个性化搜索中一种基于位置服务的隐私保护方法

在基于位置服务的个性化搜索中,利用可信第三方服务器以及对等节点是保护用户隐私的主要方法,但在现实生活中,它们却是不完全可信的。为了解决这一问题,该文提出一种个性化搜索中基于位置服务的隐私保护方法。该方法通过转换用户的位置信息,并根据用户的查询类型生成用户模型,进而形成带有用户位置信息的查询矩阵,然后利用矩阵加密用户的查询,隐藏查询矩阵中的用户信息,最后根据安全内积计算返回相关性得分最高的前K个查询文件给用户。安全性分析表明该方法能有效地保护用户的查询隐私和位置隐私,通过分析与实验表明,该方法大幅度地缩短了索引构建时间,降低了通信开销,同时为用户提供了基于位置的个性化搜索结果,一定程度上解决了移动设备屏幕小带来的弊端。     

一种面向深度神经网络的差分隐私保护算法

深度神经网络梯度下降过程中存在较大的梯度冗余,应用差分隐私机制抵御成员推理攻击时,会引入过量噪声。针对上述问题,该文利用Funk-SVD矩阵分解算法将梯度矩阵分解,分别在低维特征子空间矩阵和残差矩阵中添加噪声,利用梯度重构过程消除冗余梯度噪声。重新计算分解矩阵范数并结合平滑敏感度降低噪声规模。同时根据输入特征与输出相关性,将更多隐私预算分配给相关系数大的特征以提高训练精度。最后,根据分解矩阵范数均值提出一种自适应梯度剪裁算法以解决收敛缓慢的问题。算法利用时刻统计计算了在多种优化策略下的累计隐私损失。在标准数据集MNIST和CIFAR-10上验证了该文算法更有效地弥补了与非隐私模型之间的差距。     

一种基于ML算法及盲信道识别的DWPM系统

该文提出了一种基于ML算法及盲信道估计的离散小波包调制(Discrete Wavelet Packet Modulation,DWPM)系统.本文通过基于导频信号的盲信道识别方法,获得信道的状态信息,并且利用基于ZF(Zero Forcing)算法的H矩阵消除码间干扰,最后,利用ML(Maximum Likelihood)算法检测解调后的码元,并且通过仿真分析了该系统在多径衰落信道下的性能.仿真结果表明,该系统的性能要比传统的OFDM系统的性能好.     

基于动态反馈与功率分配的干扰对齐方法

在多用户MIMO系统中,信道状态的精确性严重影响干扰对齐技术的性能。该文针对信道状态信息(CSI)有限反馈导致的干扰泄露问题,提出一种基于动态反馈与功率分配的干扰对齐方法。首先从理论上分析了系统和速率与信道状态反馈比特分配和功率分配之间的关系,得到了在动态反馈和功率分配条件下系统和速率的解析表达式;在此基础上,以系统容量提升为目标,对反馈比特分配和功率分配优化问题进行建模;并根据信道的准静态特性利用库恩塔克条件(KKT)对该问题进行求解,得到功率和反馈比特分配方案。仿真结果表明,与单独考虑信道状态动态反馈条件下的干扰对齐技术相比,提出的方法能够有效减少干扰泄漏强度,提高系统和速率。     

基于博弈分析的众包交通监测隐私保护机制

众包交通监测利用移动终端上传的GPS位置信息实时感知交通状况,具有广阔的应用前景。然而,上传的GPS信息会泄露用户隐私。该文基于博弈论分析用户上传行为,提出隐私保护的优化上传机制。首先建立用户上传行为与路况服务质量和隐私泄露之间的关系,据此构建不完全信息博弈模型,以便分析用户上传行为;然后,根据用户上传博弈纳什均衡,提出用户终端可控的隐私保护优化上传机制。理论分析表明,该文提出的上传机制最大化用户效用,具有激励相容特性;通过真实数据实验验证,上传机制能够提高用户的隐私保护度,以及算法的激励相容特性。     

一种多输入多输出系统中有限反馈预编码的自适应跟踪测度

该文提出一种新的适用于无线相关信道中有限反馈预编码多输入多输出系统的预编码矩阵自适应跟踪测度。由于该测度在统计意义下对信道的相关性与预编码矩阵变化的关系具有更优化的描述,所以基于该测度的方案在保持较低反馈信息量的前提下,能够进一步改善预编码系统性能。文中给出优化自适应跟踪测度的理论推导。系统仿真分别针对无线信道的频域相关和时域相关,并结合空间分集和空间复用两类系统结构予以讨论,并验证了理论分析结果。另外,由于该测度方案算法复杂度更低,所以更具工程实用价值。     

基于矩阵低秩估计的可靠多载波差分混沌键控接收机

在多载波差分混沌键控(MC-DCSK)系统中,经由无线信道传输在接收端进行检测时,参考混沌信号的传输差错将降低承载信息的检测性能,降低传输可靠性。为了提高可靠性,该文基于承载信息的调制信号因共享参考混沌信号的低秩特性,提出了一种基于矩阵低秩估计(LRAM)的MC-DCSK接收机,增强系统可靠性。该接收机将接收信号矩阵表示为秩1矩阵和噪声矩阵之和,然后对接收信号矩阵进行低秩估计,以得到参考信号的最优估计,并进而将其用于承载信息的调制信号的检测和解调,从而提升系统传输可靠性。继而,该文证明了LRAM检测可等效于最大似然估计检测,并对信息泄露率理论安全性能进行了分析,分析结果表明所提方案安全性与基准MC-DCSK系统一致。仿真结果验证了该接收机在加性高斯白噪声(AWGN)和多径衰落信道下可有效提升MC-DCSK系统的可靠性。     

基于信道状态信息空时编码的FSOI系统设计

提出了一种新颖的基于空时编码的信道信息状态验证方法,添加训练比特序列来提高信道状态信息的精确性,确保自由空间光学互连系统的高效运行.理论分析和仿真结果表明,采用最大似然检测,利用信道信息状态进行重构,降低了系统误码率并提高了吞吐量.     

基于自适应的增广状态-交互式多模型的机动目标跟踪算法

现有的增广状态-交互式多模型算法存在着依赖于量测噪声协方差矩阵这一先验信息的问题。当先验信息未知或不准确时,算法的跟踪性能将会下降。针对上述问题,该文提出一种自适应的变分贝叶斯增广状态-交互式多模型算法VB-AS-IMM。首先,针对增广状态的跳变马尔科夫系统,该文给出了联合估计增广状态和量测噪声协方差矩阵的变分贝叶斯推断概率模型。其次,通过理论推导证明了该概率模型是非共轭的。最后,通过引入一种“信息反馈+后处理”方案,提出联合后验密度的次优求解方法。所提算法能够在线估计未知的量测噪声协方差矩阵,具有更强的鲁棒性和适应性。仿真结果验证了算法的有效性。     

基于确定性观测的压缩感知MIMO信道参数反馈

在实际资源受限(带宽受限或功率受限)的无线通信系统中,多径信道具有很强的稀疏特性,如何利用这一特点更加高效地将接收端获得的多径信道状态信息( CSI)进行压缩、反馈,是目前信道状态信息反馈技术的研究热点。针对现有多入多出( MIMO)信道状态信息反馈方法中随机观测矩阵需要较大存储空间的问题,引入了确定性Golay测量矩阵,提出了一种基于确定性观测的压缩感知MIMO多径信道参数反馈方法。在接收端对由信道估计得出的信道状态信息利用确定性Golay测量矩阵进行观测,将较少数目的观测值反馈到发送端,在发送端通过重构算法恢复出完全信道状态信息。仿真实验表明,与随机观测相比,采用确定性Golay观测矩阵的方法虽然需要的观测值数目会有所增加,但所需存储空间远小于随机观测矩阵,且利用确定性观测反馈信道状态信息的重构性能与随机观测矩阵相当。     

Verification analysis of self-verifying automata via semi-tensor product of matrices

The semi-tensor product （STP） of matrices was used in the article, as a new matrix analysis tool, to investigate the problem of verification of self-verifying automata （SVA）. SVA is a special variant of finite automata which is essential to nondeterministic communication with a limited number of advice bits. The status, input and output symbols are expressed in vector forms, the dynamic behaviour of SVA is modelled as matrix product is STP. By such algebraic formulation, three an algebraic equation of the states and inputs, in which the necessary and sufficient conditions are presented for the verification problem, by which three algorithms are established to find out all the strings which are accepted, rejected, or unrecognized by a SVA. Testing examples show the correctness of the results.     

Compatible-invariant subset analysis of deterministic finite automata via semi-tensor product of matrices approach

The compatible-invariant subset of deterministic finite automata (DFA) is investigated to solve the problem of subset stabilization under the frameworks of semi-tensor product (STP) of matrices. The concepts of compatible-invariant subset and largest compatible-invariant subset are introduced inductively for Moore-type DFA, and a necessary condition for the existence of largest compatible-invariant subset is given. Meanwhile, by using the STP of matrices, a compatible feasible event matrix is defined with respect to the largest compatible-invariant subset. Based on the concept of compatible feasible event matrix, an algorithm to calculate the largest compatible-invariant subset contained in a given subset is proposed. Finally, an illustrative example is given to validate the results.     

Passivity Verification in Delay-Based Macromodels of Multiconductor Electrical Interconnects

This paper presents a generalized theory of passivity verification in delay-based macromodels for multiconductor transmission line networks generated using the method of characteristics (MoCs). We demonstrate that the passivity in an MoC macro-model is equivalent to the nonnegative definiteness in the admittance matrices of two submodels. We then provide the necessary and sufficient conditions for each submodel to have a nonnegative definite admittance matrix. The presented theory develops an algebraic test to verify the passivity in MoC macromodels. Numerical results demonstrate the validity of the proposed theory.     

基于PMU的电力系统监控体系结构优化设计

文中提出了一种利用有限数量的相量测量单元(PMU)和相量数据集中器(PDC)设计最优监控结构的方法。通过在大量的设定值场景下,使电力系统可观测性曲线的期望值最大化,同时使通信基础设施成本最小化,最终确定PMU和PDC的最佳位置。提出了一种非线性动态扩展卡尔曼滤波(EFK)状态观测器。这种状态观测器可以将暂态行为转换为由代数微分方程描述的广域电力系统,而无需非线性反演技术。最后以IEEE-5电力系统为例,说明了该方法的有效性。     

Honeypot game‐theoretical model for defending against APT attacks with limited resources in cyber‐physical systems

A cyber‐physical system (CPS) is a new mechanism controlled or monitored by computer algorithms that intertwine physical and software components. Advanced persistent threats (APTs) represent stealthy, powerful, and well‐funded attacks against CPSs; they integrate physical processes and have recently become an active research area. Existing offensive and defensive processes for APTs in CPSs are usually modeled by incomplete information game theory. However, honeypots, which are effective security vulnerability defense mechanisms, have not been widely adopted or modeled for defense against APT attacks in CPSs. In this study, a honeypot game‐theoretical model considering both low‐ and high‐interaction modes is used to investigate the offensive and defensive interactions, so that defensive strategies against APTs can be optimized. In this model, human analysis and honeypot allocation costs are introduced as limited resources. We prove the existence of Bayesian Nash equilibrium strategies and obtain the optimal defensive strategy under limited resources. Finally, numerical simulations demonstrate that the proposed method is effective in obtaining the optimal defensive effect.     

Piezoelectric vibration control for all-clamped panel using DOB-based optimal control

Considering the spillover and harmonic effect in real active vibration control, a novel composite controller based on disturbance observer (DOB) for the all-clamped panel is presented. The single-mode of the piezoelectric panel can be regarded as a second-order system. The unmodeled error of the current controlled mode, harmonic effects, uncontrolled mode effects, etc., are regarded as the lumped disturbances which can be estimated by the DOB, and the estimated value is used for the feed-forward compensation design. Then, an optimal linear quadratic regulator (LQR) strategy is employed for the feedback design. In order to solve the difficulty of determining the weight matrices of LQR, a chaos optimization method based on logistic map is proposed. So the weight matrices can be tuned automatically. Combining with a new transient performance function, the optimal weight matrices can be obtained. The composite controller can effectively suppress the lumped disturbances of the all-clamped panel. Experiment comparisons with conventional LQR are given to verify the effectiveness of the proposed method.     

Privacy region protection for H.264/AVC with enhanced scrambling effect and a low bitrate overhead

While video surveillance systems have become ubiquitous in our daily lives, they have introduced concerns over privacy invasion. Recent research to address these privacy issues includes a focus on privacy region protection, whereby existing video scrambling techniques are applied to specific regions of interest (ROI) in a video while the background is left unchanged. Most previous work in this area has only focussed on encrypting the sign bits of nonzero coefficients in the privacy region, which produces a relatively weak scrambling effect. In this paper, to enhance the scrambling effect for privacy protection, it is proposed to encrypt the intra prediction modes (IPM) in addition to the sign bits of nonzero coefficients (SNC) within the privacy region. A major issue with utilising encryption of IPM is that drift error is introduced outside the region of interest. Therefore, a re-encoding method, which is integrated with the encryption of IPM, is also proposed to remove drift error. Compared with a previous technique that uses encryption of IPM, the proposed re-encoding method offers savings in the bitrate overhead while completely removing the drift error. Experimental results and analysis based on H.264/AVC were carried out to verify the effectiveness of the proposed methods. In addition, a spiral binary mask mechanism is proposed that can reduce the bitrate overhead incurred by flagging the position of the privacy region. A definition of the syntax structure for the spiral binary mask is given. As a result of the proposed techniques, the privacy regions in a video sequence can be effectively protected by the enhanced scrambling effect with no drift error and a lower bitrate overhead.     

Accelerating dynamic spiral MRI by algebraic reconstruction from undersampled k--t space

The temporal resolution of dynamic magnetic resonance imaging (MRI) can be increased by sampling a fraction of k-space in an interleaved fashion, which introduces spatial and temporal aliasing. We describe algebraically and graphically the aliasing process caused by dynamic undersampled spiral imaging within 3-D xyf space (the Fourier transform of k(x)k(y)t space) and formulate the unaliasing problem as a set of independent linear inversions. Since each linear system is numerically underdetermined, the use of prior knowledge in the form of bounded support regions is proposed. To overcome the excessive memory requirements for handling large matrices, a fast implementation of the conjugate gradient (CG) method is used. Numerical simulation and in vivo experiments using spiral twofold undersampling demonstrate reduced motion artifacts and the improved depiction of fine cardiac structures. The achieved reduction of motion artifacts and motion blur is comparable to simple filtering, which is computationally more efficient, while the proposed algebraic framework offers greater flexibility to incorporate additional algebraic acceleration techniques and to handle arbitrary sampling schemes.     

Design and experimental research of observer-based adaptive type-2 fuzzy steering control for automated vehicles with prescribed performance

Steer-by-Wire (SbW) system is a significant electromechanical subsystem of automated vehicles. This paper proposes an observer-based type-2 fuzzy control method for the SbW system with uncertain nonlinearity, unknown modeling parameters, and unavailable state. First, an interval type-2 fuzzy logic system (IT2 FLS) and an IT2 FLS-based state observer are constructed to estimate the uncertain nonlinearity and unavailable state of SbW systems. Then, a prescribed performance control (PPC) method is proposed to achieve the prescribed tracking performance of SbW systems. Much importantly, a modified performance function is incorporated in this control method, such that the prescribed tracking performance can be guaranteed within a finite time regardless of the initial state. Finally, simulation and vehicle experiments are given to verify the effectiveness and superiority of the proposed methods.     

Recasting modified nodal analysis to improve reliability in numerical circuit Simulation

Modified nodal analysis (MNA) can be considered as the most adopted method in circuit simulation programs. Once node equations were written and complemented with those from the current controlled branches, a nonlinear system of algebraic and/or differential equations is obtained. In general, by using linear multistep integration methods, differential equations are recast as nonlinear algebraic ones, which are solved through the Newton method at each integration time step. While computer precision is not an issue in most situations, some specific but frequent cases yield ill-conditioned or singular matrices even in originally well posed circuits. This drawback can occur in different situations namely in presence of strongly nonlinear elements and/or when very small integration time steps are used. In the second case, very large conductances in the companion model of capacitors can introduce roundoff errors. In this paper, a transformation of the MNA that overcomes these problems is proposed. It is based on a suitable recombination of equations and electrical variables of the conventional MNA and it can be easily implemented in a circuit simulator.