ID 原文 译文
18545 设计了一种基于交替优化技术的迭代数值求解方案来保证算法的收敛性。 An iterative numerical scheme is developed with alternating optimization, and the convergence can be guaranteed effectively.
18546 该文在多个视觉数据集上进行分类任务的对比实验，实验结果表明所提算法在分类准确度和鲁棒性方面均优于传统特征学习方法。 Extensive experimental results on several visual datasetsdemonstrate that the proposed method outperforms conventional feature learning methods on both of accuracyand robustness.
18547 针对多约束条件下稀布矩形平面阵列天线的优化问题，该文提出一种基于动态参数差分进化(DPDE)算法的方向图综合方法。 For solving the problem of the synthesis of sparse rectangular planar arrays with multiple constraints,this paper proposes a Dynamic Parameters Differential Evolution (DPDE) based algorithm.
18548 首先，对差分进化(DE)算法中的缩放因子和交叉概率引入动态变化控制策略，提高搜索效率和搜索精度。 Firstly, to improvesearching efficiency and accuracy of Differential Evolution (DE), the proposed method introduces dynamicallychanging strategies to the scaling factor and the crossover probability of the traditional Differential Evolutionalgorithm.
18549 其次，改进矩阵映射方法，重新定义映射法则，改善现有方法随机性强和搜索精度低的不足。 Secondly, a modified matrix mapping method and the redefinition of mapping principles arepresented to make up the defects of strong randomness and low accuracy in existing methods.
18550 最后，为检验所提方法的有效性进行仿真实验，实验数据表明，该方法可以提高天线优化性能，有效降低天线的峰值旁瓣电平。 Finally,simulation experiments of antenna arrays are performed to validate the effectiveness of the proposed method,and the results demonstrate that the proposed method performs out the existing methods in the respect ofreducing peak sidelobe level of antenna arrays.
18551 无线局域网(WLAN)室内入侵检测技术是目前智能检测领域的研究热点之一，而传统基于数据库构建的入侵检测技术没有考虑复杂室内环境中WLAN信号的时变性，从而导致WLAN室内入侵检测系统的鲁棒性较差。 Wireless Local Area Network (WLAN) indoor intrusion detection technique is one of the current research hotspots in the field of intelligent detection, but the conventional database construction based intrusion detection technique does not consider the time-variant property of WLAN signal in the complicated indoor environment, which results in the low robustness of WLAN indoor intrusion detection system.
18552 为了解决这一问题，该文提出一种基于多核最大均值差异(MKMMD)迁移学习的WLAN室内入侵检测方法。 To address this problem, a Multiple Kernel Maximum Mean Discrepancy (MKMMD) transfer learning basedWLAN indoor intrusion detection approach is proposed.
18553 该方法首先利用离线有标记和在线伪标记的接收信号强度(RSS)特征来分别构建源域和目标域； First of all, the offline labeled and online pseudo-labeled Received Signal Strength (RSS) features are used to construct source and target domains respectively.
18554 其次，通过构造最优迁移矩阵以最小化源域和目标域RSS特征混合分布之间的MKMMD； Second, the optimal transfer matrix is constructed to minimize the MKMMD of the joint distributions of RSSfeatures in source and target domains.