Application of generally weighted moving average method to tracking signal state space model

In predicting time series, if a trend includes a structural break, then a state space model can be applied to revise the predictive method. Some scholars suggest that restricted damped trend models yield excellent prediction results by automatically revising unforeseen structural break factors in the prediction process. Restricted damped trend models add a smoothed error statistic to a local‐level model and use the exponentially weighted moving average (EWMA) method to make corrections. This paper applies the generally weighted moving average (GWMA) concept and method to a restricted damped trend model that changes the smoothed error statistic from the EWMA form to the GWMA form and adds the correction parameter λ, which distinguishes three situations , , and . The original restricted damped trend model applies only to , enabling the model to capture situations in which and increases its generality. This paper also compares the effect of various parameter values on the predictive model and finds the range of parameter settings that optimize the model.     

遗传程序设计分析股价移动平均及中长期走势*

将遗传程序设计应用到股票价格分析,在股票市场各种因素相互作用与影响很难厘清的情况下,只从个别因素（价格）入手,测试对单一因素预测所能达到的效果;提出了两种预测方法：对不同尺度的股票移动平均线进行预测和对股票价格数据进行平滑预处理之后所进行的中长期预测。通过遗传程序设计算法,寻找前几个时间单位的股票价格对本期股票价格影响的经验公式,以期反映价格变动的规律。计算机实验模拟表明,该方法对于平均线的预测和中长期预测有较好的效果。     

Robustness of ISS systems to inputs with limited moving average: Application to spacecraft formations

We provide a theoretical framework that fits realistic challenges related to spacecraft formation with disturbances. We show that the input‐to‐state stability of such systems guarantees some robustness with respect to a class of signals with bounded average‐energy, which encompasses the typical disturbances acting on spacecraft formations. Solutions are shown to converge to the desired formation, up to an offset, which is somewhat proportional to the considered moving average of disturbances. In the presence of fast peaking perturbations, the approach provides a tighter evaluation of the disturbances' influence, which allows for the use of more parsimonious control gains. Copyright © 2015 John Wiley & Sons, Ltd.     

滑动平均和改进权重函数的快速非局部平均图像去噪算法

非局部平均算法(NL-means)是一种有效的高斯噪声去除方法,由于其实现时效率低下,很难应用到实际中。针对非局部平均算法的低效率问题,提出一种快速的非局部平均去噪算法(FNLM)。首先,为了实现对算法的加速,采用滑动平均和权重对称技术。其次,算法在加速时一般会影响到去噪效果,为了使算法加速的同时保证去噪效果,提出一种改进的权重计算函数。最后,对新算法进行了一定的实验分析,实验结果显示提出的快速算法FNLM与原始的非局部平均算法相比,效率得到了很大提升,与其他的经典算法相比,在效率和效果上都非常有竞争力。     

A new exponentially weighted moving average control chart for monitoring the coefficient of variation

Monitoring coefficient of variation is one of the successful approaches to Statistical Process Control (SPC) when the process mean and standard deviation are not constants. This paper presents a modified Exponentially Weighted Moving Average (EWMA) chart in order to further enhance the sensitivity of the EWMA control chart proposed by Castagliola et al. (2011). Tables are provided for the statistical properties of the new chart. Some numerical results and comparisons are given and show that the new chart has an average run length performance that is superior to some other competing procedures. A real data example from manufacturing shows that it performs quite well in applications.     

非线性时间序列建模的混合自回归滑动平均模型

提出了一类用于非线性时间序列建模的混合自回归滑动平均模型(MARMA).该模型是由K个平稳或非平稳的ARMA分量经过混合得到的.讨论了MARMA模型的平稳性条件和自相关函数.给出了MARMA模型参数估计的期望极大化(expectation maximization)算法.运用贝叶斯信息准则(Bayes information criterion)来选择该模型.MARMA模型分布形式富于变化的特征使得它能够对具有多峰分布以及条件异方差的序列进行建模.通过两个实例验证了该模型,并和其他模型进行比较,结果表明MARMA模型能够更好地描述这些数据的特征.     

自回归滑动平均建模中观测噪声方差估计的新方法

目前的自回归滑动平均(ARMA)建模方法由于只利用了观测数据的高阶自协方差构建Yule-Walker方程,而没有利用观测数据的低阶自协方差信息,导致观测噪声方差的估计精度不高,并且在自回归(AR)阶次p小于或等于滑动平均(MA)阶次q时无法估计出观测噪声方差.为此,本文提出了一种单独估计观测噪声方差的新方法,即先将ARMA模型近似为一高阶AR模型,再构建从观测数据1阶自协方差开始的Yule-Walker方程.由于充分利用了观测数据的统计信息,有利于提高观测噪声方差的估计精度,为后续的AR和MA参数估计精度的提高奠定了基础,也解决了p小于或等于q时观测噪声方差无法估计的问题,仿真和实验结果验证了该方法的有效性.     

Using geometric Poisson exponentially weighted moving average control schemes in a compound Poisson production environment

In this study, the variable to be controlled over time is the number of defects. Meanwhile, the underlying distribution of defects is the geometric Poisson distribution, a Poisson distribution compounded by a geometric distribution. For production process control, the exponentially weighted moving average (EWMA) control scheme based on the geometric Poisson process is addressed. Performance of the EWMA control scheme is assessed not only by both in-control and out-of-control average run lengths (ARL’s), but also by higher moments of the run length (RL) distribution. The run length distribution properties can be obtained from the probability transition matrix and implemented using the computer programs developed in this study. With proper ARL and variance of RL selected, any small shift in mean can be detected via the geometric Poisson EWMA control scheme.     

Abnormal visual event detection based on multi-instance learning and autoregressive integrated moving average model in edge-based Smart City surveillance

The abnormal visual event detection is an important subject in Smart City surveillance where a lot of data can be processed locally in edge computing environment. Real-time and detection effectiveness are critical in such an edge environment. In this paper, we propose an abnormal event detection approach based on multi-instance learning and autoregressive integrated moving average model for video surveillance of crowded scenes in urban public places, focusing on real-time and detection effectiveness. We propose an unsupervised method for abnormal event detection by combining multi-instance visual feature selection and the autoregressive integrated moving average model. In the proposed method, each video clip is modeled as a visual feature bag containing several subvideo clips, each of which is regarded as an instance. The time-transform characteristics of the optical flow characteristics within each subvideo clip are considered as a visual feature instance, and time-series modeling is carried out for multiple visual feature instances related to all subvideo clips in a surveillance video clip. The abnormal events in each surveillance video clip are detected using the multi-instance fusion method. This approach is verified on publically available urban surveillance video datasets and compared with state-of-the-art alternatives. Experimental results demonstrate that the proposed method has better abnormal event detection performance for crowded scene of urban public places with an edge environment.     

An average optimal control approach to the set stabilization problem for boolean control networks

This paper addresses the set stabilization problem for deterministic Boolean control networks (BCNs). An optimal control approach is investigated to solve the problems by using the semi‐tensor product of matrices, where a policy iteration algorithm for the set stabilization problem is deduced. Finally, the intervention problem of a cAMP receptor protein is addressed in the framework of the set stabilization problem. The problem is solved to validate the effectiveness of the proposed policy iteration approach for a practical application.     

估计MA参数的多维强Gevers-Wouters算法及其在构造ARMA新息模型中的应用

提出了用多维Gevers-Wouters（G－W）算法得到稳定的滑动平均（MA）过程的一个频域充分条件,并给出了在构造ARMA新息模型中的应用,给出了保证ARMA新息模型的MA多项式矩阵稳定的一个时域充分条件,仿真结果表明,多维G－V算法具有快速收敛的性质。     

Packet-level traffic control for the Internet: a framework and its experimental validation

This paper presents a theoretical framework, which can be the basis for traffic control and resource management mechanisms, that provide QoS with quantitative guarantees in the Internet. The starting point is a fairly general traffic shaping algorithm for effective rate enforcement which is based on a packet spacing law. Multiplexing several independent shaped streams results in a tight upper bound to the queue-length distribution at the multiplexer. The algorithm effectively works with any kind of input traffic (non-stationary, non-Markovian, heterogeneous, long-range dependent (LRD), etc.). Based on the definition of shaped streams, we devise mechanisms for aggregating, splitting and policing such streams without affecting the queuing performance at subsequent network nodes. Also, a calculus for end-to-end QoS in this framework is presented. The theoretical statements are supported by simulation and experimental results on a network testbed. Since the enforced effective rate features the convenient additivity property , it can be handily used for many traffic control and accounting functions, like policing, admission control, bandwidth allocation and charging.     

轧钢生产过程产品质量控制方法与应用研究

针对轧钢生产线控制难度大的问题,提出了一种有效的方法来建立轧钢生产过程模糊质量模型。通过对系统反应机理的分析,确定出模糊质量模型的规则总数和前件参数,利用最小二乘法求得模型的后件参数。仿真分析验证了建模方法的有效性,为产品设计和工艺设计提供了新的方便的途径。     

ARMA模型法生成粉红噪声的研究

针对现有粉红噪声的生成方法所存在的计算过程复杂,与理想粉红噪声相比偏差较大等问题,本文提出了一种利用自回归滑动平均(ARMA)模型法生成粉红噪声的新方法。首先,构造一个待定系数的ARMA模型,并通过Z变换和功率谱估计的公式进行推导;其次,利用已知的粉红噪声模拟滤波器的传递函数H(s)和双线性Z变换法推导出IIR数字滤波器的传递函数H(z),进而得到粉红噪声的ARMA模型;最后,利用MATLAB对生成的粉红噪声进行功率谱估计并与理想的粉红噪声进行对比。由MATLAB仿真结果可知,利用该方法生成的粉红噪声与理想的粉红噪声拟合度更高,完全符合粉红噪声的各项性能要求。     

Model-based control of a simulated moving bed chromatographic process for the separation of fructose and glucose

Chromatographic separations are an expanding technology for the separation of high value products, particularly in the area of pharmaceutics, food, and fine chemicals. The simulated moving bed (SMB) process as a continuous chromatographic separation process is an interesting alternative to conventional batch chromatography, and gained more and more impact recently. The SMB process is realized by connecting several single chromatographic columns in series. A countercurrent movement of the bed is approximated by a cyclic switching of the inlet and outlet ports in the direction of the fluid stream. Because of its complex dynamics, the optimal operation and automatic control of SMB processes is a challenging task. This paper presents the design of a model-based optimization and control scheme for SMB chromatographic separation processes and its application to the separation of fructose and glucose. We propose a two-layer control architecture where the optimal operating trajectory is calculated off-line by dynamic optimization based on a rigorous process model. The parameters of the model are adapted based on online measurements. The low-level control task is to keep the process on the optimal trajectory despite disturbances and plant/model mismatch. Here identification models based on simulation data of the rigorous process model along the optimal trajectory are combined with a suitable local controller. The efficiency of the trajectory control algorithm is shown in a simulation study for the separation of fructose and glucose on an 8-column SMB plant.     

A sub-circuit model of a microbolometer IR detector and its experimental validation

In this paper, we present a generic circuit model of microbolometer Infrared detector that can be used to simulate the electrical and thermal performance of microbolometers using SPICE like circuit simulator. Using this model, we have studied the effects of various parameters on the microbolometer performance by simulations in PSPICE for its verification. We have validated the model with the performance of our titanium microbolometers being developed at our laboratory. We have tuned the model parameters for these microbolometers and have shown that the simulated performance agrees with the measured performance reasonably well with the variety of measurement condition. The validated model has been used to fine tune the design of our titanium microbolometers as it allows us to monitor some internal parameters also that are not easy to measure in practical devices, like instantaneous temperature of microbolometer for a varying IR intensity falling on it. The proposed model is generic and therefore, using similar procedure it may be used for other types of microbolometers also like amorphous-Si based, vanadium oxide based etc., once it is validated for that.     

A model validation approach to texture recognition and inpainting

A new approach to texture recognition and inpainting problems is proposed. The approach is based on the robust model validation and state estimation techniques. The proposed solutions require the modeling of textures by using uncertain dynamical systems. We propose a new modeling method which is efficient in terms of computational and memory requirements. The main aspects of the modeling method include system identification and order reduction of marginally stable uncertain discrete-time systems. To demonstrate the results, both static-image textures and video textures (also known as dynamic textures) are considered.     

读请求的空间与时间特征建模

为了改善并行应用程序和并行文件系统的I/O性能，对读请求的空间与时间特征进行建模。使用自相关函数分析和Haar小波变换来自动识别自回归、集成的移动平均的模型结构，通过该模型来预测读请求的时间特征；使用马尔可夫模型对读请求的空间特征进行建模、预测。该模型可以将自回归、集成的移动平均时间预测模型与马尔可夫空间预测模型结合，并自适应地预测什么时间、取哪些数据块、取多少数据块。     

汽包水位温压补偿控制系统研究和应用

对汽包双室平衡容器水位温压补偿控制系统进行了探讨和研究,根据温压补偿模型,分析了P L C系统难以独立实现的原因以及查表法的缺陷,提出了P L C系统与上位机系统相结合的水位温压实时连续补偿的综合控制策略,提出并分析比较了三种体系结构及其实现原理和技术,工程应用结果表明该控制系统提高了水位控制的实时性、稳定性、准确性和安全性。     

基于LMI的约束系统H∞控制及其滚动优化实现

在LMI优化框架下,讨论有时域硬约束线性系统的H_∞控制问题.首先提出了一种基于LMI优化的状态反馈方法,并给出了闭环系统保证H_∞性能和满足时域硬约束的条件.在此基础上,融合预测控制的滚动优化原理讨论了一种滚动时域H_∞性能控制方法.通过对H_∞性能指标γ的在线最小化,闭环系统能实时协调控制性能要求和硬约束,并充分利用有限的控制能力提高控制性能.