基于渐进添边的准循环压缩感知时延估计算法

针对时延估计问题中压缩感知类算法现有测量矩阵需要大量数据存储量的问题,提出了一种基于渐进添边的准循环压缩感知时延估计算法,实现了稀疏测量矩阵条件下接收信号时延的准确估计.该算法首先建立压缩感知与最大似然译码之间的理论桥梁,然后推导基于低密度奇偶校验码的测量矩阵的设计准则,引入渐进添边的思想构造具有准循环结构的稀疏测量矩阵,最后利用正交匹配追踪算法正确估计出时延.对本文算法的计算复杂度与测量矩阵的数据存储量进行理论分析.仿真结果表明,所提算法在测量矩阵维数相同的条件下正确重构概率高于高斯随机矩阵和随机奇偶校验测量矩阵,相比于随机奇偶校验矩阵,在数据存储量相等的条件下,以较少的计算复杂度代价得到了重构概率的较大提高.     

基于多模光纤散斑的压缩感知在光学图像加密中的应用

为了安全高效地对图像信息进行传输,提出了一种新颖的基于多模光纤散斑的压缩感知结合双随机相位编码的光学图像加密方法.多模光纤产生的光斑作为压缩感知的测量矩阵,完成对图像的第一次压缩和加密,并且充当第一级密钥;再利用双随机相位编码技术进行第二次加密,实现对图像的完整加密过程,随机相位掩模板充当第二级密钥,解密过程与此相反.通过将光斑测量矩阵与用于压缩感知的常用随机测量矩阵进行对比研究后发现,使用光斑测量矩阵解密后的图像质量更好,而且相比于其他随机测量矩阵在硬件实现上的复杂性与高成本,光斑矩阵可以很容易地通过简单的光学器件来获得,且可以利用工作波长的改变来进行变换,也即第一级密钥非常容易变换.同时经研究表明,本文方法可以有效抵抗统计分析、噪声干扰和剪切等攻击,且对密钥敏感性高,具有良好的鲁棒性和安全性.因此,本文提出的这种基于光斑矩阵的压缩感知与双随机相位编码结合起来的加密方法,可以获得良好的加密效果与极大的密钥空间,并且易于在光学领域整合.     

基于近似l0范数最小化的NMR波谱稀疏重建算法

在核磁共振（NMR）波谱中,过长的数据采集时间会使很多化学以及分子生物学领域的高分辨率多维谱应用难以实现. 传统的解决办法是使用随机非均匀采样代替奈奎斯特采样,但这样会使谱图质量受损. 压缩传感的出现为此提供了更好的解决办法,合适的压缩传感重建算法可以通过很少的随机非均匀采样将谱图高质量的重建出来. 该文先介绍了一种可用于谱图重建的压缩传感重建算法,名为“平滑l₀范数最小化法”,然后针对该算法对采样噪声鲁棒性较差的缺点进行了改进. 通过将改进后的算法与原算法在一维实数域信号以及NMR波谱信号重建实验中进行对比后表明,改进后的算法对噪声的鲁棒性明显提高,并能获得更好的重建性能.     

Visual Secure Image Encryption Scheme Based on Compressed Sensing and Regional Energy

The network security transmission of digital images needs to solve the dual security problems of content and appearance. In this paper, a visually secure image compression and encryption scheme is proposed by combining compressed sensing (CS) and regional energy. The plain image is compressed and encrypted into a secret image by CS and zigzag confusion. Then, according to the regional energy, the secret image is embedded into a carrier image to obtain the final visual secure cipher image. A method of hour hand printing (HHP) scrambling is proposed to increase the pixel irrelevance. Regional energy embedding reduce the damage to the visual quality of carrier image, and the different embedding positions between images greatly enhances the security of the encryption algorithm. Furthermore, the hyperchaotic multi-character system (MCS) is utilized to construct measurement matrix and control pixels. Simulation results and security analyses demonstrate the effectiveness, security and robustness of the propose algorithm.     

面向低信噪比的自适应压缩感知方法

在压缩感知工程应用中, 信号往往被噪声和干扰所影响, 常规的压缩感知方法难以达到理想的重构效果, 特别是低信噪比应用场景中, 稀疏重构往往会失效. 分析了压缩感知中噪声对重构性能的影响, 从理论上解释了压缩感知中的噪声折叠原理, 并在此基础上提出了一种基于方向性测量的自适应压缩感知方案. 该方案通过后端信号处理系统估计出噪声的相关信息并反馈至压缩感知前端, 前端根据反馈的噪声信息调整测量矩阵, 从而改变感知矩阵的方向, 自适应地感知稀疏谱, 从而有效地抑制信号噪声. 仿真实验表明, 所提的自适应压缩感知方法对稀疏信号重构性能有较大的提升.     

基于压缩感知理论的~(252)Cf源中子脉冲信号分析

针对252Cf源驱动核材料产生裂变中子脉冲信号具有脉冲序列特殊的"0,1"稀疏结构之特点,采用压缩感知理论,通过巧妙引入图论中的二分图模型,同时结合二分图的最小覆盖性质,适当添加约束条件,构建了稀疏均匀的观测矩阵。研究结果表明,利用压缩感知理论对"0,1"中子脉冲序列特殊稀疏结构的信号重构算法不仅可行,而且还获得了优于l1范数最小化方法重构结果,这对252Cf驱动核材料的中子脉冲信号分析与处理提供了一种新的途径或方法。     

Authenticable Quantum Scheme for Secret Sharing Based on Local Distinguishability

The main defects of the existing quantum secret sharing schemes are as follows: (1) The identity of the secret sender cannot be confirmed. Receivers of shared secret information may be vulnerable to Trojan attacks; (2) If a malicious attacker Eve impersonates the identity of the receiver, she can finally obtain all the information of the secret that Alice shared; (3) In the process of secret recovery, it is necessary to transmit qubits among all participants involved in secret recovery. Sometimes, the same particle needs to be operated on by all participants to achieve secret sharing, which increases the possibility of eavesdropping and also increases the probability of errors. In this work, we proposed a quantum secret sharing scheme with authentication, the receiver performs corresponding operations on qubits of Greenberger-Horne-Zeilinger(GHZ) state based on the key string calculated by the shared identity number and random Error Correction Code(ECC), the secret sender can calculate the corresponding measurement basis(MB) through the information she has, and then inform the measurement party. This process realizes the mutual authentication between the sender and the receiver. It can protect against identity impersonation attacks, through the ECC verification, it also can resist intercept-resend attacks.

     

A hybrid strategy for cryptanalysis of optical encryption based on double-random phase–amplitude encoding

A hybrid two-step attack scheme that combines the chosen-plaintext attack (CPA) and the known-plaintext attack (KPA) algorithms is proposed to acquire the secret keys of the optical cryptosystem based on double-random phase–amplitude encoding (DRPAE) technique. By implementing our presented attack, an opponent can obtain not only the estimated solutions of the two random phase keys but also the accurate solution of the amplitude modulator (AM), which is introduced to the encryption process and regarded as an additional key to enhance the security level of the DRPAE-based cryptosystem. The validity and effectiveness of this attack strategy is analyzed theoretically and then verified by computer simulations.     

基于压缩感知的矢量阵聚焦定位方法

本文针对噪声源近场定位识别问题,利用声源分布在空间域具有稀疏性,在压缩感知理论框架下建立了新体系下的矢量阵聚焦波束形成方法,用于解决同频相干声源的定位识别问题.新方法可在小快拍下准确获得噪声源的空间位置,且不损失对噪声源贡献相对大小的评价能力.通过详细的理论推导、仿真分析和试验验证,证明了基于压缩感知的矢量阵聚焦定位新方法本质上实现了l1范数正则化求解下的波形恢复和空间谱估计,因此具有较高的定位精度,较强的相干声源分辨能力、准确的声源贡献相对大小评价能力以及较高的背景压制能力,可应用于水下复杂噪声源的定位识别.     

An infrared image super-resolution reconstruction method based on compressive sensing

Limited by the properties of infrared detector and camera lens, infrared images are often detail missing and indistinct in vision. The spatial resolution needs to be improved to satisfy the requirements of practical application. Based on compressive sensing (CS) theory, this thesis presents a single image super-resolution reconstruction (SRR) method. With synthetically adopting image degradation model, difference operation-based sparse transformation method and orthogonal matching pursuit (OMP) algorithm, the image SRR problem is transformed into a sparse signal reconstruction issue in CS theory. In our work, the sparse transformation matrix is obtained through difference operation to image, and, the measurement matrix is achieved analytically from the imaging principle of infrared camera. Therefore, the time consumption can be decreased compared with the redundant dictionary obtained by sample training such as K-SVD. The experimental results show that our method can achieve favorable performance and good stability with low algorithm complexity.     

基于量子图态的量子秘密共享

本文基于量子图态的几何结构特征,利用生成矩阵分割法,提出了一种量子秘密共享方案.利用量子图态基本物理性质中的稳定子实现信息转移的模式、秘密信息的可扩展性以及新型的组恢复协议,为安全的秘密共享协议提供了多重保障.更重要的是,方案针对生成矩阵的循环周期问题和因某些元素不存在本原元而不能构造生成矩阵的问题提出了有效的解决方案.在该方案中,利用经典信息与量子信息的对应关系提取经典信息,分发者根据矩阵分割理论获得子秘密集,然后将子秘密通过酉操作编码到量子图态中,并分发给参与者,最后依据该文提出的组恢复协议及图态相关理论得到秘密信息.理论分析表明,该方案具有较好的安全性及信息的可扩展性,适用于量子网络通信中的秘密共享,保护秘密数据并防止泄露.     

离散分数阶随机变换与加权直方图交叉置乱的双图像加密算法

为了实现对两幅图像进行同步加密,降低传输负载并提高密文的抗明文攻击能力,提出了离散分数阶随机变换与加权像素混沌置乱的双图像加密算法。将2个分阶参数引入到Tent映射中,设计了新的Tent映射;根据明文像素值,构建加权像素直方图模型,联合位外部密钥,生成改进的Tent映射的初值;再利用初值对分数阶Tent映射进行迭代,输出2组随机序列,对2幅明文进行位置交叉混淆,获取2个置乱密文;基于DWT(discrete wavelet transform)技术,对2个置乱密文进行稀疏表示;根据混沌序列,定义随机循环矩阵,联合稀疏表示,获取2个置乱密文对应的测量矩阵。根据随机掩码与调制相位掩码,建立数据融合模型,将2个测量矩阵组合为复合矩阵;基于离散分数阶随机变换,对复合图像进行扩散,获取密文。测试数据显示:与已有的多图像加密方案相比,该算法的抗明文攻击能力与用户响应值更理想,密文的NPCR、UACI值分别达到了99.83%、34.57%。该算法具有较高的加密安全性,能够有效抵御网络中的外来攻击,确保图像安全传输。     

Image sharing scheme based on combination theory

We present a simple algorithm for sharing and hiding secret image based on combination theory. The secret image is firstly encrypted by matrix multiplications and then shared into many shadow images by multiplying binary random sampling matrices. The sampling matrices randomly assign the pixel values to the shadow images which satisfy a specific combination rule as a constrain, so that the (t, n) threshold secret sharing scheme can be implemented. Numerical experiments have demonstrated the effectiveness of this image sharing algorithm.     

Efficient Solution to Electromagnetic Scattering Problems of Bodies of Revolution by Compressive Sensing

Under the theory structure of compressive sensing(CS),an underdetermined equation is deduced for describing the discrete solution of the electromagnetic integral equation of body of revolution(BOR),which will result in a small-scale impedance matrix.In the new linear equation system,the small-scale impedance matrix can be regarded as the measurement matrix in CS,while the excited vector is the measurement of unknown currents.Instead of solving dense full rank matrix equations by the iterative method,with suitable sparse representation,for unknown currents on the surface of BOR,the entire current can be accurately obtained by reconstructed algorithms in CS for small-scale undetermined equations.Numerical results show that the proposed method can greatly improve the computational efficiency and can decrease memory consumed.     

Structured sublinear compressive sensing via belief propagation

Compressive sensing (CS) is a sampling technique designed for reducing the complexity of sparse data acquisition. One of the major obstacles for practical deployment of CS techniques is the signal reconstruction time and the high storage cost of random sensing matrices. We propose a new structured compressive sensing scheme, based on codes of graphs, that allows for a joint design of structured sensing matrices and logarithmic-complexity reconstruction algorithms. The compressive sensing matrices can be shown to offer asymptotically optimal performance when used in combination with orthogonal matching pursuit (OMP) methods. For reduced-complexity greedy reconstruction schemes, we propose a new family of list-decoding belief propagation algorithms, as well as reinforced and multiple-basis belief propagation (BP) algorithms. Our simulation results indicate that reinforced BP CS schemes offer very good complexity–performance tradeoffs for very sparse signal vectors.     

Secure Direct Communication Based on Non-Orthogonal Entangled Pairs and Local Measurement

We propose a quantum secure direct communication scheme based on non-orthogonal entangled pairs and local measurement. In this scheme, we use eight non-orthogonal entangled pairs to act as quantum channels. Due to the non-orthogonality of the quantum channels, the present protocol can availably prohibit from all kinds of valid eavesdropping and acquire a secure quantum channel. By local measurement, the sender acquires a secret random sequence. The process of encoding on the random sequence is identical to the one in one-time-pad. So the present protocol is secure. Even for a highly lossy channel, our scheme is also valid. The scheme is feasible with present-day techniques.     

基于随机相位编码的确定性量子密钥分配

提出一种新的随机相位编码的确定性量子密钥分配(QKD)方案.在该方案中，通信双方不需要公布测量基，就可以共享秘密信息，提高了密钥生成效率.因为传输的量子比特是随机编码的，即便光源非严格为单光子，该方案仍旧是安全的.理论分析显示出，对于光子数分裂攻击，中间人攻击和特洛伊木马等攻击手段，本方案比之前的QKD方案具有更强的安全性.     

一种基于压缩感知的三维导体目标电磁散射问题的快速求解方法

提出了一种将压缩感知和特征基函数结合的方法来计算三维导体目标的雷达散射截面.利用压缩感知理论,将随机选择的矩量法阻抗矩阵作为测量矩阵,将激励电压视为测量值,然后再用恢复算法可实现二维或二维半目标感应电流的求解.对于三维导体目标,使用Rao-Wilton-Glisson基函数表示的感应电流在常用的离散余弦变换基、小波基等稀疏基上不稀疏.为此,本文将计算出的目标特征基函数作为稀疏基,用广义正交匹配追踪算法作为恢复算法来加速恢复过程,并应用到三维导体目标的雷达散射截面计算中.数值结果证明了本文方法的准确性与高效性.     

Implementing compressive fractional Fourier transformation with iterative kernel steering regression in double random phase encoding

This paper proposes a novel approach in double random phase encryption based on compressive fractional Fourier transform along with the kernel steering regression. The method increases the complexity of the image by using fractional Fourier transform and taking fewer measurements from the image data. Numerical results are given to analyze the validity of this technique. Considering natural images to be sparse in some domain, we apply a compressive sensing (CS) approach by using a TwIST algorithm. The encryption process has kernel steering regression algorithm for denoising and compressive sensing technique for image compression along with the fractional Fourier transform that makes the image in more complex form.     

基于回溯筛选的稀疏重构时延估计算法

针对无线定位中时延估计在小样本(单快拍)、低信噪比条件下需要大量独立分布测量数据问题,提出了一种基于回溯筛选的稀疏重构时延估计算法,实现了单快拍、低信噪比条件下接收信号的精确时延估计.该算法首先建立接收信号的稀疏表示模型,然后基于该模型建立正交观测矩阵,最后在重构算法中引入回溯筛选思想,利用时延与观测矩阵之间的一一对应关系得到时延的无偏估计.对该模型下时延估计的克拉美罗界进行了推导.仿真分析表明,所提方法在单快拍、低信噪比条件下精度远高于求根多重信号分类算法,相比于正交匹配追踪算法,在较小的复杂度代价下性能得到了较大提升.