culinary 发表于 2025-3-21 19:15:40
书目名称Wireless Algorithms, Systems, and Applications影响因子(影响力)<br> http://impactfactor.cn/if/?ISSN=BK1028939<br><br> <br><br>书目名称Wireless Algorithms, Systems, and Applications影响因子(影响力)学科排名<br> http://impactfactor.cn/ifr/?ISSN=BK1028939<br><br> <br><br>书目名称Wireless Algorithms, Systems, and Applications网络公开度<br> http://impactfactor.cn/at/?ISSN=BK1028939<br><br> <br><br>书目名称Wireless Algorithms, Systems, and Applications网络公开度学科排名<br> http://impactfactor.cn/atr/?ISSN=BK1028939<br><br> <br><br>书目名称Wireless Algorithms, Systems, and Applications被引频次<br> http://impactfactor.cn/tc/?ISSN=BK1028939<br><br> <br><br>书目名称Wireless Algorithms, Systems, and Applications被引频次学科排名<br> http://impactfactor.cn/tcr/?ISSN=BK1028939<br><br> <br><br>书目名称Wireless Algorithms, Systems, and Applications年度引用<br> http://impactfactor.cn/ii/?ISSN=BK1028939<br><br> <br><br>书目名称Wireless Algorithms, Systems, and Applications年度引用学科排名<br> http://impactfactor.cn/iir/?ISSN=BK1028939<br><br> <br><br>书目名称Wireless Algorithms, Systems, and Applications读者反馈<br> http://impactfactor.cn/5y/?ISSN=BK1028939<br><br> <br><br>书目名称Wireless Algorithms, Systems, and Applications读者反馈学科排名<br> http://impactfactor.cn/5yr/?ISSN=BK1028939<br><br> <br><br>使出神 发表于 2025-3-21 21:45:22
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978-3-031-19213-5The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature SwitzerlThymus 发表于 2025-3-22 08:16:43
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Robust Adaptive Cubature Kalman Filter for Attitude Determination in Wearable Inertial Sensor Networt CKF algorithm based on quaternion and gyroscope error modeling proposed in this paper can solve motion attitude solution. Lastly, we compare our method with CKF and EKF algorithm, the proposed algorithm can effectively improve the precision of attitude analysis.放弃 发表于 2025-3-22 19:41:00
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0302-9743 edings were carefully reviewed and selected from 265 submissions. The contributions in. algorithms, systems; and applications of internet of things;information processing and data management;.radar and sonar networks.978-3-031-19213-5978-3-031-19214-2Series ISSN 0302-9743 Series E-ISSN 1611-3349Androgen 发表于 2025-3-23 06:51:51
Unsupervised Deep Learning-Based Hybrid Beamforming in Massive MISO Systemstimizing the HBF through deep learning (DL) has gained considerable attention in recent years due to its potential in dealing with the nonconvex problems. However, existing DL-based HBF methods require wider or deeper neural networks to guarantee training performance, which not only leads to higher