ID 原文 译文
16695 然后，针对轨迹的时序特性，该文采用逻辑回归的预测思路，用当前轨迹集在路网特征空间中的线性组合来预测轨迹； Secondly, considering the temporal features of the trajectory, the logistic regression method and the linearcombination of the current trajectory set in the road network features space are used to predict the trajectory.
16696 最后，结合自然语言处理领域中的词嵌入的思想，基于实际轨迹中节点存在的上下文关系，运用节点的向量集表征了节点间的交通时空关系。 Finally, Based on the idea of word embedding in the field of natural language processing and the contextualrelationship of intersections in the actual trajectory, the vector set of intersections is used to represent thespatiotemporal relationship of traffic between intersections.
16697 实验结果表明该模型不仅能够有效地提取轨迹特征，并且在拓扑结构复杂的路网中也能得到较好的预测结果。 The experimental results show that the model cannot only extract the trajectory features effectively, but also obtain better prediction performance in a roadnetwork with complex topology.
16698 P, T波的检测在临床上是心血管疾病诊断的重要依据。 The detection of P and T waves is an important basis for the diagnosis of cardiovascular disease inthe clinic.
16699 由于其波形能量低、形态复杂，极易受到噪声干扰，导致现有检测算法精度仍有待提高。 Because of its low waveform energy and complex shape, it is extremely susceptible to noise interference, which leads to the need to improve the accuracy of existing detection algorithms.
16700 该文提出平稳和连续小波变换融合算法检测P, T波， In this paper, aP and T wave algorithm based on stable and continuous wavelet transform is proposed .
16701 利用连续小波变换的多尺度信息，获取心电图(ECG)信号中P, T波主要成分，融合其平稳小波对P, T波候选段进行平滑处理，消除波形中锯齿状毛刺对峰值点检测的影响， First, the smoothwavelet transform is used to smooth the ElectroCardioGram (ECG) signal to eliminate the effect of jaggedburrs on the peak point detection. Then, the multiscale information of continuous wavelet transform is used toobtain the main components of P and T waves in the ECG signal.
16702 最后对P, T波过零点进行时移修正，保证过零点还原到原始信号过程中能够准确对应其峰值点，从而提高P, T波检测精度。 According to the translation correction rule,the time shift of the zero crossings of P and T waves is corrected to improve the detection accuracy of P and Twaves.
16703 该文算法在MIT-BIH arrhythmic数据库上进行验证，最终P波的误差率、敏感度、正确预测度达到：0.23%, 99.85%, 99.90%；T波的误差率、敏感度、正确预测度达到0.27%, 99.85%, 99.87%。 The algorithm of this paper is verified on the MIT-BIH arrhythmic database, and the final P-wave errorrate, sensitivity, and correct prediction reach 0.23%, 99.85%, 99.90%; the T-wave error rate, sensitivity, andcorrect prediction reach 0.27%, 99.85%, 99.87%.
16704 相较于线性调频(LFM)信号，双曲调频(HFM)信号因具有良好的脉冲压缩性能和多普勒不变性，被广泛用于雷达侦查、水声探测等多普勒影响严重的场景中，其中HFM信号的参数估计问题尤为重要。 Compared with Linear Frequency Modulation (LFM) signals, Hyperbolic Frequency Modulation(HFM) signals, which have good performance of the pulse compression and the Doppler invariance, are widely used in scenes with severe Doppler effects such as radar detection and underwater acoustic detection, and among them, the parameter estimation problem of HFM signals is particularly important.