ID 原文 译文
26015 本文以手持式毫米波人体安检设备为研究背景，设计了一种工作于 90 ～ 94GHz 频段的稀疏十字阵列，并采用时域相关算法与改进距离徙动算法(Ｒange Migration Algorithm，ＲMA)对目标进行成像。 Sparse cross array that operating in the 90 ～ 94GHz frequency band was designed for the handheld millime-terwave human body security inspection. The time-domain correlation algorithm and the modified range migration algorithm
26016 针对改进 ＲMA 算法在推导过程中存在球面波展开为平面波近似和复杂的插值问题，本文提出一种高精度的无需球面波展开和复杂插值运算的基于(Fast Fourier Transform，FFT)的成像算法，在实现过程中不会引入近似误差和插值误差。 (ＲMA) were chosen as image reconstruction methods. Due to the existence of spherical wave expansion approximation and complex interpolation processes in the deriving of the modified ＲMA algorithm, a high-precision FFT-based imaging algorithm without spherical wave expansion and complex interpolations was proposed．
26017 采用电磁仿真软件建立目标回波模型，进行测试分辨率和噪声鲁棒性的实验。 The electromagnetic simulation software was used to build target model obtaining raw echo data, the resolution test and noise robustness verification experiments were carried out．
26018 系统方位分辨率达到 5mm，满足系统设计指标要求，验证了所提算法的正确性。 The azimuth resolution can achieve 5mm, which meets the system design requirements，and verifies the effectiveness of the proposed algorithm．
26019 综合实验结果得出所提算法的计算效率优于时域相关算法并且噪声鲁棒性优于改进 ＲMA 算法，在手持式毫米波人体安检设备实时成像的应用中，所提算法的适用性更好。 The computational efficiency of the proposed algorithm is better than that of the time-domain correlation algorithm and the noise robustness is better than the modified ＲMA algorithm. It can be concluded that the proposed algorithm is a better choice in real-time imaging scenarios of the hand held millimeter-wave human body security inspection．
26020 针对现有 Android 恶意代码检测方法容易被绕过的问题，提出了一种强对抗性的 Android 恶意代码检测方法。 Conventional Android malware detection method can easily be evaded. In this study, we propose a detection method of Android malicious code based on short-term memory network (LSTM), which makes malware more difficult to evade from detection．
26021 首先设计实现了动静态分析相结合的移动应用行为分析方法，该方法能够破除多种反分析技术的干扰，稳定可靠地提取移动应用的权限信息、防护信息和行为信息。 In this method, a program analysis framework that combines static and dynamic analysis is proposed at first toget the permission information, protection information and behavior information.
26022 然后，从上述信息中提取出能够抵御模拟攻击的能力特征和行为特征，并利用一个基于长短时记忆网络(Long Short-Term Memory，LSTM)的神经网络模型实现恶意代码检测。 Secondly, entrenched features such as ability features and behavior features are extracted from the information that provided by the program analysis framework. With the entrenched features, we design a malware detection method based on LSTM model to distinguish benign applications from the malicious ones．
26023 最后通过实验证明了本文所提出方法的可靠性和先进性。 Experimental results demonstrate that our approach is more effective and robust in Android malware detection than the state-of-the-art methods．
26024 传统主元分析(Principal Component Analysis，PCA)、相对主元分析等多元统计法基于阈值诊断故障，由于是原空间等价表示，并未增加任何信息量，使得微小故障难以诊断; Traditional principal component analysis, relative principal component analysis and other multivariate statistical methods based on threshold to do the fault diagnosis. Since multivariate statistical method is an equivalent representation of the original space, it does not add any amount of information, making it difficult to diagnose minor faults.