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一元训练理论 被引量:160
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作者 茅鹏 严政 程志理 《体育与科学》 CSSCI 北大核心 2003年第4期5-10,18,共7页
传统的体育运动训练理论 ,是把“体能 (身体素质 )”与“技术”作为两个“元因素” ,是在这个基础上构建起来的 ,可称之为“二元”训练理论。二十世纪五、六十年代之交 ,有人发现这个理论迷误了。“体能”与“技术”本是“一元”的。这... 传统的体育运动训练理论 ,是把“体能 (身体素质 )”与“技术”作为两个“元因素” ,是在这个基础上构建起来的 ,可称之为“二元”训练理论。二十世纪五、六十年代之交 ,有人发现这个理论迷误了。“体能”与“技术”本是“一元”的。这个发现 ,萌发了“一元”训练理论 ,展开了对训练原理的新探索。本文谨对半个世纪的探索发现 ,扼要予以阐述。 展开更多
关键词 “一元”训练理论 “二元”训练理论 “技术” “体能” “体力波” “训练波” 运动能力
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Synchronization and channel estimation for MIMO OFDM wireless LAN systems 被引量:2
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作者 陆震 葛建华 《Journal of Harbin Institute of Technology(New Series)》 EI CAS 2009年第6期799-804,共6页
A new preamble structure is designed for wireless LAN based on MIMO OFDM systems, which can be used for both synchronization and channel estimation. Modulatable orthogonal polyphase sequence is utilized in training sy... A new preamble structure is designed for wireless LAN based on MIMO OFDM systems, which can be used for both synchronization and channel estimation. Modulatable orthogonal polyphase sequence is utilized in training symbol design regarding its correlation properties. The time synchronization and channel estimation are achieved by measuring the correlation between the received training sequence and the locally generated training sequence. Repeated training symbols are used to get carrier frequency offset (CFO) estimation. It is shown from the analysis that the accuracy of frequency synchronization is close to the Cramer-Rao lower bound. The training sequences are optimal for channel estimation based on the minimum mean square error (MMSE). 展开更多
关键词 SYNCHRONIZATION channel estimation MIMO OFDM wireless LAN
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Real-time road traffic state prediction based on ARIMA and Kalman filter 被引量:28
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作者 Dong-wei XU Yong-dong WANG +2 位作者 Li-min JIA Yong QIN Hong-hui DONG 《Frontiers of Information Technology & Electronic Engineering》 SCIE EI CSCD 2017年第2期287-302,共16页
The realization of road traffic prediction not only provides real-time and effective information for travelers, but also helps them select the optimal route to reduce travel time. Road traffic prediction offers traffi... The realization of road traffic prediction not only provides real-time and effective information for travelers, but also helps them select the optimal route to reduce travel time. Road traffic prediction offers traffic guidance for travelers and relieves traffic jams. In this paper, a real-time road traffic state prediction based on autoregressive integrated moving average (ARIMA) and the Kalman filter is proposed. First, an ARIMA model of road traffic data in a time series is built on the basis of historical road traffic data. Second, this ARIMA model is combined with the Kalman filter to construct a road traffic state prediction algorithm, which can acquire the state, measurement, and updating equations of the Kalman filter. Third, the optimal parameters of the algorithm are discussed on the basis of historical road traffic data. Finally, four road segments in Beijing are adopted for case studies. Experimental results show that the real-time road traffic state prediction based on ARIMA and the Kalman filter is feasible and can achieve high accuracy. 展开更多
关键词 Autoregressive integrated moving average (ARIMA) model Kalman filter Road traffic state REAL-TIME PREDICTION
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