带未知时变噪声的非线性系统卡尔曼滤波器算法研究

针对带有未知时变噪声的非线性系统的状态估计问题，详细研究了基于有限差分和未知时变噪声估计器的扩展Kalman滤波器算法。仿真结果发现，该算法具有滤波精度高，数值计算稳定等优点，但系统状态估计对初始误差较敏感。     

聚酯缩聚反应过程分子量分布的优化控制

针对带有未知时变噪声的非线性系统的状态估计问题，详细研究了基于有限差分和未知时变噪声估计器的扩展Kalman滤波器算法。仿真结果发现，该算法具有滤波精度高，数值计算稳定等优点，但系统状态估计对初始误差较敏感。     

基于增强的粒子滤波算法的医学图像动态轮廓跟踪新方法

关于医学图像的研究,感兴趣区的运动估计和跟踪是一个深受关注的领域。鉴于医学图像质量低、噪声大的普遍特点,从状态变量的非线性、非高斯分布前提出发,利用粒子滤波技术解决该类跟踪问题是一种具有挑战性的技术:由于经典粒子滤波器的权值计算,尤其是重要密度函数的构造方法严重影响了粒子滤波器的性能,本文提出了重要改进。针对用粒子滤波方法估计动态轮廓线这一特殊应用,构造了具有特色的似然和先验概率密度算法。结合客观的理论评价标准和大量比较试验,该方法为精确估计动态轮廓线提供了较好的解决对策。     

基于增强的粒子滤波算法的医学图像动态轮廓跟踪新方法

关于医学图像的研究，感兴趣区的运动估计和跟踪是一个深受关注的领域。鉴于医学图像质量低、噪声大的普遍特点，从状态变量的非线性、非高斯分布前提出发，利用粒子滤波技术解决该类跟踪问题是一种具有挑战性的技术：由于经典粒子滤波器的权值计算，尤其是重要密度函数的构造方法严重影响了粒子滤波器的性能，本提出了重要改进。针对用粒子滤波方法估计动态轮廓线这一特殊应用，构造了具有特色的似然和先验概率密度算法。结合客观的理论评价标准和大量比较试验，该方法为精确估计动态轮廓线提供了较好的解决对策。     

基于Cauchy鲁棒函数的UKF改进算法

对于大多数实际系统,其噪声统计特性未知,不敏卡尔曼滤波(unscented Kalman filter,UKF)算法对噪声信息不准的鲁棒性较差,导致滤波精度急剧下降,甚至滤波发散。借助鲁棒数据校正的思想,提出了一种基于Cauchy鲁棒函数的UKF改进算法。以UKF的测量先验值与其实际值的残差作为基准,采用联合权函数对噪声估计值进行实时修正,从而提高了UKF算法的精度。通过两个实例的仿真,验证该算法的有效性。     

基于观测噪声实时估计的卡尔曼滤波车窗防夹系统研究

卡尔曼滤波可有效解决电机参数变化对车窗防夹控制性能的影响。然而,由于观测噪声往往是未知并且随时间变化,这对基于卡尔曼滤波的车窗防夹控制系统性能有着重要的影响。本文利用小波变换可以对信号和噪声进行分离的特性,提出了一种基于观测噪声实时估计的电动车窗防夹控制方法。在Matlab环境下进行了建模和仿真,结果表明本文算法可以有效实现对观测噪声的实时估计,在不同的噪声条件下都达到了较好的控制效果。     

自适应噪声抵消在抑制高频电刀对心电监护仪干扰中的应用研究

本文讨论了如何利用自适应噪声抵消去除高频电刀工作时对心电监护波形的干扰.本课题基于高频电刀干扰成分的研究,采用了滤波系统去除高频成分的干扰;利用了自适应噪声抵消系统实现对噪声的跟踪、去除.并利用 MATLAB语言对抑制措施进行动态仿真,验证了抑制措施的可行性.     

基于UKF的参数和状态联合估计

对于因模型参数失配造成的非线性系统状态估计不准确现象,采用基于不敏卡尔曼滤波（UKF）的参数和状态联合估计方法,即将未知模型参数和状态组成增广的状态向量,用UKF同时获得参数和状态估计值。通过一个离散非线性随机系统的蒙特卡洛仿真,总结滤波器参数对联合估计器性能的影响及参数选择规律。最后将该方法应用于一个典型的化工反应过程,获得了较好的效果。     

卡尔曼滤波在盾构姿态测量中的应用

三点法是一种传统的实时计算刚体三姿态角（滚动角、俯仰角和水平角）的方法。在盾构掘进过程中,观测点测量不同步会导致较大的姿态测量误差。采用卡尔曼滤波对观测点的坐标进行预测补偿来提高测量精度。建立系统运动的状态方程和量测方程,对系统噪声和量测噪声的协方差进行估计,通过递归运算对观测点坐标进行预测,蒙特卡洛仿真结果表明,这种处理方式优于传统三点法测量效果。仿真实验和测量实验结果都表明卡尔曼滤波算法既可以明显减小姿态角测量误差,又对随机系统噪声和量测噪声引起的姿态角误差具有抑制作用。     

基于小波的肠鸣音滤波方法及其应用

目的：肠鸣音是肠生理状态的反映,在临床急腹症的诊断中具有重要的意义。为深入研究肠鸣音的产生机理,需要对采集的肠鸣音进行滤波,并开发相关系统,以期为临床医生的疾病诊断提供便捷。方法：在肠鸣音采集系统的基础上,采用小波的方法进行肠鸣音的滤波,消除影响医生进行疾病诊断的干扰噪声,并搭建了相应的肠鸣音滤波分析系统。结果：搭建的分析系统与前端的采集系统一起,可以有效的组成肠鸣音记录与处理系统。结论：经过临床医生的鉴别,所采用的滤波方式能有效滤出干扰噪声,所搭建的系统具备的信号转换及音频播放功能,可以为临床医生进行疾病诊断提供便捷的方式。     

Suppression of Impulse Noise in Medical Images with the Use of Fuzzy Adaptive Median Filter

A new rule based fuzzy filter for removal of highly impulse noise, called Rule Based Fuzzy Adaptive Median (RBFAM) Filter, is aimed to be discussed in this paper. The RBFAM filter is an improved version of Adaptive Median Filter (AMF) and is presented in the aim of noise reduction of images corrupted with additive impulse noise. The filter has three stages. Two of those stages are fuzzy rule based and last stage is based on standard median and adaptive median filter. The proposed filter can preserve image details better then AMF while suppressing additive salt&pepper or impulse type noise. In this paper, we placed our preference on bell-shaped membership function instead of triangular membership function in order to observe better results. Experimental results indicates that the proposed filter is improvable with increased fuzzy rules to reduce more noise corrupted images and to remove salt and pepper noise in a more effective way than what AMF filter does.     

基于机理模型的精馏塔组分非线性预测控制算法

当精馏塔存在如进料流量、进料成分扰动,或是负荷发生大范围扰动变化时,常规控制器难以保持控制品质。本文提出了一种基于机理模型的精馏塔组分非线性预测控制方法;针对精馏塔组分不能在线测量的问题设计了扩展卡尔曼滤波器,使用可测的状态温度估计组分,并结合慢频的分析化验值对组分进行联合校正。仿真结果表明了该算法的有效性,在系统存在失配或进料扰动的情况下,可以取得良好的控制效果。     

MR Images Restoration With the Use of Fuzzy Filter Having Adaptive Membership Parameters

A new fuzzy adaptive median filter is presented for the noise reduction of magnetic resonance images corrupted with heavy impulse (salt and pepper) noise. In this paper, we have proposed a Fuzzy Adaptive Median Filter with Adaptive Membership Parameters (FAMFAMP) for removing highly corrupted salt and pepper noise, with preserving image edges and details. The FAMFAMP filter is an improved version of Adaptive Median Filter (AMF) and is presented in the aim of noise reduction of images corrupted with additive impulse noise. The proposed filter can preserve image details better than AMF while suppressing additive salt and pepper or impulse type noise. In this paper, we placed our preference on bell-shaped membership function with adaptive parameters instead of triangular membership function without variable coefficients in order to observe better results.     

EVALUATION OF SEQUEST RESULT FILTER-XCORR AND UNIFIED SCORE

Objective To estimate the effect of two simple filters, two or more positive peptide filter and Unified Score filter on the true positive rate of protein and peptide. Methods Twenty-two LC-MS/MS datasets were from 18 known protein mixture. Two or more positive peptide filter and Unified Score filter were applied to the 22 datasets. The filters effect was evaluated according to the true positive rate of protein and peptide for each filter. The positive rates of protein and peptide from two or more peptide filter raised from 56.49% to 92.86%-99.12% (for protein) and from 90.67% to 97.74%-99.62% (for peptide), but many positive proteins were filtered out.The positive rates of protein and peptide from Unified Score (ThermoFinnigan value 2400) were only about 35.51% and 82.99%, but after adjusted the value (3900) according to the number of false positive peptide, those positive rate raised to 63.61% (for protein) and 91.97% (for peptide). Conclusions Two or more peptides requirement could significantly decrease false positive rate, but it also may filter out many true positive proteins especially low molecular weight and less abundant proteins. Unified Score may be a better filter than Xcorr and DeltaCn combination and the value of 3900 is found to be more suitable for this particular datasets.     

Quantum Noise Suppression in X-ray Images using Fuzzy 2-D Wiener Filter

The noisy images are caused by decreasing quantity of the produced X-ray due to the deformation of the X-ray tube’s anode. While obtaining the image from low quantity X-ray, shot noise or quantum noise occurs, and this decreases the quality of the image. The aim of this study is to define the novel method called as Fuzzy 2-D Weiner filter (FWF-2D), which suppresses the shot noise from noisy image by avoiding any harm to the image details. With this filtering technique, it is possible to preserve the sharp-edge and the details of the image without any damage during suppressing the noise from images. FWF-2D is one of the best techniques to suppress the corrupted quantum noises due to damaged X-ray tube. The fuzzy rules used in this filter are aimed to distinguish noise pixels from image ones, and the Wiener Filter is working to remove noise pixels distinguished by these fuzzy rules. It is then possible to obtain clean images from damaged X-ray tubes by using FWF-2D technique.     

基于非线性各向异性散布滤波器的磁共振颅脑图像的分割方法

目的：介绍一种有效的分割磁共振颅脑图像中的大脑结构的方法,方法它是一个多步处理过程,首先,粗略地勾画出磁共振颅脑图像中的大脑结构作为感兴趣区;其次,对感兴趣区进行各向异性散布滤波处理;然后,对滤波图像进行二值化处理作为图像模板;最后,利用该模板模原始图像中提取出大脑结构。结果该方法能有效地分磁共振颅脑图像中的大脑结构。结论利用 基于非线性各向异性散布滤波器的图像育很好从磁共振颅脑图像中分割出大脑结构,该算法具有很强的鲁棒性稳定性。