ID 原文 译文
1013 由于涉及的优化问题是非凸的，本文先通过寻找问题最优解的结构，然后根据分式规划理论，提出了一种新的迭代资源分配算法来求解该问题。 The formulated problem is non-convex and thus is difficult to solve. To tackle this problem, we first find the structure of its optimal solution, and then pro-pose an efficient iterative algorithm to solve it based on the fractional programming technique.
1014 仿真结果表明，与“吞吐量最大化策略”和“固定时间分配策略”两种基准策略相比，所提出的算法显著提高了网络的能量效率。 Simulation results show that the energy efficiency performance of the proposed algorithm significantly outperforms that of two benchmark schemes, namely the throughput maximization scheme and the fixed time allocation scheme.
1015 本文设计并实现了依需聚合的语义深层网查询模型———SemtoSql + 。 In this paper, we design and propose SemtoSql + , a semantic deep network query model based on demand aggregation.
1016 提出以长短期记忆网络为基础，采用词嵌入技术将语料库训练为模型输入的词向量; At the same time, it is a network to address the complex and cross-domain Text-to-SQL generation task. Based on LSTM and Word2Vec embedding technology, the corpus is trained as the input word vector of the model.
1017 并结合依赖关系图，将 SQL 语句四个层级的生成问题转换为依赖关系图中槽的填充问题， Combined with the dependency graph method, the problem of SQL statement generation transforms into slot filling.
1018 同时引入注意力机制有效避免了传统模型中的顺序问题;采用随机蒙蔽机制，构建依需聚合的增强型 SemtoSql + 模型。 SemtoSql + divides com-plex tasks into four levels and constructs by the need of aggregation, using the attention mechanism to effectively avoid the order problem in the traditional model and using a random masked mechanism to enhance the model.
1019 论文提出了一种基于 trace 特征的逆合成孔径雷达( Inverse Synthetic Aperture Radar，ISAR) 像空间目标识别算法。 This paper proposes a space target recognition algorithm based on the trace feature of ISAR( Inverse Syn-thetic Aperture Radar) image.
1020 首先将 ISAR 像进行分割与归一化处理，利用 Canny 边缘检测、Hough 变换方法提取空间目标 ISAR 像最长轴，确保所提特征具有旋转不变性; Firstly, the ISAR images are segmented and normalized. The Canny edge detection and Houghtransform method are used to extract the longest axis of the ISAR image of space target to ensure the rotation invariance of the proposed feature.
1021 然后仅对最长轴所在局部区域进行 Trace 变换生成空间目标 ISAR 像的局部 trace矩阵，使得所提 trace 特征满足低维要求; Then, Trace transformation is only carried out in the local area where the longest axis is located to gen-erate the local trace matrix of ISAR image, so that the trace features proposed can meet the requirements of low dimension;
1022 再将 trace 矩阵每一列向量进行移位对准操作以消除 ISAR 像平移对识别带来的影响并将其作为空间目标识别的特征向量; then each column of the trace matrix is shifted and aligned to eliminate the impact of ISAR image translation on the recogni-tion and take it as the feature vector of the space target recognition;