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Tianwei Lan, Zhaofa Zeng, Liguo Han and Jingwen Zeng
The neural network denoising technique has achieved impressive results by being able to automatically learn the effective signal from the data without any assumptions. However, it has been found experimentally that the performance of the method using neu...
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Vinoth Babu Kumaravelu, Agbotiname Lucky Imoize, Francisco R. Castillo Soria, Periyakarupan Gurusamy Sivabalan Velmurugan, Sundarrajan Jayaraman Thiruvengadam, Dinh-Thuan Do and Arthi Murugadass
Reconfigurable intelligent surface (RIS)-assisted non-orthogonal multiple access (NOMA) has the ability to overcome the challenges of the wireless environment like random fluctuations, shadowing, and mobility in an energy efficient way when compared to m...
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Chenbo Shi, Yanhong Cheng, Chun Zhang, Jin Yuan, Yuxin Wang, Xin Jiang and Changsheng Zhu
The detection of poultry egg microcracks based on electrical characteristic models is a new and effective method. However, due to the disorder, mutation, nonlinear, time discontinuity, and other factors of the current data, detection algorithms such as s...
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Dascha Dobrovolskij and Katja Schladitz
Ultrasonic testing of polycrystalline media relies heavily on simulation of the expected signals in order to detect and correctly interpret deviations due to defects. Many effects disturb ultrasonic waves propagating in polycrystalline media. One of them...
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Yingmei Qi, Heming Huang and Huiyun Zhang
Speech emotion recognition is a crucial work direction in speech recognition. To increase the performance of speech emotion detection, researchers have worked relentlessly to improve data augmentation, feature extraction, and pattern formation. To addres...
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Okiemute Roberts Omasheye, Samuel Azi, Joseph Isabona, Agbotiname Lucky Imoize, Chun-Ta Li and Cheng-Chi Lee
The accurate and reliable predictive estimation of signal attenuation loss is of prime importance in radio resource management. During wireless network design and planning, a reliable path loss model is required for optimal predictive estimation of the r...
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Weicheng Sun, Zhenqun Guan, Yan Zeng, Jiacheng Pan and Zhonghai Gao
This paper designed a bolt-loosening Support Vector Machines? conduct detection method with feature vectors comprising eigenvalue decomposition based on Variational Modal Decomposition (VMD) and Singular Value Decomposition (SVD), combined with permutati...
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Seyeong Choi, Duckdong Hwang and Sung Sik Nam
With the increase in the complexity of communication systems, order statistics have become increasingly significant in performance evaluation, especially for advanced diversity techniques over fading channels. However, existing analytical approaches are ...
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Andreea Bianca Popescu, Ioana Antonia Taca, Anamaria Vizitiu, Cosmin Ioan Nita, Constantin Suciu, Lucian Mihai Itu and Alexandru Scafa-Udriste
Deep learning (DL)-based algorithms have demonstrated remarkable results in potentially improving the performance and the efficiency of healthcare applications. Since the data typically needs to leave the healthcare facility for performing model training...
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Khurram Naeem, Bok Hyeon Kim, Dong-Jin Yoon and Il-Bum Kwon
We propose a weighted singular value decomposition (WSVD) to reduce the random noise in the Rayleigh backscattering signal of the phase-sensitive optical time domain reflectometry (F-OTDR) to enhance the detection performance of the distributed vibration...
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