ARCHE
发表于 2025-3-25 05:15:48
Sweep-Frequency Measurements of Solar Burstspay attention to the fault diagnosis of power transformers. This paper proposes a fault diagnosis method based on Canonical Variate Analysis and Support Vector Machine (CVA-SVM). As a system identification method, CVA is widely used for fault detection because of its ability to identify multivariate
Embolic-Stroke
发表于 2025-3-25 10:37:41
Some Problems of Planetary Radio Astronomyn implementing smart city service. Along with the security problem, Mobile Edge Computing(MEC) and Blockchain techniques are applied to relieve these problems. This paper proposes a MEC system based on Blockchain, and models the resource allocation problem taking into account the mining time and min
Panther
发表于 2025-3-25 14:08:51
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驳船
发表于 2025-3-25 16:43:03
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GUISE
发表于 2025-3-25 23:21:07
https://doi.org/10.1007/978-981-99-2362-5Wireless communications; Wireless networks; Internet of Things; Wireless sensor networks; Signal process
STALL
发表于 2025-3-26 03:04:49
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动机
发表于 2025-3-26 05:41:21
Research on the Improved Design and Implementation of Signal Processing and Detection Algorithm forsignal to noise ratio in signal detection is introduced. Then, a signal detection method for high speed moving target is proposed. Based on the real data of high speed moving target, several detection methods in radar signal processing algorithm are compared and analyzed, and the advantages and disadvantages of different methods are described.
宇宙你
发表于 2025-3-26 10:42:24
,A Low Complexity Decoding Algorithm for Polar Codes with Flexible Path Expansion and List Size,ist size. Simulation results show that when the bit error rate reaches ., the complexity of our proposed algorithm can be reduced by 69.29% and 43.16% compared with cancellation list decoding of polar codes based on path metric and traditional MP-SCL, respectively.
罐里有戒指
发表于 2025-3-26 15:31:38
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Harridan
发表于 2025-3-26 18:50:16
An Improved Grey Wolf Optimizer for Numerical Optimization,ump out of local optimum. Simulation experiments on the CEC2017 test set show that compared with standard GWO, the results obtained by IGWO have higher accuracy, which proves that the algorithm has better performance in dealing with complex optimization problems.