Uniquely Decomposable Constellation Group-Based Sparse Vector Coding for Short Packet Communications

Sparse vector coding(SVC)is emerging as a potential technology for short packet communications.To further improve the block error rate(BLER)performance,a uniquely decomposable constellation group-based SVC(UDCG-SVC)is proposed in this article.Additionally,in order to achieve an optimal BLER performance of UDCG-SVC,a problem to optimize the coding gain of UDCG-based superimposed constellation is formulated.Given the energy of rotation constellations in UDCG,this problem is solved by converting it into finding the maximized minimum Euclidean distance of the superimposed constellation.Simulation results demonstrate the validness of our derivation.We also find that the proposed UDCGSVC has better BLER performance compared to other SVC schemes,especially under the high order modulation scenarios.

Influence of B1 code correlation loop for vector tracking structures under complicated environment

The code tracking loop is a key component for user positioning. The pseudorange information of Bei Dou B1 signals has been fused and changed for vector tracking, so a correlation output model for complex scenarios is designed to prevent the propagation of error and valuate the signal performance. The relevant software and hardware factors that affect the output are analyzed.A single channel time-division multiplexing(TDM) method for multicorrelation data extraction is proposed. Statistical characteristics of the correlation output data for both vector and scalar structures are evaluated. Simulation results show that correlation outputs for both structures follow normal or Chi-squared distributions in normal conditions, and the Gamma distribution in harsh conditions. It is shown that a tracking model based on the multi-channel fusion hardly changes the probability distribution of the correlation output in the normal case, but it reduces the ranging error of the code loop, and hence the tracking ability of the code loop for weak signals is improved. Furthermore, vector tracking changes the pseudorange characteristics of channels anytime, and affects the mutual correlation outputs of the code loops in the abnormal case. This study provides a basis for the subsequent design of autonomous integrity algorithms for vector tracking.

二元广义反码与最优LCD码

基于二元线性码的定义向量理论,引入广义反码及其定义向量概念,确立广义反码、它的参数与二元最优线性码之间的联系。利用广义反码的性质和参数研究对应二元最优线性码的线性补对偶(LCD)性质,证明11类二元最优线性码不是LCD码。该方法突破现有方法的局限性,为研究高维二元LCD的参数确定与构造问题提供了可借鉴的新理论和新方法。

Predicting and Classifying User Identification Code System Based on Support Vector Machines

In digital fingerprinting, preventing piracy of images by colluders is an important and tedious issue. Each image will be embedded with a unique User IDentification (UID) code that is the fingerprint for tracking the authorized user. The proposed hiding scheme makes use of a random number generator to scramble two copies of a UID, which will then be hidden in the randomly selected medium frequency coefficients of the host image. The linear support vector machine (SVM) will be used to train classifications by calculating the normalized correlation (NC) for the 2-class UID codes. The trained classifications will be the models used for identifying unreadable UID codes. Experimental results showed that the success of predicting the unreadable UID codes can be increased by applying SVM. The proposed scheme can be used to provide protections to intellectual property rights of digital images and to keep track of users to prevent collaborative piracies.

基于小波压缩深度学习重构的多图像光学加密

为解决多图像加密算法密文体积大、加密效果差、重构效果不理想等问题,提出一种基于小波压缩和深度学习重构的多图像光学加密方法。利用小波压缩提取多图像的低频部分,将重排后的新图放入改进的FDT-DRPE光学加密系统中得到密文;利用矢量分解和螺旋相位变换克服FDT-DRPE不敏感问题;构造的L_S混沌系统提高密钥敏感性。提出新型深度学习网络模型BHCN,解决传统图像重构精度不高问题。实验结果表明,密文体积可压缩至原图的1/4,重构图像的峰值信噪比为34.57 dB,结构相似性为0.9521,与同类文献相比,速度更快,重构效果更好,安全性更高。

基于运动向量修改的保持块间扰动最小的HEVC信息隐藏算法

高效视频编码(High Efficiency Video Coding, HEVC)标准能够大幅度提升压缩效率,正被广泛应用中。为提高基于运动向量修改的HEVC视频隐写算法的安全性,本文结合了HEVC标准中帧间预测编码的新技术,并利用在运动向量域进行信息嵌入扰动较小的优点,提出了一种基于运动向量修改的保持块间扰动最小的HEVC信息隐藏算法。首先,该算法量化了修改运动向量后对当前高级运动向量预测(Advanced Motion Vector Prediction, AMVP)单元和其相邻融合(Merge)模式预测单元产生的扰动代价,将运动向量垂直分量和水平分量之和作为原始载体元素。其次,结合校验网格码(Syndrome Trellis Codes, STC),寻找扰动代价最小的嵌入路径,通过修改运动向量中绝对值较大的分量将信息嵌入在AMVP模式的预测单元运动向量上。此外,为减小对视频质量的影响,利用修改后的运动向量更新运动向量差值。实验结果表明,所提方法对视频序列进行信息嵌入后,由于本文引入的扰动代价判断可以有效控制视频质量变化,对视频序列的峰值信噪比、码率影响较小,所以该方法对视频的扰动很小。而且本文算法不仅在视频质量保护上有良好的性能,还对运动向量域专用隐写分析具有良好的抗检测能力,有利于基于HEVC视频码流的隐蔽通信的进一步发展。

多信源多播网络编码问题的信息率区域刻画

该文研究多信源多播网络编码问题,其中每个信宿节点都希望正确解码由多个信源节点所生成的信源消息.对于该问题,率区域定义为平均使用一次网络时,信源节点可以将信源消息多播至所有信宿节点的码率元组所形成的集合.该文完全刻画了多信源多播网络编码问题的率区域,并且研究了码的构造.首先证明了对于信源节点集的任意子集,其码率和的上界为该子集到所有信宿节点的最小割容量的最小值.使用变换方法进一步发展了向量线性网络编码的系统构造.这种码的构造方式适用于任何可行的码率元组.基于已得到的率区域的外界以及码的构造,完整刻画出任意多信源多播网络编码问题的率区域.

基于安全多方计算的高效保密电子投票方案

保密电子投票是目前信息化时代广为使用的选举投票方案,可以提高选举的安全性、可靠性和公正性,以及增加选民的参与度。虽然保密电子投票方案具有许多潜在优点,如提高投票效率和方便性,但也面临着一些挑战,如信息安全问题、技术难题、隐私保护问题以及系统的信任度问题等。本研究针对这些问题,结合门限公开秘密体制(Number Theory Research Unit,NTRU)加密算法、向量编码方法,提出了一种基于安全多方计算的高效保密电子投票方案。为验证所提出协议的安全性,采用模拟范例方法进行了安全性证明。通过理论分析和实验仿真展示了本文提出方案的高效性,本方案具有实用价值,为解决电子投票过程中隐私保护问题提供了可行且高效的解决方案。

FAST IMAGE ENCODING ALGORITHM BASED ON MEAN-MATCH CORRELATION VECTOR QUANTIZATION

A mean-match correlation vector quantizer (MMCVQ) was presented for fast image encoding. In this algorithm, a sorted codebook is generated regarding the mean values of all codewords. During the encoding stage, high correlation of the adjacent image blocks is utilized, and a searching range is obtained in the sorted codebook according to the mean value of the current processing vector. In order to gain good performance, proper THd and NS are predefined on the basis of experimental experiences and additional distortion limitation. The expermental results show that the MMCVQ algorithm is much faster than the full-search VQ algorithm, and the encoding quality degradation of the proposed algorithm is only 0.3～0.4 dB compared to the full-search VQ.

Silhouettes Based Human Action Recognition in Video via Procrustes Analysis and Fisher Vector Coding

This paper proposes a framework for human action recognition based on procrustes analysis and Fisher vector coding(FVC).Firstly,we applied a pose feature extracted from silhouette image by employing Procrustes analysis and local preserving projection(LPP).Secondly,the extracted feature can preserve the discriminative shape information and local manifold structure of human pose and is invariant to translation,rotation and scaling.Finally,after the pose feature was extracted,a recognition framework based on FVC and multi-class supporting vector machine was employed to classify the human action.Experimental results on benchmarks demonstrate the effectiveness of the proposed method.

Local prediction of the chaotic fh-code based on LS-SVM

Support vector machine （SVM） is powerful to solve some problems such as nonlinear classification, function estimation and density estimation. To consider the chaotic fh （frequency hopping）-code＇s characters in chaotic dynamic system, the forecasting model of the support vector machine in combination with Takens＇ delay coordinate phase reconstruction of chaotic times is established and the least squares model for large-scale problems is used in local training for this model. Finally, a fh-code series generated by Logistic-Kent mapping is applied to verify the local prediction model. Simulation results show that the high accuracy and fault tolerant SVM model has an excellent performance in predicting the fh code, with a very low mean square error and a high relative coefficient.

A New Method of Designing Waveform Codebook

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ROTATED BARNES-WALL LATTICE BASED VECTOR QUANTIZER AND ITS APPLICATION IN IMAGE-SEQUENCE CODING

A new scheme is presented to design a rotated Barnes-Wall lattice based vector quantizer(LVQ). The construction method of the LVQ and its fast quantizing algorithm are described at first. Then gain-shape lattice vector quantizer(GSLVQ) with LVQ as shape quantizer is discussed. Finally the GSLVQ is used in image-sequence coding and good experimental results are obtained.

REMOTE SENSING IMAGE CODING METHOD COMBINING WAVELET TRANSFORM WITH CLASSIFIED VECTOR QUANTIZATION

A new remote sensing image coding scheme based on the wavelet transform and classified vector quantization (CVQ) is proposed. The original image is first decomposed into a hierarchy of 3 layers including 10 subimages by DWT. The lowest frequency subimage is compressed by scalar quantization and ADPCM. The high frequency subimages are compressed by CVQ to utilize the similarity among different resolutions while improving the edge quality and reducing computational complexity. The experimental results show that the proposed scheme has a better performance than JPEG, and a PSNR of reconstructed image is 31～33 dB with a rate of 0.2 bpp.

Image Coding Using Wavelet Transform and EntropyConstrained Vector Quantization with Quadtree Structure Vectors

This paper presents a new wavelet transform image coding method. On the basis of a hierarchical wavelet decomposition of images, entropy constrained vector quantization is employed to encode the wavelet coefficients at all the high frequency bands with

Lattice Vector Quantization Applied to Speech and Audio Coding

Lattice vector quantization （LVQ） has been used for real-time speech and audio coding systems. Compared with conventional vector quantization, LVQ has two main advantages： It has a simple and fast encoding process, and it significantly reduces the amount of memory required. Therefore, LVQ is suitable for use in low-complexity speech and audio coding. In this paper, we describe the basic concepts of LVQ and its advantages over conventional vector quantization. We also describe some LVQ techniques that have been used in speech and audio coding standards of international standards developing organizations （SDOs）.

METHOD OF VECTOR QUANTIZATION CODING USING RECTANGULAR TRANSFORM FOR IMAGE COMPRESSION

First of all a simple and practical rectangular transform is given,and then thevector quantization technique which is rapidly developing recently is introduced.We combinethe rectangular transform with vector quantization technique for image data compression.Thecombination cuts down the dimensions of vector coding.The size of the codebook can reasonablybe reduced.This method can reduce the computation complexity and pick up the vector codingprocess.Experiments using image processing system show that this method is very effective inthe field of image data compression.

OCDMA SystemSignature Code Design Theory Via Finite Projective Geometry

Optical orthogonal code is the main signature code employed by optical CDMA system. Starting from modern mathematics theory, finite projective geometry and Galois theory, the essential connection between optical orthogonal code designing and finite geometry theory were discussed; find out the corresponding relationship between the parameter of OOC and that of finite geometry space. In this article, the systematic theory of OOC designing based on projective geometry is established in detail. The designing process and results of OOC on projective plane PG(2,q) and on m-dimension projective space are given respectively. Furthermore, the analytical theory for the corresponding relation between OOC with high cross-correlation and k-D manifold of projective space is set up. The OOC designing results given in this article have excellent performance, whose maximum cross-correlation is 1, and the cardinality reaches the Johnson upper bound, i.e. it realizes the optimization in both MUI and system capacity.

A Novel Coding Method Based on Fuzzy Vector Quantization for Noised Image

In this paper a novel coding method based on fuzzy vector quantization for noised image with Gaussian white-noise pollution is presented. By restraining the high frequency subbands of wavelet image the noise is significantly removed and coded with fuzzy vector quantization. The experimental result shows that the method can not only achieve high compression ratio but also remove noise dramatically.

基于VectorCAST平台的铁路信号软件动态测试方法

铁路信号系统软件测试类型按照不同的分类方法可以分成静态测试和动态测试,黑盒测试和白盒测试,手动测试和自动测试等。这些方法适用于不同的测试阶段,且在同一个测试阶段又可结合使用,相辅相成,使软件测试活动的效用最大化。本文结合一种自动测试平台Vector CAST,介绍在集成测试阶段动态测试的软件覆盖率测量方法,结果可以作为动态测试案例集对软件需求覆盖度的评价指标,用于改进和提升动态测试的代码覆盖率,进而提升软件整体的可靠性和安全性。