基于信息论方法的分类数据相似性度量

两实例的距离或相似性度量在数据挖掘和机器学习中扮演着重要的角色。常用的距离度量方法主要适用于数值数据,针对分类数据,本文提出一种数据驱动的相似性度量方法。该方法利用属性值与类标签的信息,将属性值的类条件概率结合信息论来度量分类数据的相似性。为了与已提出的相似性度量方法作比较,把各度量方法与k最近邻算法结合,对多个分类数据集进行分类,通过十折交叉验证比较结果的错误率。实验表明该度量结合k最近邻方法使分类具有较低的错误率。     

ICP框架下基于表面间平均体积测度的深度像配准

提出一种利用深度像重叠区域间的空间体积作为误差度量的精确配准算法.通过寻找2幅深度像重叠区域内的有效三角形对,并将这些三角形对所夹的三维空间作为误差测度来指导深度像的配准;然后将对应三角形的质心作为对应点对,估计出新的空间位置转换关系.实验结果表明:该算法具有较高的配准精度,收敛速度快并且具有一定的抗噪声能力.     

离散系统快速递推仿真算法及其在柔性制造系统中的应用

本文对具有中央服务台形式,队列均为FCFS服务规则,不同顾客类不同路径和不同服务速率的闭网络进行了研究。文中引入多变量排队网络理论建立了一类离散事件系统仿真模型,提出一快速递推算法,该算法计算量小并应用于实际问题。     

Residual bounds for discrete-time Lyapunov equations

This paper presents a novel backward error criterion together with a sensitivity measure for assessing the solution accuracy of discrete-time Lyapunov equations. The conventional method involves standard perturbation and sensitivity results for certain associated linear systems. Such an approach, however, ignores the structure of the linear system and is often inconclusive. The method considered in this paper takes full account of the underlying structure of the problem and provides a meaningful measure of accuracy     

A self-calibration method for error of photoelectric encoder based on gyro in rotational inertial navigation system

As a precision goniometer, photoelectric encoder plays an important role in rotational inertial navigation system (RINS). The encoder is used to measure the rotate angle of rotating mechanism for attitude calculation and feedback of motor control. However, the experiment shows that there are position-related errors in the encoder output, so calibration is necessary in high precision applications. This paper presents a calibration method designed by the characteristics of encoder errors and the structure of a tri-axis RINS. In RINS, the gyro sensitive axis can be coincided with the motor axis by gimbals rotation, and then the gyro and the photoelectric encoder measure the same angle, so the error can be calculated as the difference between the encoder output and the integral of gyro output. The error will be analyzed through Fourier method, then the error will be fitted by least squares method and a harmonic model will be established. The verification experiments demonstrate that the angle measurement error is reduced from ± 40″ to ± 2″, and the attitude output error drops 75″. The calibration method is proved to be experimentally effective.

     

Selecting the optimal focus measure for autofocusing anddepth-from-focus

A method is described for selecting the optimal focus measure with respect to gray-level noise from a given set of focus measures in passive autofocusing and depth-from-focus applications. The method is based on two new metrics that have been defined for estimating the noise-sensitivity of different focus measures. The first metric-the autofocusing uncertainty measure (AUM)-is useful in understanding the relation between gray-level noise and the resulting error in lens position for autofocusing. The second metric-autofocusing root-mean-square error (ARMS error)-is an improved metric closely related to AUM. AUM and ARMS error metrics are based on a theoretical noise sensitivity analysis of focus measures, and they are related by a monotonic expression. The theoretical results are validated by actual and simulation experiments. For a given camera, the optimally accurate focus measure may change from one object to the other depending on their focused images. Therefore, selecting the optimal focus measure from a given set involves computing all focus measures in the set     

Monte Carlo methods in fuzzy linear regression

We apply our new fuzzy Monte Carlo method to a certain fuzzy linear regression problem to estimate the best solution. The best solution is a vector of triangular fuzzy numbers, for the fuzzy coefficients in the model, which minimizes one of two error measures. We use a quasi-random number generator to produce random sequences of these fuzzy vectors which uniformly fill the search space. We consider an example problem and show this Monte Carlo method obtains the best solution for one error measure and is approximately best for the other error measure.     

Confined‐error‐diffusion algorithm for flat‐panel display

Abstract— The reduction of a structural pattern at specific gray levels caused by digital halftone methods is the subject of this paper. This problem is more severe in some flat‐panel displays because their black levels typically are brighter than other display blocks. A patented halftone algorithm, confined error diffusion (CED), that confines the error‐carry within the dither mask is described and extended. First, the CED algorithm that dynamically applies random error diffusion or the ordered‐dither method, depending upon image content, is described in detail. Finally, we propose an advanced CED algorithm for improving the gradation characteristics of the CED algorithm. The performance of the proposed algorithms is compared to the experimental results for natural test images. In order to verify the halftone quality, a structural similarity measure for color images by taking into account the interrelation between color channels is proposed, and the results based on the proposed method, the color similarity measure method, is given.     

数控机床的螺距误差检测及补偿

本文介绍了数控机床的螺距误差补偿原理和基于激光干涉仪的螺距误差测量系统,并且讨论了在螺距误差测量中所出现的问题和解决方案,最后介绍了螺距误差补偿的适用范围。     

Variable structure control of a class of uncertain systems

This brief paper proposes a method for tuning the parameters of a variable structure controller. The approach presented extracts the error at the output of the controller and applies a nonlinear tuning law using this error measure. The adaptation mechanism drives the state tracking error vector to the sliding hypersurface and maintains the sliding mode. In the simulations, the approach presented has been tested on the control of Duffing oscillator and the analytical claims have been justified under the existence of measurement noise, uncertainty and large nonzero initial errors.     

Combined state of charge estimator for electric vehicle battery pack

Ah counting is not a satisfactory method for the estimation of the state of charge (SOC) of a battery, as the initial SOC and coulomb efficiency are difficult to measure. To address this issue, an equivalent coulomb efficiency is defined and a new SOC estimation method, denoted as “KalmanAh”, is proposed. This method uses the Kalman filtering method to correct for the initial value used in the Ah counting method. A Ni/MH battery test, consisting of 8.08 continuous federal urban driving schedule (FUDS) cycles, is carried out to verify the method. The SOC estimation error is 2.5% when compared with the real SOC obtained from a discharge test. This compares favorably with an estimation error of 11.4% when using Ah counting.     

飞机刹车半实物仿真机轮速度信号模拟装置的设计

受器件老化、随机噪声等因素影响,晶振频率变化较复杂。以GPS秒脉冲作为测量标准,构建了晶振频率随时间变化的测量系统,通过对测量数据进行一元回归统计处理,分离出了晶振实际频率与其标称频率的相对偏差及晶振的各种随机误差,并分析了这两种误差对晶振准确度及稳定度的影响。该方法可为频率源误差测量分析提供借鉴作用。     

一种八位置数字磁强计系统误差标定方法

由于数字磁强计本身制作和生产安装的精度差异,产生了数字磁强计的系统误差.通过对数字磁强计的系统误差进行详细分析和理论计算,建立了误差方程,并提出了一种简单有效的系统误差补偿方法--八位置标定方法,并对此方法进行了实验验证.实验结果表明:该方法可以较好地补偿数字磁强计的系统误差,提高航向测量精度.     

触针式轮廓仪弹性测量杆的设计

针对传统的触针式轮廓仪杠杆式测量杆的转动支点由于滚动体跳动容易引入随机误差的问题,提出并设计了一种基于弹性变形理论的轮廓仪测量杆。利用高精度电容传感器测量测量杆的弹性变形量,然后利用悬臂梁的挠曲线公式求出触针针尖的位移量从而得到待测面的微观不平度信息,消除了杠杆式测量杆引入的随机误差,进一步提高了粗糙度测量精度。     

直线度的高精度测量

提出采用两个测头加一个自准直仪的测量装置进行直线度的测量,误差分离技术采用“自然延拓”的方法从测得的差分值中重构工件轮廓,这种频域方法适应光滑和粗糙表面的测量,并允许采用大的测头间距。通过采用该测量系统和误差分离技术就可以高精度测量直线度。仿真结果表明该测量方法具有很高的重构精度,并采用该方法对自制的大理石超精密机床的直线度进行了检测。     

弹载地磁测量系统的抗干扰设计

为了消除弹载地磁测量系统所受的矿山、电磁、金属等干扰,本文设计了充磁电路,消除强磁场对磁阻传感器的干扰;设计了滤波电路及合理的布线,消除高频干扰信号;再提出了误差识别补偿及看门狗设置算法,补偿了软硬磁干扰、零位误差、正交误差。转台试验与数据分析表明:各组合方法的采用,减少了干扰误差使姿态角测量精度达到1°以内,具有一定的工程价值。     

Improve the robot calibration accuracy using a dynamic online fuzzy error mapping system.

Traditional robot calibration implements model and modeless methods. The compensation of position error in modeless method is to move the end-effector of robot to the target position in the workspace, and to find the position error of that target position by using a bilinear interpolation method based on the neighboring 4-point's errors around the target position. A camera or other measurement devices can be utilized to find or measure this position error, and compensate this error with the interpolation result. This paper provides a novel fuzzy interpolation method to improve the compensation accuracy obtained by using a bilinear interpolation method. A dynamic online fuzzy inference system is implemented to meet the needs of fast real-time control system and calibration environment. The simulated results show that the compensation accuracy can be greatly improved by using this fuzzy interpolation method compared with the bilinear interpolation method.     

溶解氧预报模型及误差校正

针对污水处理过程中，由于溶氧仪表面生成生物氧化膜，产生“钝化”现象，造成了溶氧值测量误差，以至影响生产；又因为需要频繁地清理溶氧仪，造成了人力、物力、财力的浪费，降低生产效率等问题，利用人工神经元网络建立了溶解氧预报模型。基于此模型，给出了传感器误差校正的具体方法。当误差超出给定界限时，给出故障报警。现场应用表明，该方法在一定程度上延长了溶氧仪清理的间隔时间，节约了生产成本，提高了生产效率，收到了较好的预报效果。     

基于三角函数的正交矩函数的误差预测与分析

提取图像中旋转不变特征是图像处理和模式识别中重要的应用。在极坐标下的正交矩函数则是提取这种特征信息的主要方法。正交矩函数在图像分解和重建过程中的误差是衡量其特征提取精确度的标准。为了提高正交矩函数在图像重建中的性能,提出了一种新的基于三角函数的正交矩函数和一种基于函数误差分析的新的衡量方法,并分别应用新的衡量方法和传统的在大量图像中进行重建误差统计的方法对新的正交矩函数以及另外两种在特征提取方面表现最好的正交矩函数进行了比较。实验结果验证了新的衡量方法的有效性并得到了新的正交矩函数的重建效果更好的结论。     

基于FPGA的伺服驱动高精度位置反馈研究

伺服驱动向CNC反馈进给轴的位置量时,转换存在量化误差,如果处理不当.持续多个周期转换就存在积累误差.文中提出一种以CNC脉冲当量之半为量尺的方法,以减法代替除法求得反馈脉冲量和误差,保证每一个周期的误差小于一个脉冲当量.同时在每一次计算电机编码器测得的位置量时加入上次误差的方向和大小,从而保证了积累误差小于一个脉冲当量,实现了伺服驱动向CNC的高精度位置反馈.