数字混沌扩频序列的盲估计

混沌序列具有非线性、宽带类噪声、大的码族、任意长的周期且容易产生的特性,因此在扩频通信系统中很有实用价值。本文将文献[1]中对伪随机扩频序列盲估计的方法推广应用到混沌扩频通信中,并对其不足提出了改进方法。在只知道扩频码周期而无其它任何先验知识的条件下,利用特征值分析的方法可以对数字混沌直扩序列进行盲估计,仿真实验证明了该方法的有效性。     

Application of the blind source separation method to feature extraction of machine sound signals

As the result of vibration emission in air, a machine sound signal carries important information about the working condition of machinery. But in practice, the sound signal is typically received with a very low signal-to-noise ratio. To obtain features of the original sound signal, uncorrelated sound signals must be removed and the wavelet coefficients related to fault condition must be retrieved. In this paper, the blind source separation technique is used to recover the wavelet coefficients of a monitored source from complex observed signals. Since in the proposed blind source separation (BSS) algorithms it is generally assumed that the number of sources is known, the Gerschgorin disk estimator method is introduced to determine the number of sound sources before applying the BSS method. This method can estimate the number of sound sources under non-Gaussian and non-white noise conditions. Then, the partial singular value analysis method is used to select these significant observations for BSS analysis. This method ensures that signals are separated with the smallest distortion. Afterwards, the time-frequency separation algorithm, converted to a suitable BSS algorithm for the separation of a non-stationary signal, is introduced. The transfer channel between observations and sources and the wavelet coefficients of the source signals can be blindly identified via this algorithm. The reconstructed wavelet coefficients can be used for diagnosis. Finally, the separation results obtained from the observed signals recorded in a semi-anechoic chamber demonstrate the effectiveness of the presented methods .     

Ownership-attached unblinding of blind signatures for untraceable electronic cash

In an untraceable electronic cash protocol based on blind signatures, an identified customer can withdraw a blinded electronic cash from the bank and the unblinding operation is adopted by the customer to transform the blinded electronic cash into a valid one. Before performing the operation, the blinded electronic cash is protected well since attackers cannot convert it into a valid electronic cash without the blinding factor corresponding to the operation. However, after unblinding, the electronic cash will suffer from the theft attacks since it is not protected by any security mechanism. This paper introduces a new unblinding operation called ownership-attached unblinding which attaches the identities of a designated payee and a specified transaction to the blinded electronic cash and then produces an ownership-attached electronic cash other than a bare one such that the cash can withstand the theft attacks during the entire transaction because it is valid for the designated payee and the specified transaction only. Furthermore, the proposed scheme does not largely increase the computation cost required for each customer so that it also is a customer efficient protection solution for untraceable electronic cash and especially suitable for mobile clients and smart-card users.     

红外制导系统误差信号分布曲线及盲区的计算

本文介绍了红外制导系统误差信号分布曲线及盲区的计算方法，对目前红外界使用的计算公式进行了讨论。     

一种用于视频流的强鲁棒性数字水印方案

研究了视频流的水印嵌入和提取,为视频流提供版权保护。针对现阶段越来越多的视频流盗版现状,为了保护版权方的利益,提出了一种将版权方信息作为数字水印嵌入到视频流中的方法。通过该方法,在视频流中嵌入了不易破坏的版权方的信息,该信息可作为流媒体的追溯标记和证据。经实验证明:改进方案与其他数字水印方案相比,具有很强的鲁棒性,可抵抗视频的重复编码,抵抗分辨率缩放,抵抗一定程度的内容修改,支持水印的盲提取。     

ARD算法收敛性分析

对交替行对角化（ARD）算法收敛性进行分析.基于收敛性分析,给出了一些关于如何选取初始矩阵的策略,提出了算法终止的新准则.通过3个数值例子来说明所提出的分析策略的有效性.     

Blind Deconvolution Models Regularized by Fractional Powers of the Laplacian

We present a method for deconvolution of images by means of an inversion of fractional powers of the Gaussian. The main feature of our model is the introduction of a regularizing term which is also a fractional power of the Laplacian. This term allows us to recover higher frequencies. The model is particularly useful to devise an algorithm for blind deconvolution. We will show, analyze and illustrate through examples the performance of this algorithm.

矢量聚类及其在稀疏分量分析中的应用

针对传统聚类分析不能有效处理矢量数据聚类的问题,提出矢量聚类算法。该算法以点到矢量的距离最小化为分类依据,所得类簇中心为一矢量。根据稀疏信号的分布特性,用矢量聚类方法估计系统的混合矩阵,再利用估计的混合矩阵分离混合信号,从而得到稀疏信源的估计,简化了传统的混合信号分离过程。实验结果表明该矢量聚类方法能比传统的标量聚类方法更有效地估计矢量数据的中心,能在稀疏的处理域中很好地分离出稀疏信源。     

频域盲源分离的邻频幅角比排序算法

频域盲源分离方法通过STFT变换将时域的线性卷积模型转化为频域的瞬时混合模型,可以利用瞬时混合的成熟算法,然而缺点是存在排列和尺度的不确定性,会使逆STFT变换后的信号发生再次混叠。对分离矩阵内部结构进行研究,提出邻频幅角比的概念,通过纠正图样中发生排列错误频点处的分离矩阵结构,达到正确拟合已分离信号的目的。仿真结果表明,邻频幅角比排序算法可以纠正大多数频点上的排序错误,正确进行盲源分离。     

基于中心与邻域系数均值关系的盲水印算法

为了能够更好的满足水印的鲁棒性和不可见性,提出了一种基于关系的DWT域盲水印算法,首先对原始图像进行二级小波变换,在小波系数的中频子带中,根据比较中心系数与邻域系数均值关系的方法来嵌入水印,水印嵌入前进行了最优置乩处理,使得修改的中频系数最少,从而保证了较好的不可见性.在水印的提取过程中无需参考原始图像,实现了全盲检测.通过对嵌入水印的图像进行加入噪声、滤波、压缩以及裁剪等大量图像处理实验,均能正确检测出水印,结果表明算法具有很好的感知效果以及较强的鲁棒性,可用于数字图像的版权保护.