会议信息

NCC 2014: National Conference on Communications

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NCC
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截稿日期:
2013-10-27 Extended
通知日期:
2014-01-15
会议日期:
2014-02-28
会议地点:
Kanpur, India
届数:
20
浏览: 20936   关注: 1   参加: 0

会伴指数 (CP-I)

49.1 / 100
全站第 1,783 名 / 共 5,682 个会议 · 前 32%

网络与通信 第 255 / 864

学术认可 (35%) 无数据 —— 按中性基准 50 分计入
投稿选择性 (20%) 无数据 —— 按中性基准 50 分计入
会议传承 (20%)
82
社区关注 (10%)
15
资料公开度 (15%)
25

用到的输入: 有据可查的届次:20 · 在会伴关注它的研究者:1 人 · 过去 24 个月打开过本页的研究者:2 人

公开资料里还缺: 历年录用率 (+4.5) · 历届信息 (+3.0) · 最佳论文记录 (+2.3)
主办方认领本会议后,可直接在这一页补上;分数每晚重算。如何提升这个分数

置信度 45% —— 分数中有多大比例来自实际观测到的数据,而不是中性基准。 这个分数是怎么算出来的 · 查看完整榜单 · 算法版本 1.1 · 算于 2026-09-17

征稿

NCC 2014 (National Conference on Communications) is an academic conference held in Kanpur, India on 2014-02-28. The paper submission deadline is 2013-10-27 (extended). Acceptance notifications are sent on 2014-01-15.

The Twentieth National Conference on Communications (NCC-2014) will be held at Indian Institute of Technology Kanpur, during 28th February - 2nd March 2014. The conference will feature three symposia in the following areas: Communication Theory and Systems Information Theory Coding Theory and Practice Wireless & Mobile Communications Broadband Wireless Access Satellite Communications Network Information Theory Cooperative Communications Cognitive Radio Optical Communications RF & Microwave Communications Antennas and Propagation VLSI for Communications Smart Grid Communications Green Communications Next Generation Networks Optical Networks & Systems Wireless & Wireline Networks Ad hoc & Sensor Networks Underwater Wireless Networks Vehicular Networks Networks & Information Security Network & Services Management Performance Analysis Complex Networks Network Interoperability Biological Networks Social Networks Network Testbeds Signal Processing for Communications Detection & Estimation Image & Video Signal Processing Computer Vision Multimedia Applications DSP Algorithms & Architectures Speech & Audio Processing Biomedical Signal Processing Language Identification Machine Learning Pattern Analysis & Classification Large Dimensional Signal Processing Compressive Sensing Sparse Signal Recovery
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