ID 原文 译文
14465 最后,在QPSK、8PSK、16APSK和32APSK这四种调制方式下,分析QPD算法的误码率、资源消耗和吞吐率。 Finally，the error symbol rate，resource consumption and throughput rate of the QPD algorithm are analyzed under the four modulation modes of QPSK，8PSK，16APSK and 32APSK．
14466 仿真结果表明,该算法相比于DD算法、PD算法、基于Q次方的极性环具有频偏估计范围较大、估计精度较高、资源消耗相对较少、吞吐率较高等特点,且适用于多种调制方式。 The simulation results show that compared with the DD algorithm，PD algorithm and the polar ring based on Q－th power，the algorithm has the characteristics of larger frequency offset estimation range，higher estimation accuracy，relatively less resource consumption，higher throughput rate，and is suitable for multiple modulation modes．
14467 准确地识别有出境意向的用户具有重要的意义,可为出境服务企业的精准营销实施、出境运营的高效管理和政策制定提供决策支持。 It is of great significance to accurately identify mobile phone users who will go abroad in the near future． It can provide decision support for the precise marketing implementation of outbound service companies，the efficient management of outbound operations and policy formulation．
14468 针对此需求,提出了一种基于多分类器集成和特征融合的用户出境预测方法。 Based onensemble learning and features fusion，a method for mobile phone users' outbound prediction is proposed．
14469 首先利用用户的移动终端信息交互数据,挖掘用户的出境相关行为特征和静态特征作为样本特征。 The method first uses the information interaction data of the user's mobile terminal，and mines users' specific behavioral features and attributes features as sample features．
14470 其次,通过最小冗余最大相关算法筛选最优特征,并利用贝叶斯优化算法寻找多个分类器最优超参数。 Secondly，the optimal features are selected by using the algorithm of minimum redundancy maximum correlation，and multiple classifiers are adjusted based on Bayesian optimization algorithm．
14471 最后,基于集成学习思想构建三层架构的用户出境预测模型,模型通过融合前两层分类器的输出特征生成新特征,并将其输入第三层分类器进行学习和预测。 Finally，a three－level model for users' outbound prediction is constructed by using ensemble learning method． The model generates new features by fusing the output features of 1－level and 2－level classifiers，and then uses the 3－level classifier to train and predict new features．
14472 实验表明,所提方法的F1值和AUC(Area under the Curve)值分别达到了97.16%和97.21%,对于用户出境具有较高的预测精度。 The experimental results show that the F1－score and the area under the curve( AUC) value of the proposed model is 97． 16% and 97． 21% ，respectively，and a higher prediction accuracy for users' outbound is obtained．
14473 当大功率信号进入接收机后,将迫使模数转换器工作在非线性区,并导致接收信号中含有大量非线性杂散。 When a high－power signal enters the receiver，the analog －to －digital converter( ADC) will be forced to work in nonlinear region，and there are a large number of nonlinear spurs in the received signal．
14474 为了抑制杂散并提高接收机对小信号的侦测能力,提出了一种具有无杂散高动态范围(Spurious-free Dynamic Range, SFDR)的信号接收方法。 In order to suppress spurs and improve the capability of detecting small signal，a signal receiving method with high spurious－free dynamic range( SFDＲ) is proposed．