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Sakshi Dua, Sethuraman Sambath Kumar, Yasser Albagory, Rajakumar Ramalingam, Ankur Dumka, Rajesh Singh, Mamoon Rashid, Anita Gehlot, Sultan S. Alshamrani and Ahmed Saeed AlGhamdi
Deep learning-based machine learning models have shown significant results in speech recognition and numerous vision-related tasks. The performance of the present speech-to-text model relies upon the hyperparameters used in this research work. In this re...
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Yuanjie Jiang, Yuda Chen, Ruyun Tian, Longxu Wang, Shixue Lv, Jun Lin and Xuefeng Xing
Seismic communication might promise to revolutionize the theory of seismic waves. However, one of the greatest challenges to its widespread adoption is the difficulty of signal extraction because the seismic waves in the vibration environments, such as s...
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Zhiwei Li, Jun Li, Yousheng Xia, Pingfa Feng and Feng Feng
Epileptic diseases take EEG as an important basis for clinical judgment, and fractal algorithms were often used to analyze electroencephalography (EEG) signals. However, the variation trends of fractal dimension (D) were opposite in the literature, i.e.,...
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Haiyang Ju, Xinhua Wang and Yizhen Zhao
The non-contact detection of buried ferromagnetic pipeline is a long-standing problem in the field of inspection of outside pipelines, and the extraction of magnetic anomaly signal is a prerequisite for accurate detection. Pipeline defects can cause the ...
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Chenxi Liu, Tao Jiang, Zhen Zhang, Baikai Sui, Xinliang Pan, Linjing Zhang and Jingyu Zhang
Mariculture is crucial in environmental monitoring and safety assurance of marine environments. Certain mariculture areas are often partially or completely submerged in water, which causes the target signal to be extremely weak and difficult to detect. A...
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Shigeaki Okumura, Vu-Hieu Nguyen, Hirofumi Taki, Guillaume Haïat, Salah Naili and Toru Sato
Quantitative ultrasound techniques for assessment of bone quality have been attracting significant research attention. The axial transmission technique, which involves analysis of ultrasonic guided waves propagating along cortical bone, has been proposed...
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Zhi-An Deng, Di Wu, Yiran Zhou and Zhenyu Na
Feature extraction methods have been used to extract location features for indoor positioning in wireless local area networks. However, existing methods, such as linear discriminant analysis and principal component analysis, all suffer from the multimoda...
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Yuxing Li, Yilan Lou, Lili Liang and Shuai Zhang
In recent years, fuzzy dispersion entropy (FDE) has been proposed and used in the feature extraction of various types of signals. However, FDE can only analyze a signal from a single time scale during practical application and ignores some important info...
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Shang Feng, Haifeng Li, Lin Ma and Zhongliang Xu
In the application of the brain-computer interface, feature extraction is an important part of Electroencephalography (EEG) signal classification. Using sparse modeling to extract EEG signal features is a common approach. However, the features extracted ...
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Binbin Ren, Zhaoyuxuan Wang, Kainan Ma, Yiheng Zhou and Ming Liu
Heart rate measurement employing photoplethysmography (PPG) is a prevalent technique for wearable devices. However, the acquired PPG signal is often contaminated with motion artifacts, which need to be accurately removed. In cases where the PPG and accel...
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Chengjiang Zhou, Ling Xing, Yunhua Jia, Shuyi Wan and Zixuan Zhou
Aiming at the problem that fault feature extraction is susceptible to background noises and burrs, we proposed a new feature extraction method based on a new decomposition method and an effective intrinsic mode function (IMF) selection method. Firstly, p...
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Kathia Chenane, Youcef Touati, Larbi Boubchir and Boubaker Daachi
The following contribution describes a neural net-based, noninvasive methodology for electroencephalographic (EEG) signal classification. The application concerns a brain?computer interface (BCI) allowing disabled people to interact with their environmen...
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Wensheng Chen, Yinxi Niu, Zhenhua Gan, Baoping Xiong and Shan Huang
Enhancing information representation in electromyography (EMG) signals is pivotal for interpreting human movement intentions. Traditional methods often concentrate on specific aspects of EMG signals, such as the time or frequency domains, while overlooki...
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Jie Chen, Bing Han, Xufeng Ma and Jian Zhang
Underwater target recognition is an important supporting technology for the development of marine resources, which is mainly limited by the purity of feature extraction and the universality of recognition schemes. The low-frequency analysis and recording...
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Rania Alhalaseh and Suzan Alasasfeh
Many scientific studies have been concerned with building an automatic system to recognize emotions, and building such systems usually relies on brain signals. These studies have shown that brain signals can be used to classify many emotional states. Thi...
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Xuanyuan Su, Hongmei Liu and Laifa Tao
In practical engineering, the vibration-based fault diagnosis with few failure samples is gaining more and more attention from researchers, since it is generally hard to collect sufficient failure records of centrifugal pumps. In such circumstances, effe...
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Sahar Ujan, Neda Navidi and Rene Jr Landry
Radio Frequency Interference (RFI) detection and characterization play a critical role in ensuring the security of all wireless communication networks. Advances in Machine Learning (ML) have led to the deployment of many robust techniques dealing with va...
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Zheng Li, Anbo Ming, Wei Zhang, Tao Liu, Fulei Chu and Yin Li
In order to extract and enhance the weak fault feature of rolling element bearings in strong noise conditions, the Empirical Wavelet Transform (EWT) is improved and a novel fault feature extraction and enhancement method is proposed by combining the Maxi...
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Woo-Hyuk Jung and Sang-Goog Lee
This study proposes electrocardiogram (ECG) identification based on non-fiducial feature extraction using window removal method, nearest neighbor (NN), support vector machine (SVM), and linear discriminant analysis (LDA). In the pre-processing stage, Dau...
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Andres Gallego and Francisco Roman
Complex natural resonances (CNRs) extraction methods such as matrix pencil method (MPM), Cauchy, vector-fitting Cauchy method (VCM), or Prony?s method decompose a signal in terms of frequency components and damping factors based on Baum?s singularity exp...
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