改进DTW下界函数的距离度量方法研究

动态时间弯曲算法（DTW）是一种常见的时间序列相似性度量方法,对数据挖掘任务起着至关重要的作用。针对现有DTW算法的时间复杂度高、度量精确度一般的特征,提出一种DTW下界函数的提前终止算法（LB＿ESDTW）。引入提前终止思想,提高算法的执行效率;再在提前终止算法思想的基础上,与DTW下界函数相结合,提出一种基于提前终止DTW的下界函数算法（LB＿ESDTW）。该算法在保证高效的运行时间效率的同时,也使得算法的度量准确率得到了提升。实验结果表明,LB＿ESDTW在绝大部分时间序列数据集中,都表现出良好的适应性,针对不同类别的时间序列,都能有良好的度量性能。     

基于局部梯度和二进制模式的时间序列分类算法

时间序列分类问题是时间序列数据挖掘中的一项重要任务, 近些年受到了越来越广泛的关注. 该问题的一个重要组成部分就是时间序列间的相似性度量. 在众多相似性度量算法中, 动态时间规整是一种非常有效的算法,目前已经被广泛应用到视频、音频、手写体识别以及生物信息处理等众多领域. 动态时间规整本质上是一种在边界及时间一致性约束下...     

一种基于包排队方式的网络路径可用带宽探测方法

对IP网络路径带宽的探测是目前网络研究领域的一个热点。本文提出了一种针对端到端的网络、基于包排队方式的双向双步长网络路径可用带宽的探测方法。该探测方法由时延监视和UDP发送两个进程组成,基于包的排队时延来获取路径的可用带宽,并通过采用双向双步长的方法来递增或递减UDP包的发送速率。所提出的探测方法可以明显减少探测次数和运行时间,从而降低探测带来的开销。实验结果显示,所设计的方法和技术是可行的和有效的。     

随机系统中能容忍连续丢包和测量时延的卡尔曼滤波

通过转换原线性系统到能容忍连续丢包和测量时延的随机参数系统,推导了一个最优线性滤波器.给出一个仿真例子,比较已存在的结果,仿真结果表明被提出的线性滤波器有优越的性能.然而,该滤波器不能应用于非线性系统.从应用角度,为非线性系统提出了一个增强型的滤波器.而且,该增强型的滤波器能成功地应用于不可靠的无线传感器网络场景来跟踪移动目标.这些滤波器只依靠测量值的达到概率,而不需要知道某一时刻测量是否接收.仿真说明了被提出的增强型滤波器不仅能改善实时目标跟踪的鲁棒性,而且比标准的扩展卡尔曼滤波器能够提供更精确的估计.     

水泥熟料质量软测量模型中的时序分析方法

针对常规水泥熟料质量软测量模型未充分考虑过程变量间时序信息的问题,本文根据水泥生产流程工艺的时滞性、连续性特点,提出了一种时序分析方法,以提高熟料中游离氧化钙含量的软测量准确度.首先根据物料的传输机理,估算出物料在各工艺设备中的停留时间,在此基础上将软测量模型的输入输出变量进行时序匹配,之后采用类高斯函数对各输入变量匹配时刻前后的时序数据进行加权,获得具有时序信息的输入–输出样本对,然后以支持向量机模型结构为例,对引入时序信息后的游离氧化钙含量软测量模型进行训练和测试,并讨论了时序参数对结果的影响.采用某水泥生产线的实际过程数据对本文模型与方法进行验证,结果表明,该模型预测值与实际的游离氧化钙含量吻合良好,能正确预测其变化趋势;将本文模型测量结果与未使用时序信息的常规支持向量机模型对比,结果表明,过程变量间的时序信息有助于提高水泥熟料质量软测量模型的精度.本文提出的时序分析方法为水泥生产等流程工业过程建立软测量模型提供了新思路.     

Measurement designs to improve the computational efficiency of linear system state estimators

A design procedure for the measurement process is proposed to decrease the computational burden of state estimation in linear discrete-time systems. System order reduction is involved, which is achieved by a derived transformation, yielding an alternative system and measurement process representation that includes time delays in both the system and the measurement process. Without loss of filter optimality, measurement designs yielding reductions in the computational requirements of the Kalman filter applied to the reduced order system are derived. A computational comparison is included to show that the proposed method, as opposed to the direct application of the Kalman filter, can yield large reductions in the filter computation time.     

Differentiator-based time delay control for uncertain robot manipulators

High-quality acceleration signal plays a significant role in fast and precise trajectory tracking of robot manipulators via time delay control (TDC). This paper proposes a fast transient tracking differentiator (FTD) for obtaining the noise-less time derivative from a noisy measurement within the framework of tracking differentiator (TD) design methodology. Global asymptotic convergence of the proposed FTD is proven by Lyapunov's direct method and TD theory. The proposed FTD is cascaded to construct an acceleration estimation and is integrated with the commonly used TDC for an improved trajectory tracking of robot manipulators in the presences of parametric uncertainties and bounded disturbances. Numerical simulations and real-time experimental validation comparisons demonstrate that the proposed approach provides an easy-going model-free improved design for fast and accurate trajectory tracking of robot manipulators with position measurement only.     

Adaptive tracking system for a manoeuvring target using images with correlated noises

An effective scheme is proposed for estimating the state parameters of a manoeuvring target from a noisy image sequence, providing the sequence contains correlated noises and the trajectory of the target is disturbed by an unknown acceleration. For the correlated noises, a first-order difference operator is applied to the original image sequence to generate an artificial measurement sequence with only uncorrelated white noises. For the unknown acceleration, a Kalman filter augmented by a semi-Markov process and the bayesian theory is applied to form an adaptive filter. In the proposed tracking system, the filter first generates an artificial measurement at each sampling time from the observation. It then utilizes an artificial measurement sequence up to the current time instance to predict the a posteriori probability of each possible acceleration state. The weighted average of acceleration, where the weight is the a posteriori probability, is applied to derive the optimal estimates of the state parameters. Several computer simulations with external force applied at unknown times are performed to demonstrate the applicability and superiority of the proposed system.     

Precise evaluation of LCD gray‐to‐gray response time based on a reference pattern synchronous measurement using high speed charge‐coupled device camera

A reference pattern method based on synchronous measurement for evaluating the response time of liquid crystal display was proposed to overcome the shortcomings of the unsmooth response curve induced by the backlight modulation. The feasibility of the method is verified by measurement using a high speed charge‐coupled device camera. The measured gray‐to‐gray response time results are compared with those obtained from standard measurement approach. The results indicate that the proposed method improves the accuracy and repeatability of the response time measurement.     

一种提高溶解氧测定响应速度的方法

研究了溶解氧测定仪的响应时间影响因素,提出了一种提高溶解氧测定的响应速度的方法;利用在电流电压转换电路的精密电阻上并联一个储能电容,该电容在测量系统断电之后,能够继续给溶解氧测定的阴极和阳极提供0.2 V左右的极化电压;在溶解氧进行多次测量的时候,测量系统通电之前被测溶液已经有了一个低电压预极化的过程,可以大幅降低0.68 V极化电压对被测溶液的极化时间。测试结果显示,该方法与没有使用储能电容预极化系统相比,响应时间能减少40%。     

Adaptive sliding mode control for a class of uncertain discrete-time systems using multi-rate output measurement

This article is concerned with the design of an adaptive sliding mode control (SMC) for a class of uncertain discrete-time systems using the multi-rate output measurement. The states of the discrete-time systems are assumed to be taken in the multi-rate output measurement by the contamination with measurement noise. The uncertainties are assumed not to satisfy the matching condition, and are expressed in a parameterised form. A least squares estimator (LSE) to take the estimates for the un-measurable states and the uncertainties is designed in a batch form by using the noisy multi-rate output measurement. The proposed adaptive SMC is designed by using the sliding surface expressed as the linear state function and the estimates obtained from the LSE. It is proved that the estimation errors converge to zero as time tends to infinite, and the states of the system are bounded under the action of the proposed adaptive SMC. The effectiveness of the proposed method is indicated through the simulation experiment in a simple system.     

基于ARM+CPLD的高精度超声波风速仪的设计

分析了运用超声波时差法测量风速风向的基本原理,介绍了风速风向的相关算法,重点给出了基于ARM+CPLD的超声波风速风向仪原型设计。同时提出了一种处理0°(360°)附近平均风向问题的算法,结合实际运用(风力发电)给出了一种运用气压传感器进行绝对风速测量的理论模型。所设计的超声波风速风向仪对环境监测和风力发电等具有重要的参考应用价值。     

Passive Attack Detection for a Class of Stealthy Intermittent Integrity Attacks

This paper proposes a passive methodology for detecting a class of stealthy intermittent integrity attacks in cyber-physical systems subject to process disturbances and measurement noise. A stealthy intermittent integrity attack strategy is first proposed by modifying a zero-dynamics attack model. The stealthiness of the generated attacks is rigorously investigated under the condition that the adversary does not know precisely the system state values. In order to help detect such attacks, a backward-in-time detection residual is proposed based on an equivalent quantity of the system state change, due to the attack, at a time prior to the attack occurrence time. A key characteristic of this residual is that its magnitude increases every time a new attack occurs. To estimate this unknown residual, an optimal fixed-point smoother is proposed by minimizing a piece-wise linear quadratic cost function with a set of specifically designed weighting matrices. The smoother design guarantees robustness with respect to process disturbances and measurement noise, and is also able to maintain sensitivity as time progresses to intermittent integrity attack by resetting the covariance matrix based on the weighting matrices. The adaptive threshold is designed based on the estimated backward-in-time residual, and the attack detectability analysis is rigorously investigated to characterize quantitatively the class of attacks that can be detected by the proposed methodology. Finally, a simulation example is used to demonstrate the effectiveness of the developed methodology.      

基于互相关的超声非介入测压方法

非介入测压对液压系统的故障诊断与检测具有关键作用,为了提高超声非介入式测压的测量精度,提出了一种基于互相关理论的超声延时计算方法,实验结果与客观实际较为相符,验证了基于互相关理论的超声非介入压力测量技术的可行性,为小管径液压系统的在线压力测量提供了一种新的方法.     

主被动结合的网络测量技术研究

网络测量技术可以有效地帮助网络研究者和管理者更好地理解网络性能和结构。鉴于单一的主动测量或被动测量技术难以实现对网络信息进行精准而有效的测量,提出一种主被动结合的网络测量技术。针对被动测量方式获得的数据采用基于正则表达式的匹配和信息筛选机制提炼有效数据信息;基于这些信息,提出一种周期动态调整的主动发包方式测量目标网络的丢包率,并采用泊松分布的采样方式采集丢包率的测量数据;同时提出一种多路径动态路由测量算法,测量目标网络的路由路径信息。实验结果显示,周期动态调整的主动发包方式与固定周期发包的测量方式相比,可以将链路丢包率降低60%以上;多路径动态路由测量方法与Traceroute和Dijkstra路由寻路探测方式相比,路由探测准确率虽然相差很小,但是平均路由跟踪时间分别减少了大约10%和42%。表明周期动态调整的主动发包方式在网络突发时段可以适当调整发包周期;多路径动态路由测量方法可以有效地减少探测过程中的平均路由跟踪时间。     

一种基于测量构件变迁模型的可重构测量构件一致性检测方法

可重构网络测量系统中,工作流测量构件间迁移的过程是否与规约描述一致,是检验测量构件一致性测试的重要内容。建立了一种基于工作流的构件变迁模型MCTM(Measurement Component Transfer Model),详细阐述了MCTM模型的形式化定义,并基于MCTM模型给出了一种能自动生成遍历所有构件的测试用例生成算法CTBMCTM。实验结果表明,CTBMCTM算法可以准确定位存在问题的构件,与T&GS算法相比,该算法在生成较短测试序列的同时显著缩短了算法的运行时间。     

Sliding-mode observers for nonlinear systems with unknown inputs and measurement noise

This paper deals with the design of observers for Lipschitz nonlinear systems with not only unknown inputs but also measurement noise when the observer matching condition is not satisfied. First, an augmented vector is introduced to construct an augmented system, and an auxiliary output vector is constructed such that the observer matching condition is satisfied and then a high-gain sliding mode observer is considered to get the exact estimates of both the auxiliary outputs and their derivatives in a finite time. Second, for nonlinear system with both unknown inputs and measurement noise, an adaptive robust sliding mode observer is developed to asymptotically estimate the system’s states, and then an unknown input and measurement noise reconstruction method is proposed. Finally, a numerical simulation example is given to illustrate the effectiveness of the proposed methods.     

基于卫星共视法的电网时频测量及同步技术

时间同步对电网的安全和管理有着重要影响,如何准确可靠地同步电网时间值得研究。为此,提出利用卫星共视技术进行电网时间频率的远程校准、进而实现电网时间同步的方法。首先,提出电力系统的四级时间频率溯源体系,明确了电网时间频率溯源关系。其次,研究建立了可以满足卫星共视要求的时间频率计量标准装置,依托标准装置,将卫星共视技术应用于电力系统时间频率远程校准中,利用卡尔曼滤波算法去除干扰,并分析了基于卫星共视技术的电网时间频率同步方法。为定量评价提出方法的有效性,研究了采用提出的方法进行溯源时的时间不确定度和频率不确定度。实验及分析结果表明,提出的方法可以实现时间频率量值的高精度远程传递,从而保障电力系统中的时间同步。     

SDN中基于蚁群优化的网络测量节点选择算法

在软件定义网络（SDN）中,当流传输路径信息获取受限时,现有的测量节点选择算法只能基于网络拓扑的中心性指标进行测量节点选择,存在测量精度较低、测量负载不均衡、运行时间长等问题。将SDN网络中测量节点选择问题抽象为最小顶点覆盖模型,提出一种基于蚁群优化的测量节点选择算法ACO-NS。利用复杂网络的度分布理论缩减状态转移过程中的候选集规模,同时设计一种信息素局部增强-全局挥发机制,增大可行解的信息素浓度,提高算法的准确度和收敛度,并且缩短搜索时间。通过OpenFlow消息在线计算测量节点的负载,采用邻域搜索策略对过载节点进行筛选和替换,以降低过载处理的时间。实验结果表明,与ACO算法相比,该算法的准确度和收敛度分别提高56.7和28.2个百分点,且单位时间内的过载处理开销降低79.8个百分点,具有较高的测量精度。     

基于ARM虚拟化扩展的Android内核动态度量方法

针对现阶段内核级攻击对Android系统完整性的威胁,提出一种基于ARM虚拟化扩展的Android内核动态度量方法DIMDroid。该方法利用ARM架构中的硬件辅助虚拟化技术,提供度量模块与被度量Android系统的隔离,首先通过分析在Android系统运行时影响内核完整性的因素从而得到静态和动态度量对象,其次在度量层对这些度量对象进行语义重构,最后对其进行完整性分析来判断Android内核是否受到攻击;同时通过基于硬件信任链的启动保护和基于内存隔离的运行时防护来保证DIMDroid自身安全。实验结果表明,DIMDroid能够及时发现破环Android内核完整性的rootkit,且该方法的性能损失在可接受范围内。