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Zhi Quan, Hailong Zhang, Jiyu Luo and Haijun Sun
Signal modulation recognition is often reliant on clustering algorithms. The fuzzy c-means (FCM) algorithm, which is commonly used for such tasks, often converges to local optima. This presents a challenge, particularly in low-signal-to-noise-ratio (SNR)...
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Tianhao Gao, Meng Zhang, Yifan Zhu, Youjian Zhang, Xiangsheng Pang, Jing Ying and Wenming Liu
Classifying sports videos is complex due to their dynamic nature. Traditional methods, like optical flow and the Histogram of Oriented Gradient (HOG), are limited by their need for expertise and lack of universality. Deep learning, particularly Convoluti...
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Rong Wang, Xinyang Zhou, Yi Liu, Dongqi Liu, Yu Lu and Miao Su
To ensure the safety and durability of concrete structures, timely detection and classification of concrete cracks using a low-cost and high-efficiency method is necessary. In this study, a concrete surface crack damage detection method based on the ResN...
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Liang-Wei Ouyang, Jill C. Mayeda, Clint Sweeney, Donald Y. C. Lie and Jerry Lopez
This paper presents a broadband millimeter-wave (mm-Wave) low noise amplifier (LNA) designed in a 22 nm fully depleted silicon-on-insulator (FD-SOI) CMOS technology. Electromagnetic (EM) simulations suggest that the LNA has a 3-dB bandwidth (BW) from 17....
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Yan Liu and Zhichun Lei
Mitigating low-frequency noise in various industrial applications often involves the use of the filter-x least mean squares (FxLMS) algorithm, which relies on the mean square error criterion. This algorithm has demonstrated effectiveness in reducing nois...
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