语音信号盲分离方法研究

本文采用WVA分布与联合对角化的盲分离算法,估计出源语音信号,实现对混叠信号的盲分离。通过仿真实验,结果表明,本算法具有分离效果好,能有效的将混叠的盲语音信号分离。     

基于子块区域分割和自嵌入技术的全盲多功能图像水印算法

利用子块区域分割思想和自嵌入技术提出了一种只利用攻击图像就能进行版权鉴别和内容认证的全盲多功能图像水印算法。将原始图像分割成不重叠的子块,对每个子块进行离散余弦变换,将每个子块离散余弦变换矩阵分成为区域1和区域2两部分,然后对区域1进行奇异值分解,通过判断奇异值均值的最高位数字奇偶性产生特征水印,然后通过调整区域2的2个离散余弦变换交流系数大小自嵌入特征水印,最后对每个子块进行逆离散余弦变换得到含水印图像。算法通过结合将区域1产生的特征水印自嵌入区域2和在区域2盲提取认证水印实现全盲检测和多功能。实验结果表明,算法既能实现版权保护又能实现内容认证,而且还具有区分恶意篡改和无意篡改的能力。     

三频段准连续波雷达信号目标检测性能分析

准连续波雷达是一种低截获概率雷达,结合了脉冲雷达收发隔离和连续波雷达截获概率低的优点,但其检测性能的优劣很大程度依赖于信号形式,普通的编码信号和线性调频信号已经不能满足其对目标探测的要求。为解决这个问题,设计了一种三频段信号和与之相应的收发系统,对系统结构及三频段信号的参数选择原则、目标检测原理、模糊函数、抗近距离盲区性能做了详细分析,并指出了三频段信号相对于相位编码信号和分时发射信号的优势所在,最后通过仿真证明,将三频段信号应用于准连续波体制雷达中时能准确探测目标,得到目标的各个参数并且能有效消除近距离盲区。     

基于马尔科夫识别的敌我目标识别新方法

针对敌我识别系统在现代战争中的保密要求,提出一种将马尔科夫系统识别技术应用于敌我识别的新方法,每个发射机按照系统分配的转移矩阵发射随机码,接收机利用已知的不同我方作战单元的转移矩阵,判断码序列所属,实现我方目标的识别。与传统方法相比,发射机每次按照一定的转移概率发射服从马尔科夫分布的随机编码,大大提高了敌方截获和破译的难度,提升了系统的抗欺骗干扰性能。仿真结果表明,该方法在发射序列比较长的情况下,可以获得准确的识别结果。     

超短波跳扩频电台抗扫频干扰的性能仿真研究

依据超短波跳扩频电台的工作机理,采用Matlab中的Simulink分别建立了直扩、跳频、跳扩结合三种通信方式下的仿真模型以及扫频干扰模型。不仅研究了当存在扫频干扰时,改变扩频增益和跳频速度的参考值,仿真得出三种扩频方式下的误码率并进行了比较,还进一步探讨了改变扫频干扰参数（如扫频周期、扫频带宽等）情况下,计算各种通信方式下的干扰容限,比较得出跳扩结合模式抗扫频干扰性能最佳的结论。     

含噪盲信号分离与识别方法研究

针对经典FastICA不能对含噪盲信号进行较好的分离,提出了一种基于偏移FastICA及支持向量机(SVM)的含噪通信盲信号分离与调制方式识别的方法.其核心思想是首先对接收到的含有高斯白噪声的盲信号运用偏移FastICA进行分离,然后对分离出的信号分别提取5种特征参数,利用SVM对其数字调制方式识别,理论研究和仿真结果证明:偏移FastICA对含噪盲信号分离效果好,在信噪比不低于10 dB时,调制识别率可以达到93％以上,能够较好地识别2ASK,4ASK,2FSK,4FSK,2PSK,4PSK,16QAM信号,具有一定的可行性.     

Analysis and improvement of verifiable blind quantum computation

In blind quantum computation (BQC), a client with weak quantum computation capabilities is allowed to delegate its quantum computation tasks to a server with powerful quantum computation capabilities, and the inputs, algorithms and outputs of the quantum computation are confidential to the server. Verifiability refers to the ability of the client to verify with a certain probability whether the server has executed the protocol correctly and can be realized by introducing trap qubits into the computation graph state to detect server deception. The existing verifiable universal BQC protocols are analyzed and compared in detail. The XTH protocol (proposed by Xu Q S, Tan X Q, Huang R in 2020), a recent improvement protocol of verifiable universal BQC, uses a sandglass-like graph state to further decrease resource expenditure and enhance verification capability. However, the XTH protocol has two shortcomings: limitations in the coloring scheme and a high probability of accepting an incorrect computation result. In this paper, we present an improved version of the XTH protocol, which revises the limitations of the original coloring scheme and further improves the verification ability. The analysis demonstrates that the resource expenditure is the same as for the XTH protocol, while the probability of accepting the wrong computation result is reduced from the original minimum (0.866)^d* to (0.819)^d*, where d^* is the number of repeated executions of the protocol.     

A blind separation algorithm for underdetermined convolutional mixed communication signals based on time–frequency soft mask

This paper focuses on the separation for time–frequency (TF) overlapped communication signals received by the sensors. A novel blind separation strategy is proposed to improve the poor performance of signal separation by traditional algorithms for convolutional mixtures in underdetermined cases. Firstly, the number of sources and cluster centers are obtained in the sparse domain by combining the density peak clustering (DPC) with fuzzy c-means (FCM) clustering algorithm; Then the GMM clustering algorithm is applied to calculate the membership degree of the source signal in the mixed signals, so as to construct a TF soft mask matrix to more precisely carry out separation for TF overlapped signals. In this paper, the separation simulations are conducted with the digital modulation signals of 2ASK, BPSK, QPSK, etc. The results show that the algorithm proposed in this paper has better anti-aliasing and anti-noise performance than the comparison algorithms.     

Multi-hop wireless network oriented multiple jammers localization algorithm

A multiple jammer localization algorithm in multi-hop wireless networks was proposed. The proposed algo-rithm contained three steps, packet delivery ratio (PDR) valley point determination based on gradient descent algorithm, received jamming signal strength (RJSS) peak point determination based on gradient ascent algorithm and cluster analysis. Firstly, the algorithm started from a few initial nodes and moved along the gradient descent direction of PDR to approach the jammers until reaches the PDR valley point. Then, the algorithm moved toward the jammers using power adaptation technique based on RJSS gradient ascent process until it reached the RJSS peak point. Finally, through applying cluster analysis on the neighbour nodes which fail to communicate with RJSS peak points, the number and positions of the jam-mers can be estimated. Experimental results have verified that the proposed algorithm can improve the accuracy of local-ization compared with existed localization algorithms. Furthermore, the performance of the proposed algorithm is promi-nent when the distance of jammers accords with constraint condition.     

部分精英策略并行遗传优化的神经网络盲均衡

针对高维非凸代价函数下神经网络盲均衡算法收敛速度慢、容易陷入局部极小值的缺点,提出了一种组群并行遗传优化神经网络的方法。根据神经网络拓扑结构进行个体编码,设置控制码和权重系数码以实现对网络拓扑结构和网络权重同时优化。优化迭代过程中根据适应度对个体排序分组,以融合不同遗传算子条件下遗传算法的优势。部分精英策略有效避免最优个体把持进化过程引发早熟的现象。非线性信道条件下的仿真结果证明方法具有更好的收敛性能。