欢迎您！东篱公司
退出
-
申报数据库
-
立项数据库
-
成果数据库
-
项目获奖数据库
中文摘要：
传统小波分解去噪需要先验知识,缺乏自适应性,将多元经验模态分解间隔阈值（Multivariate Empirical Mode Decomposition,MEMD）滤波方法用于电磁泄漏信息预处理。首先对电磁泄漏信号进行对齐处理。然后,针对多元经验模态分解直接阈值滤波产生的不连续性问题,提出采用MEMD间隔阈值滤波方法进行不相关模态滤波,解决传统经验模态分解的模态混叠问题。最后,分别采用巴特沃斯低通滤波、小波阈值、MEMD-DT和MEMD-IT方法对密码芯片电磁泄漏数据进行去噪处理,通过基于最小二乘支持向量机分类识别,实验结果表明该自适应去噪方法的优于传统的电磁侧信道分析预处理方法。
英文摘要：
To overcome the dependence of prior knowledge and non-adaptive of traditional filtering algorithm, a Multivariate Empirical Mode Decomposition interval threshold（MEMD-IT） de-noising which is a nonparametric signal de-noising approach is presented as a preprocessing stage for electromagnetic radiation signals. First, the near field electromagnetic leakage signals were captured while cipher device was executing RC4 algorithm. MEMD-IT is developed which can reduce the discontinuity induced by EMD-DT. Comparing with the other filters, such as Butterworth low-pass filter, wavelet threshold denoising, and MEMD direct threshold（MEMD-DT） de-noising, the proposed de-noising method evaluated by the Hanming weight classification results based on LSSVM has a better performance.
同期刊论文项目
同项目期刊论文
Study of half-metallic ferromagnetism in V-doped CdTe alloys by using First-Principles calculations.
Design of terahertz band-stop filter based on a metallic resonator on high-resistivity silicon wafer
位置：