ID 原文 译文
25905 首先，从新闻文本中采用 TF-IDF(Term Frequeney-Inverse Document Frquency)和语义相似度算法构建负面新闻情感词库; Firstly, this paper uses TFIDF (Term Frequeney-Inverse Document Frquency) and emotional similarity algorithm to construct negative news emotional lexicon from news texts．
25906 其次，采用情感倾向计算方法计算负面新闻情感词的情感倾向度; Secondly, this paper uses the method of emotional tendency calculation to calculate the degree of emotional tendency of negative news affective words．
25907 最后，将词语和词语的情感倾向度进行向量化表示，并采用层次化多头注意力机制进行正负面新闻的判定。 Finally, the model vectorizes the emotional tendencies of words and expressions, and use hierarchical multi-attention model to judge the positive and negative emotions of news．
25908 情感计算和多头注意力机制的引入，对于捕获文本中的情感词语提供了很大帮助。 The introduction of emotional computing and multi-attention mechanism is of great help in capturing emotional words in texts．
25909 最终本文基于真实的网络新闻文本数据与现有的多种算法进行对比，证明了该模型具有较好的识别效果，相比于 Han 模型和 LSTM 模型分别提高了 0. 67% 和 3. 29% 。 Finally, this paper compares the real network news text data with many existing algorithms, and proves that the model has a good recognition effect. Compared with the Han model and LSTM model, it is increased by 0. 67% and 3. 29% respectively．
25910 为解决波达方向(Direction Of Arrival，DOA)估计方法在阵元失效条件下性能下降甚至失效的问题，本文提出一种基于 Toeplitz 协方差矩阵重构的 DOA 估计方法。 Array sensors failure can significantly deteriorate the performance of direction of arrival (DOA) estimation. To address this problem, an algorithm via covariance matrix reconstruction is proposed．
25911 首先，提出了一种失效阵元检测方法，并根据阵列的鲁棒性将失效阵元分为冗余阵元失效和非冗余阵元失效两种情况。 Firstly, we devise a diagnosis method to detect the failure sensors. Based on the robustness of the array, the sensor failure scenarios are divided into redundant sensor failures and non-redundant sensor failures．
25912 然后，分别针对两种失效场景提出相应 DOA 估计方法:一是冗余阵元失效，利用阵列冗余度，结合差联合阵列对失效阵元进行填充; Then, the corresponding DOA estimation method is adopted for two failure scenarios. For redundant sensor failures, the virtual sensors of the difference coarray can be used to occupy the positions of the failed physical sensors by utilizing the array redundancy．
25913 二是非冗余阵元失效，利用阵列冗余度进行填充后仍存在空洞，结合矩阵填充理论，用迹范数代替秩范数进行凸松弛以恢复协方差矩阵，进而实现对虚拟阵元空洞的填充，恢复阵列自由度。 For non-redundant sensor failures, the virtual sensors inthe difference coarray will have holes. Employing the matrix completion theory, we use trace norm instead of the rank norm for convex relaxation to recover the matrix, thereby realizing the filling of the virtual sensor holes in the difference coarray and restoring the DOFs．
25914 相对于稀疏类算法，有效消除了模型失配的影响。 Compared with the sparsity-based methods, the proposed method can eliminate the effect of the off-grid．