共查询到18条相似文献,搜索用时 187 毫秒
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在深入地研究P T P时钟同步机理的前提下,仔细分析了时钟偏差产生的原因,并引入了基于最小二乘法的频率补偿算法来校正相对时钟漂移偏差,在搭建的以太网精确时钟同步平台基础上,通过实验验证了该算法的可行性。结果表明,该算法的引人大大地提高了P T P的同步精度。 相似文献
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针对精确时钟协议(PTP)用于半实物网络仿真测试时难以实现精确系统同步的问题,研究从时钟频率漂移对PTP仿真系统同步性能的影响。建立了半实物网络环境下PTP系统模型和时钟模型,解析性推导出单向传输链路中Slaven对主时钟的时延误差估计,得出从时钟模型时延误差表达式具有一致的加权结构,且各误差项都将累积并渗透到传输线路中,影响整个网络的同步精度。基于此,设计多种半实物网络仿真场景进行验证、分析和测试。仿真结果表明:单个从时钟频率漂移对系统同步精度影响甚微,但系统内从时钟均存在漂移或主时钟存在时间抖动的情况下,造成的同步误差是单个从时钟频率漂移时的10倍,会对系统同步精度产生严重的影响,研究成果能为半实物网络测试环境时钟部署策略提供重要参考。 相似文献
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针对大规模多跳传感器网络节点间所存在的同步误差及其累积误差问题,提出了一种基于加权最小二乘法的TPSN-RBS联合时间同步算法.该算法充分利用可监听到的消息,通过加权最小二乘法估计得到节点逻辑时钟的时间偏移和频率偏移的最优解.用Cramér-Rao下界对本算法进行性能分析,同时与TPSN算法进行仿真对比,结果表明:该算法提高了节点间的同步精度,且在节点密集的大规模无线传感器网络中,在保证较低通信量的同时降低了累积误差. 相似文献
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时钟同步在计算机网络领域中应用广泛,是实现许多网络功能的重要基础。软件定义网络(SDN)作为一种新兴的网络架构,其中的确定性时延、同步传输、网络虚拟化等研究都依赖于网络协议进行软件时钟同步。研究如何通过软件方式提升时钟同步精度在SDN系统中有着重要的意义。本文对现有的PTP的时钟同步方式进行了介绍与分析,在此基础上提出了一种改进的时钟加权算法,通过利用网络中上一层多个节点的时钟信息来提升多跳同步的时钟精度。在对典型网络的仿真测试中,每个节点时钟同步精度的提升幅度从1倍到2.6倍不等。网络中的链路越多,算法提升效果越明显。 相似文献
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针对基于PTPV2的网络化测试系统中,时钟频率漂移对链路延迟的影响问题,分析了IEEE1588时间同步过程的原理和拓扑结构图,给出了点对点PTP系统中影响同步性能的机理;在此基础上,通过引入频率变化率补偿因子CRF,获得了链路延时误差计算模型;结果表明,均衡提高主从时钟频率稳定度可改善系统同步精度,合理选择报文传递参数可减少时延计算误差。 相似文献
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提出了一种用于源-目标说话人声门波导数参数转换的、基于勒让德正交分解的声门波导数波形参数提取方法。该方法将声门波导数波形在6维正交勒让德坐标系中的投影构成了描述其形状的特征矢量,并采用基于GMM的概率分类加权转换算法,使每个特征矢量的转换规则可由多个类所对应的规则的线性加权组合得到,可以使转换性能得到较大的提高。在此基础上,又给出了一种基于GMM的声门波导数波形的码本修正算法,以弥补声门波导数波形参数化而损失的含有说话人个性特征的高频送气分量和波纹分量。实验结果表明,本文方法转换性能明显好于基于矢量量化(VQ)的码本映射算法。 相似文献
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R. Caballero-Águila A. Hermoso-Carazo 《International journal of systems science》2017,48(9):1805-1817
This paper studies the distributed fusion estimation problem from multisensor measured outputs perturbed by correlated noises and uncertainties modelled by random parameter matrices. Each sensor transmits its outputs to a local processor over a packet-erasure channel and, consequently, random losses may occur during transmission. Different white sequences of Bernoulli variables are introduced to model the transmission losses. For the estimation, each lost output is replaced by its estimator based on the information received previously, and only the covariances of the processes involved are used, without requiring the signal evolution model. First, a recursive algorithm for the local least-squares filters is derived by using an innovation approach. Then, the cross-correlation matrices between any two local filters is obtained. Finally, the distributed fusion filter weighted by matrices is obtained from the local filters by applying the least-squares criterion. The performance of the estimators and the influence of both sensor uncertainties and transmission losses on the estimation accuracy are analysed in a numerical example. 相似文献
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Maciej Nied?wiecki Author Vitae 《Automatica》2008,44(7):1718-1727
Noncausal estimation algorithms, which involve smoothing, can be used for off-line identification of nonstationary systems. Since smoothing is based on both past and future data, it offers increased accuracy compared to causal (tracking) estimation schemes, incorporating past data only. It is shown that efficient smoothing variants of the popular exponentially weighted least squares and Kalman filter-based parameter trackers can be obtained by means of backward-time filtering of the estimates yielded by both algorithms. When system parameters drift according to the random walk model and the adaptation gain is sufficiently small, the properly tuned two-stage Kalman filtering/smoothing algorithm, derived in the paper, achieves the Cramér-Rao type lower smoothing bound, i.e. it is the optimal noncausal estimation scheme. Under the same circumstances performance of the modified exponentially weighted least-squares algorithm is often only slightly inferior to that of the Kalman filter-based smoother. 相似文献
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N. B. Petrovskaya 《Calcolo》2011,48(1):127-143
Discontinuous weighted least-squares (DWLS) approximation is modification of a weighted least-squares method that requires
a local support (a reconstruction stencil) to approximate a function at a given point. A DWLS method is often employed in
computational problems where a function is approximated on an irregular computational grid. It has recently been revealed
that the method provides inaccurate approximation on irregular grids and conventional weighting of distant points captured
by a reconstruction stencil on an irregular coarse mesh does not improve the accuracy of the approximation. Thus in our paper
we further investigate the impact of distant points on the accuracy of DWLS approximation and design new weight coefficients
for DWLS reconstruction that allow one to obtain more accurate reconstruction results. Our approach is based on a concept
of numerically distant points originally developed in author’s previous works, as a new weight function calculates the distance
between two points in the data space. 相似文献
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节点定位是无线传感器网络中最为关键的一项技术。针对无源定位的问题,提出一种到达时间差(TDOA)和到达信号增益比(GROA)联合定位算法,并且采用飞行机制的萤火虫算法(GSO)来求得最终结果。结合TDOA和GROA定位模型,引入辅助变量将方程伪线性化,然后采用修正两步加权最小二乘算法(TSWLS)来进行求解。并且在不影响收敛速度和精度的前提下,采用带有飞行机制的GSO算法来寻求目标定位的最优解,克服粒子群算法易陷入局部最优的缺点。仿真结果表明,该算法相比较TDOA算法而言,定位精度提高了23 dB,并且具有相对较高和较稳定的定位精度。 相似文献
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相比于传统滑模控制算法,超螺旋控制算法可以对系统的干扰进行精确估计并补偿,因此可以显著提高闭环系统的抗干扰能力.然而,对于采样控制系统,由于采样频率的限制,离散超螺旋控制算法在性能方面受到限制.本文基于齐次系统理论提出了一种改进的离散超螺旋控制算法.通过引入一个可自由调节的分数幂参数,基于齐次系统理论,证明了所提出的改进控制算法可以使得闭环系统具有更高的控制精度.仿真实例验证了理论的正确性. 相似文献
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针对传统时差定位闭式解法在量测噪声较大情况下定位性能不佳的缺点,提出了一种新的时差定位算法。该算法首先在无约束条件下利用加权最小二乘得到目标的初始位置估计值,然后利用最大似然方程对初始位置估计值进行校正,校正后的位置估计值将更加接近最大似然估计。通过对算法的仿真分析,结果表明在量测噪声较大的情况下,算法的定位均方误差要小于经典的Chan算法。 相似文献