ID 原文 译文
21595 然后，中继依概率译码后提取出合法用户无法直接接收的固定信息再次进行安全极化编码并转发。 After receiving the codeword, relay decodes and extracts the frozen bits which the legitimate user can not obtain directly in probability, and re-encodes them by classical secrecy polar coding.
21596 最后，接收端利用收到的中继转发码字和发端码字依次分层进行译码。 Finally, the receiver decodes the received codewords from the relay and the transmitter in turn.
21597 理论和仿真分析证明，所提方法下合法用户能够可靠接收私密信息，而窃听者无法获取任何私密信息信息量； The theory and simulation results verify that the legitimate user is able to decode reliable, while the eavesdropper can not obtain any information about the secrecy bits.
21598 安全传输速率随着码长和中继转发概率的增加而增大，且高于一般的安全极化编码方法。 Moreover, the secrecy rate increases as the code length and the relay forwarding probability increase, and it outperforms the classical secrecy polar coding method.
21599 针对显示器电源线传导泄漏信号中红信号识别的难题，该文提出基于粒子群(PSO)算法优化支持向量机(SVM)的识别方法。 In order to identify the red signal in the conduction leakage signal of the display power line effectively, a Particle Swarm Optimization-Support Vector Mechine (PSO-SVM) algorithm based on ParticleSwarm Optimization (PSO) algorithm for parameter optimization is proposed.
21600 首先对传导泄漏信号进行滤波预处理并分段，然后利用粒子群-支持向量机(PSO-SVM)对传导泄漏信号进行训练、分类并与SVM分类性能进行对比，最后应用PSO-SVM实现了显示图像的还原。 Firstly, the conducted leakage signal is filtered, then the PSO-SVM is used to train and classify the conducted leakage signals and compared with the SVM classification. Finally, the display image is reconstructed using PSO-SVM.
21601 结果表明此算法可以准确实现电源线传导泄漏信号中红信号的识别，且识别率明显高于SVM分类器。 The result shows that the the red signal can be effectively identified, and the identification rate is significantly higher than the SVM classifier.
21602 独立向量分析(IVA)是解决频域卷积盲分离排序模糊性最好的方法之一，但存在迭代次数较多、运算时间较长、分离效果易受分离矩阵初值影响的局限性。 Independent Vector Analysis (IVA) is one of the best methods to solve the sort ambiguity of convolutive blind separation in frequency domain. However, it needs more iterations and computing time, and the separation effect is susceptible to the initial value of the separation matrix.
21603 该文提出一种基于步长自适应的IVA卷积盲分离算法，该算法使用特征矩阵联合近似对角化(JADE)算法对分离矩阵进行初始化，并对步长参数进行了自适应优化。 This paper proposes an IVA convolutive blind separation algorithm based on step-size adaptive, which uses Joint Approximative Diagonalization of Eigenmatrices (JADE) algorithm to initialize the separation matrix and optimizes adaptively the step-size parameters.
21604 JADE初始化能够使分离矩阵具有合理的初值，避免局部收敛的情况； JADE initialization can make the separation matrix have an appropriate initial value, thus avoiding the situation of local convergence;