一种基于压缩感知的运动目标检测技术

运动目标检测是计算机视觉、图像处理等相关领域的研究热点，其核心就是对视频图像中的每一帧图像进行相应的研究和处理。本文主要研究思路是从压缩感知技术采样信号的角度出发，将每一帧的二维图像压缩采样成具有少量信息的一维信号，再通过信号重构用少量数据量将图像重构出来，最后通过目标检测技术对每一帧的图像进行运动目标提取。仿真实验表明该方法是可行和有效的，同时可以大大减少目标检测中所记录的数据量，解决海量数据的存储与传输问题。     

步长自适应的测量矩阵迭代优化方法

在压缩感知中，降低传感矩阵的列相干性可以提高重构精度。因为稀疏字典一般是固定的，所以目前主要通过优化测量矩阵来间接降低传感矩阵列相干性。提出一种改进的测量矩阵优化算法，使用梯度下降法更新测量矩阵并结合Barzilai-Borwen方法以及Armijo准则，使步长能够在迭代中自适应调整并保证算法收敛性。仿真实验表明，所提出的方法具有更快的收敛速度并且能够得到更优的测量矩阵。     

基于改进关联规则算法的警情数据分析

针对传统Apriori算法挖掘警情数据的缺点，提出一种改进的Apriori算法。该算法首先在关联规则发现阶段引入权值参数，设计支持度阈值函数，以挖掘不常发生的重大案情发生规律；然后提出一种压缩矩阵优化算法，将数据压缩存储在只有0或1的矩阵中，并用2个数组来记录矩阵中每一行及每一列1的总数，可多次压缩矩阵，提升挖掘效率；最后将改进的算法用于实际的警情数据挖掘分析，给出关联规则挖掘结果。实验表明，改进算法不仅执行效率较传统算法有所提升，且针对警情数据的挖掘结果准确性也有所提高。     

Reduced-order multiple observer for Takagi–Sugeno systems with unknown inputs

The paper discusses a niche area problem — the design of reduced-order multiple observers which can achieve the finite-time state reconstruction for Takagi–Sugeno multiple models with unknown inputs. The new reduced-order multiple observer obtained in this paper is only the second ever designed, the author of this paper continuing his work started one year ago with the introduction of the reduced-order multiple observer concept. The obtaining of the new reduced-order multiple observer is achieved by combining two classical reduced-order observers for linear time-invariant multivariable systems with unknown inputs and a full-order multiple observer for Takagi–Sugeno systems. The main innovative idea behind the design of the reduced-order multiple observer for Takagi–Sugeno systems described by the multiple models is the split of the multiple model into two subsystems: an unknown-input-free subsystem and an unknown-input-depending subsystem. The unknown-input-free subsystem is brought to the form of a standard multiple model and, in this situation, any algorithm to design full-order multiple observers can be used in the design of reduced-order multiple observers. The steps of the design procedure have been summarized and software implemented; then, the validation of the suggested algorithm has been done for two concrete cases associated to the motion of an aircraft during its landing     

基于双应力加速寿命试验的关节轴承寿命预测与可靠性分析

自润滑关节轴承寿命主要是由衬垫的磨损性能决定的,但衬垫的磨损一般是非线性的,使得寿命难以预测。采用同时改变载荷和摆频2种应力的方法进行加速寿命试验,建立以pv值、磨损量退化数据为输入参数,寿命值为输出参数的灰色神经网络预测模型。经验证该预测模型对关节轴承寿命预测的最大误差仅为7.33%,平均误差仅为3.892%。对不同加速应力下自润滑关节轴承可靠性进行评估,结果表明,关节轴承的可靠性在L_(10)(可靠度为90%时的寿命)之前下降趋势缓慢,然后迅速下降,pv值越大可靠性下降越迅速;随着pv值的增大,关节轴承寿命近似呈指数下降,经验证可用逆幂率加速模型反映二者关系。     

Perspective of mixed matrix membranes for carbon capture

Polymeric membrane-based gas separation has found wide applications in industry, such as carbon capture, hydrogen recovery, natural gas sweetening, as well as oxygen enrichment. Commercial gas separation membranes are required to have high gas permeability and selectivity, while being cost-effective to process. Mixed matrix membranes (MMMs) have a composite structure that consists of polymers and fillers, therefore featuring the advantages of both materials. Much effort has been made to improve the gas separation performance of MMMs as well as general membrane properties, such as mechanical strength and thermal stability. This perspective describes potential use of MMMs for carbon capture applications, explores their limitations in fabrication and methods to overcome them, and addresses their performance under industry gas conditions.     

基于计算机的镀液温度智能控制系统设计

为提高镀液温度的控制精度,以计算机为平台设计了一种镀液温度智能控制系统。设计了一种模糊PID温度控制器,可实现PID控制器参数的实时在线调整。利用动态矩阵,统计过去和当前时刻的偏差,预测未来偏差,进而得到最佳输入。最后,进行了实验研究。结果表明:镀液温度智能控制系统的收敛速率快、精度高、稳定性好,能满足电镀行业的需求,具有广阔的应用前景。     

Robust predictive extended state observer for a class of nonlinear systems with time-varying input delay

ABSTRACT

This paper deals with asymptotic stabilisation of a class of nonlinear input-delayed systems via dynamic output feedback in the presence of disturbances. The proposed strategy has the structure of an observer-based control law, in which the observer estimates and predicts both the plant state and the external disturbance. A nominal delay value is assumed to be known and stability conditions in terms of linear matrix inequalities are derived for fast-varying delay uncertainties. Asymptotic stability is achieved if the disturbance or the time delay is constant. The controller design problem is also addressed and a numerical example with an unstable system is provided to illustrate the usefulness of the proposed strategy.     

Estimating epidemic coupling between populations from the time to invasion

Identifying the mechanisms by which diseases spread among populations is important for understanding and forecasting patterns of epidemics and pandemics. Estimating transmission coupling among populations is challenging because transmission events are difficult to observe in practice, and connectivity among populations is often obscured by local disease dynamics. We consider the common situation in which an epidemic is seeded in one population and later spreads to a second population. We present a method for estimating transmission coupling between the two populations, assuming they can be modelled as susceptible–infected–removed (SIR) systems. We show that the strength of coupling between the two populations can be estimated from the time taken for the disease to invade the second population. Confidence in the estimate is low if only a single invasion event has been observed, but is substantially improved if numerous independent invasion events are observed. Our analysis of this simplest, idealized scenario represents a first step toward developing and verifying methods for estimating epidemic coupling among populations in an ever-more-connected global human population.