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彭岳星
- 电子邮箱：8a919013faa8db4c3cf1f139257ab9c549860978e831fbbe5c0a349139b81d6d6f4e067d7a51458f3c49e11ff5c41e48ce68e2e0bdc005060883fd51e292c0aef5827ccdd10f2b23863fca1cf02feb43af04704c1471d7a23bf5b0f32e1eab9cfce192021e602f7d3d1c1e5d9537973c200e1a6100ab66c79d3189a0e82dd83f
- 所在单位：信息与通信工程学院
- 学历：研究生毕业
- 办公地点：科研楼627
- 性别：男
- 学位：博士学位
- 职称：副教授
- 在职信息：在职
- 毕业院校：东南大学
- 硕士生导师
- 学科：信息与通信工程*
- 所属院系：信息与通信工程学院
访问量：
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[21]Y. Zhang, H. Long, Y. Peng, K. Zheng, W. Wang, User-oriented energy- and spectral-efficiency tradeoff for wireless networks, KSII Transactions on Internet and Information Systems, vol.7, no.2, pp 216-233, 2013/2/26.
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[22]Yuexing Peng, Yonghui Li, Lei Shu, Wenbo Wang, An energy-efficient clustered distributed coding for large-scale wireless sensor networks, Journal of Supercomputing, vol.66, no.6, pp 649-669, 2013/11/1..[J]:Journal of Supercomputing,66:649–669
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[23]Yueying Zhang, Fei Liu, Yuexing Peng, Hang Long, Wenbo Wang, Fundamental tradeoffs for ubiquitous wireless service: A QoE, energy and spectral perspective, Lecture Notes in Electrical Engineering, 203 LNEE(12), pp 971-979, 2012/12.
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[24]Xiangyu Lu, Yuyan Zhang; Yuexing Peng, Hui Zhao, Wenbo Wang, A real-time two-way authentication method based on instantaneous channel state information for wireless communication systems, J. of Commun., vol. 6, no.6, pp 471-476, 2011.
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[25]Yuexing Peng, Zhao Hui, Wang Wenbo, Inter-carrier Interference Analysis and Mitigation for OFDM System over Fast Fading Channels, Chinese J. Electronics, vol.19, no.1, pp 181-186, 2010/1.
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[26]Yuexing Peng, Zhao, Hui; Wang, Wenbo; Kim, Young Il, Cooperative network coding with soft information relaying in two-way relay channels, J. Commun., vol.4, no.11, pp 849-855, 2009.
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[27]Yuexing Peng, Muzi Wu, Hui Zhao, Wenbo Wang, Bit error probability of distributed Turbo coded relay systems over quansi-static Rayleigh fading channels, Journal of China university of posts and telecommunications, 17(2), pp. 41-45, 2010
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[28]Jianing Guo, Yuexing Peng, Qinguo Zhou, Wei Xiang, An Enhanced LSTM Model for Short-Term Load Forecasting in Smart Grids, chapter of the Book “Cloud Computing, Smart Grid and Innovative Frontiers in Telecommunications”, ISBN: 978-3-030-48512-2, May, 2020.
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[29]Lingling Tang, Yulin Yi, Yuexing Peng, An ensemble deep learning model for short-term load forecasting based on ARIMA and LSTM, in Proc. SmartGridComm 2019, Beijing, China, 21-23 Oct. 2019.
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[30]L. Han, Y. Peng, X. Gao, B. Zhao, An ensemble learning-based short-term load forecasting for small datasets, in Proc. CSPS 2017, Haerbing, China, 2017.
