Although numerous researches have been done on corpus and cognitive linguistics, only a few researches combine them together, especially in language teaching. It provides a theoretical guidance for combining corpus an...Although numerous researches have been done on corpus and cognitive linguistics, only a few researches combine them together, especially in language teaching. It provides a theoretical guidance for combining corpus and cognitive linguistics in English lexical teaching. Linguists should take both the frequency and cognitive theories into consideration when they decide which word should be included in the lexical syllabus because there is sometimes a difference between the frequency and the tuition. What's more, the combination in lexical teaching can help EFL (English as a Foreign Language) learners to better deal with some common problems such as homonymy and synonymy.展开更多
在室外场景高倍压缩下,针对大规模多输入多输出(Multiple-Input Multiple-Output,MIMO)系统中大多数现有信道状态信息(Channel State Information,CSI)反馈方法重建精度低、复杂度较高的问题,提出了一种基于深度自编码器的CSI压缩反馈...在室外场景高倍压缩下,针对大规模多输入多输出(Multiple-Input Multiple-Output,MIMO)系统中大多数现有信道状态信息(Channel State Information,CSI)反馈方法重建精度低、复杂度较高的问题,提出了一种基于深度自编码器的CSI压缩反馈方法。该方法首先在编码器采用卷积神经网络提取原始CSI的特征信息;然后将全连接网络压缩为低维码字反馈回解码器;最后考虑到室外环境的CSI空间模式复杂、高倍压缩下信息损失较多,在解码器的残差网络中使用并行多分辨率卷积网络与具有丰富神经元的全连接网络对接收到的特征码字进行重建,以此增强所提方法的重建能力与泛化能力。实验结果表明,所提方法的重建质量在不同压缩比下均有显著提升。展开更多
文摘Although numerous researches have been done on corpus and cognitive linguistics, only a few researches combine them together, especially in language teaching. It provides a theoretical guidance for combining corpus and cognitive linguistics in English lexical teaching. Linguists should take both the frequency and cognitive theories into consideration when they decide which word should be included in the lexical syllabus because there is sometimes a difference between the frequency and the tuition. What's more, the combination in lexical teaching can help EFL (English as a Foreign Language) learners to better deal with some common problems such as homonymy and synonymy.
文摘在室外场景高倍压缩下,针对大规模多输入多输出(Multiple-Input Multiple-Output,MIMO)系统中大多数现有信道状态信息(Channel State Information,CSI)反馈方法重建精度低、复杂度较高的问题,提出了一种基于深度自编码器的CSI压缩反馈方法。该方法首先在编码器采用卷积神经网络提取原始CSI的特征信息;然后将全连接网络压缩为低维码字反馈回解码器;最后考虑到室外环境的CSI空间模式复杂、高倍压缩下信息损失较多,在解码器的残差网络中使用并行多分辨率卷积网络与具有丰富神经元的全连接网络对接收到的特征码字进行重建,以此增强所提方法的重建能力与泛化能力。实验结果表明,所提方法的重建质量在不同压缩比下均有显著提升。
