wet/dry spell indices.Methods including the revised Mann-Kendall test,Pettitt,and wavelet coherence are adopted to reveal the spatiotemporal variation characteristics of the dry/wet spell indices and their correlation with the large-scale circulation index.The results indicate that:① the wet and dry spells in LRGR of the Tropic of Cancer show a significant decreasing and increasing trend,respectively,especially in the area west of Yuanjiang River and south of the Tropic of Cancer.The change in the wet and dry spell indices of most stations is mainly concentrated in 2002.② The frequency of short-duration wet spells and the contribution rate to annual precipitation demonstrate an increasing trend,and those of the medium-long-duration wet spells demonstrate a decreasing trend;the short-duration dry spells are in decline while medium-long-duration dry spells are rising,and the entire region tends to aridification.③ The extreme dry spell index is closely related to ENSO,and it has a negatively correlated co-occurrence cycle of about six years;the extreme wet spell index is closely related to the summer monsoon of the South China Sea,and it has a positively correlated co-occurrence cycle of about eight years.To sum up,the above analysis shows that dry and wet spell indices in LRGR of the Tropic of Cancer demonstrate an overall trend of aridification,which means that the drought risks are increasing.Their spatiotemporal variation characteristics and local differences may be closely related to the joint influence of the large-scale circulation index,monsoon,and channel-blocking in LRGR.…”
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Advanced in Islanding Detection and Fault Classification for Grid-Connected Distributed Generation using Deep Learning Neural Network by Rusvaira Qatrunnada, Novizon Novizon, Mardini Hasanah, Tuti Angraini, Anton Anton

“…The method consists of discrete wavelet transform (DWT), which extracts some features from the fault signal. …”
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Rag‐bull rider optimisation with deep recurrent neural network for epileptic seizure detection using electroencephalogram by Prabin Jose Johnrose, Sundaram Muniasamy, Jaffino Georgepeter

“…The proposed rag‐ROA‐based Deep RNN showed improved results with maximal accuracy of 88.8%, maximal sensitivity of 91.9%, and maximal specificity of 89.9% than the existing methods, such as Wavelet + SVM, HWPT + RVM, MVM‐FzEN, and EWT + RF, using the TUEP dataset.…”
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