喜悦
发表于 2025-3-21 16:32:54
书目名称Broadband Communications, Networks, and Systems影响因子(影响力)<br> http://impactfactor.cn/if/?ISSN=BK0191230<br><br> <br><br>书目名称Broadband Communications, Networks, and Systems影响因子(影响力)学科排名<br> http://impactfactor.cn/ifr/?ISSN=BK0191230<br><br> <br><br>书目名称Broadband Communications, Networks, and Systems网络公开度<br> http://impactfactor.cn/at/?ISSN=BK0191230<br><br> <br><br>书目名称Broadband Communications, Networks, and Systems网络公开度学科排名<br> http://impactfactor.cn/atr/?ISSN=BK0191230<br><br> <br><br>书目名称Broadband Communications, Networks, and Systems被引频次<br> http://impactfactor.cn/tc/?ISSN=BK0191230<br><br> <br><br>书目名称Broadband Communications, Networks, and Systems被引频次学科排名<br> http://impactfactor.cn/tcr/?ISSN=BK0191230<br><br> <br><br>书目名称Broadband Communications, Networks, and Systems年度引用<br> http://impactfactor.cn/ii/?ISSN=BK0191230<br><br> <br><br>书目名称Broadband Communications, Networks, and Systems年度引用学科排名<br> http://impactfactor.cn/iir/?ISSN=BK0191230<br><br> <br><br>书目名称Broadband Communications, Networks, and Systems读者反馈<br> http://impactfactor.cn/5y/?ISSN=BK0191230<br><br> <br><br>书目名称Broadband Communications, Networks, and Systems读者反馈学科排名<br> http://impactfactor.cn/5yr/?ISSN=BK0191230<br><br> <br><br>
水汽
发表于 2025-3-21 21:56:21
https://doi.org/10.1007/978-3-658-02134-4eries RFID tag signal to recognize static and dynamic gestures. We conduct extensive experiments in three different environments. The results demonstrate the superior effectiveness of the proposed RF-Mnet framework.
颂扬本人
发表于 2025-3-22 04:15:59
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enumaerate
发表于 2025-3-22 07:07:10
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reception
发表于 2025-3-22 11:19:31
Measuring and Analyzing the Burst Ratio in IP Traffic various network conditions, i.e. various loads, ports/applications used and packet size distributions. Secondly, we present theoretical values of the burst ratio, computed using a queueing model, and compare them with the values obtained in the measurements.
Monotonous
发表于 2025-3-22 16:40:25
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arabesque
发表于 2025-3-22 20:42:03
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GLUE
发表于 2025-3-23 00:31:41
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坚毅
发表于 2025-3-23 04:42:34
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讨好女人
发表于 2025-3-23 07:45:34
Dynamic IFFSM Modeling Using IFHMM-Based Bayesian Non-parametric Learning for Energy Disaggregation times-series modeling as an unsupervised BNP learning method. Our suggested method can grip with few or nappropriate learning data as well as to standardize electrical appliance modeling. Our proposed method outperforms FHMM-based FSM modeling results illustrated in literature.