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Titlebook: Broadband Communications, Networks, and Systems; 10th EAI Internation Qingshan Li,Shengli Song,Honghao Gao Conference proceedings 2019 ICST

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發(fā)表于 2025-3-21 16:32:54 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
期刊全稱Broadband Communications, Networks, and Systems
期刊簡稱10th EAI Internation
影響因子2023Qingshan Li,Shengli Song,Honghao Gao
視頻videohttp://file.papertrans.cn/192/191230/191230.mp4
學(xué)科分類Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engi
圖書封面Titlebook: Broadband Communications, Networks, and Systems; 10th EAI Internation Qingshan Li,Shengli Song,Honghao Gao Conference proceedings 2019 ICST
影響因子.This book constitutes the refereed post-conference proceedings of the 10.th. International Conference on Broadband Communications, Networks, and Systems, Broadnets 2019, which took place in Xi’an, China, in October 2019. The 19 full papers presented were carefully reviewed and selected from 61 submissions. The papers are thematically grouped as follows: Wireless Networks and Applications, Communication and Sensor Networks, Internet of Things, Pervasive Computing, Security and Privacy..
Pindex Conference proceedings 2019
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書目名稱Broadband Communications, Networks, and Systems影響因子(影響力)




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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.
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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.
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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.
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