实用的MEMS惯性器件外场标定方法

在实际工程应用中,当不具备高精度实验室标定设备时,研究简易可行的MEMS惯性器件外场标定算法非常有必要。在分析MEMS惯性器件误差模型的基础上,提出一种基于椭球模值约束算法的外场标定方法,通过设计合理的实验编排方案和有效的求解算法来实现对误差模型参数的估计。对比实验结果表明:所提出的标定方法简易可行,其误差系数在合理的误差范围内,从而证明了该外场标定方法的有效性。     

An Investigation of Error Sources in Computational Fluid Dynamics Modelling of a Co-current Spray Dryer

The paper is focused on identifying error sources in computational fluid dynamics(CFD) predictions of a spray drying process. Seven groups of drying and atomisation parameters were selected for analysis and 13 simulation trials were performed. The theoretical results were compared with experimental data and sensitivity of the simulation results to the analysed factors was determined. The following parameters affecting the accuracy of CFD spray modelling were found: gas turbulence model, particle dispersion, atomising air, initial parameters of atomisation and heat losses to the environment. A major difference in the errors committed during modelling of spray drying process for fine and coarse sprays was observed.     

六维腕力传感器非线性正解耦方法设计

多维力传感器利用其多个转换单元完成测量加载于其结构上未知负载的作用效果,解耦是其设计的重要组成部分。针对传统静态线性解耦方法的不足,试图将传统线性解耦方程扩展为多项式结构,受其多元高次方式通解形式的启发,构造了一种多项式非线性静态正解耦方程,该方法无需传统线性解耦方法中的曲线拟合、逆解,不依赖以系统是线性为前提,且方程可以扩展成任意结构的多项式。实验结果表明:该方法能降低输出耦合误差。     

Prevention from Soft Errors via Architecture Elasticity

Due to the decreasing threshold voltages, shrinking feature size, as well as the exponential growth of on-chip transistors, modern processors are increasingly vulnerable to soft errors. However, traditional mechanisms of soft error mitigation take actions to deal with soft errors only after they have been detected. Instead of the passive responses, this paper proposes a novel mechanism which proactively prevents from the occurrence of soft errors via architecture elasticity. In the light of a predictive model, we adapt the processor architectures h01istically and dynamically. The predictive model provides the ability to quickly and accurately predict the simulation target across different program execution phases on any architecture configurations by leveraging an artificial neural network model. Experimental results on SPEC CPU 2000 benchmarks show that our method inherently reduces the soft error rate by 33.2% and improves the energy efficiency by 18.3% as compared with the static configuration processor.     

一种基于过零点的时延测量方法

信号传输时间（时延）的测量,是雷达、声纳系统的关键技术之一。本文研究了一种基于过零点的时延测量方法,在建立过零点搜索模型的基础上推导得出时延测量的测量结果表达式;定量分析了高斯白噪声条件下过零点时延测量的测量精度,得到测量误差的理论表达式。仿真与实验表明,过零点时延测量精度与信号频率、过零点数目、信噪比密切相关,当信噪比较高时,其测量精度与经典FFT法相当,而优势在于过零点时延测量的算法简单、计算量小,适用于对实时性要求较高的测量场合。     

一种基于随机GA的提高BP网络泛化能力的方法

LM-BP网络对其初始权值和阈值敏感,泛化能力不强,针对该缺点,采用遗传算法（GA）对其初始权阈值进行优化,在一定程度上能提高LM-BP网络的泛化能力。为进一步扩展GA初始种群的覆盖范围,进一步提高LM—BP网络的泛化能力,采用多次随机产生初始种群多次优化的方法。以伦河孝感段氟化物含量为实例,建立随机GA的LM—BP网络模型,对原始数据进行拟合及测试,结果表明该方法基本能100％拟合,测试误差不超过2．3％。经过对比实验,证明了该方法的有效性。     

LAG WINDOW ESTIMATION OF THE DEGREE OF DIFFERENCING IN FRACTIONALLY INTEGRATED TIME SERIES MODELS

Abstract. In this paper we consider the estimation of the degree of differencing d in the fractionally integrated autoregressive moving-average time series model ARFIMA ( p, d, q ). Using lag window spectral density estimators we develop a regression type estimator of d which is easy to calculate and does not require prior knowledge of p and q. Some large sample properties of the estimator are studied and the performance of the estimator for small samples is investigated using the simulation method for a range of commonly used lag windows. Some practical recommendations on the choice of lag windows and the choice of the window parameters are provided.     

基于机器学习的肺部CT图像非刚性配准误差预测方法

配准误差评估通常由人工完成,耗时费力;常用的Dice测度只关注组织边缘的配准误差,难以评估组织内部配准结果。针对以上问题,提出一种基于机器学习的肺部CT图像非刚性配准误差预测方法(PREML)。该方法首先构建形变场统计特征、形变场物理保真度特征和图像相似性特征三类特征,然后通过池化方法扩充特征数量,最后使用随机森林回归方法预测非刚性配准误差,并且使用自适应随机扰动方法模拟肺部配准误差空间分布,进一步提升形变场统计特征的配准误差表征能力。在三个肺部CT图像数据集上进行训练与测试,其配准误差预测结果与金标准之间的平均绝对差异为1.245±2.500 mm,预测性能优于基线方法。结果表明,PREML方法具有预测精度高、鲁棒性强的特点,可提升配准算法在临床应用的有效性和安全性。     

基于匹配策略融合的低误差快速图像拼接算法

针对目前多数拼接算法正确匹配率低、耗时及误差大的问题,提出了基于匹配策略融合的改进图像拼接算法。该算法首先仅在图像的重合区域提取SIFT特征点,并计算SURF特征描述符;其次,融合改进的最近邻比次近邻、双向交叉检查及匹配差值的阈值化3种匹配策略,结合坐标约束及RANSAC算法完成特征匹配;最后,提出利用配准参数计算任意图像到参考图像坐标空间的投影变换模型的方法,并利用多线程技术将所有图像投影至参考坐标系,经过亮度校正、加权融合后合成全景图。实验结果表明,提出的拼接算法正确匹配率提高了10~20%,拼接总耗时约为传统逐帧扩大式拼接算法的1/3,且累计误差大大降低,拼接图像畸变小。