基于滤波的SAR影像去噪方法分析

根据SAR(Synthetic Aperture Radar)影像相干噪声的特点,对现在广泛应用的各种抑制噪声的滤波方法如均值滤波、Frost滤波、增强型Lee滤波、Lee滤波、中值滤波等进行分析,并提出适合本研究区影像的基于小波变换的分量滤波处理去噪方法,利用均值、标准差、平滑指数、PM值、信息熵和平均梯度等评价指标对各种滤波去噪后的影像质量进行评价,并对去噪效果进行对比分析,证明本文所采用的滤波方法对SAR影像噪声有很好的抑制作用,并且较好的保存了图像纹理信息。     

汽车振动噪声测试的阶次跟踪方法

汽车振动和噪声是影响舒适性的主要因素，如何采用有效的技术手段测量分析汽车的振动、噪声，日益受到人们重视。本文应用PULSE多分析系统中的阶次跟踪分析方法，测试分析了车内司机座位处振动、噪声随发动机转速变化的关系，结果发现，对于试验车在测试工况下1．5倍发动机转速时，车内振动和噪声都有一个峰值。文中通过阶次分析，对发动机运转稳定性进行了测试。为降低车内噪声和振动响应提供了分析依据和参考。     

基于群延时信息的超声信号处理方法

充分利用超声信号的群延时信息，结合短时傅里叶变换，给出了群延时对频率导数在时一频域中的分布，以此来反映时一频域中局部信噪比的强弱。在此基础上，进一步利用超声信号的群延时信息，极大地增强了缺陷信号。     

Evaluation of tempering induced changes in the hardness profile of case-carburised EN36 steel using magnetic Barkhausen noise analysis

The effect of tempering on the magnetic Barkhausen noise (MBN) signal profile was studied in case-carburised EN36 steel using a range of magnetic excitation frequencies and a number of frequency ranges for analysis of the MBN signal. The MBN level generally increases with tempering due to coarsening of the microstructure. With higher values of excitation frequency, f_EX, the MBN profile exhibits a single peak, but with low values of f_EX, double peaks are observed. The MBN peak obtained with higher f_EX was found to correlate well with hardness changes in a region, down to 100 μm below the surface. The analysis of the MBN signal produced with low f_EX, in narrow frequency ranges selected by software frequency filtering, showed variations in the extent of changes in the relative height of the two MBN peaks in the profile. After taking into account the skin depth-frequency relation for the MBN signal, variations in the values of the two MBN peaks in different analysing frequency ranges were found to correlate well with hardness variations at different depths down to 425 μm below the surface. An empirical relationship has been established between the hardness-depth profile and the MBN measurements.     

A continuous-time framework for least squares parameter estimation

This paper proposes a continuous-time framework for the least-squares parameter estimation method through evolution equations. Nonlinear systems in the standard state space representation that are linear in the unknown, constant parameters are investigated. Two estimators are studied. The first one consists of a linear evolution equation while the second one consists of an impulsive linear evolution equation. The paper discusses some theoretical aspects related to the proposed estimators: uniqueness of a solution and an attractive equilibrium point which solves for the unknown parameters. A deterministic framework for the estimation under noisy measurements is proposed using a Sobolev space with negative index to model the noise. The noise can be of large magnitude. Concrete signals issued from an electronic device are used to discuss numerical aspects.     

炭素厂的消烟除尘和噪声控制

针对炭素制品生产过程产生的粉尘、沥青烟气、噪声等主要涉及工业卫生及环境保护等方面的问题进行剖析，并对治理方法做了简要的介绍。     

Experimental design in soap manufacturing for optimization of fuzzified process capability index

In manufacturing industries, the quality of a product depends on the combined effect of multiple input variables working singly or together and therefore attention has been given on process capability indices to shift from single to multivariate domain. In case of multivariable domain the capability to incorporate uncertainties at the time of decision making becomes necessary. Fuzzy system is introduced to take care of this requirement. In this article the process parameters of soap manufacturing industries have been analyzed. The process capability is determined using Fuzzy Inference System rule editor based on a set of justified if then statements as applicable for the process. The data has been collected in linguistic form to derive its process capability, using a set of justified rules and the effect of each factor has been determined using Design of Experiments (DoE) and analysis of variance technique (ANOVA) for improving the soap quality from perspective of its softness. This article ventures to propose a new methodology by integrating Fuzzy with DoE providing better result followed by DoE and Fuzzy Inference system in isolation.     

具有数据包丢失的离散随机不确定系统的线性最优满阶估值器

研究了具有数据包丢失和随机不确定性离散随机线性系统的状态估计问题.其中数据包丢失是随机的,且满足Bernoulli分布,系统矩阵中的随机不确定性由一个白色乘性噪声来描述.首先,通过配方方法,提出了最小均方意义下的无偏最优线性递推满阶滤波器.所提出的滤波器用到了当前时刻和最近时刻接收到的观测来保证线性最优性.与多项式滤波和增广滤波器相比,本文的滤波器具有较小的计算负担.然后,基于所获得的线性滤波器推导了线性最优预报器和平滑器.进一步研究了线性最优估值器的渐近稳定性,给出了稳态特性存在的一个充分条件.最后,通过两个仿真例子验证了所提估计算法的优越性.     

EMD-IT去噪算法的阈值估计方法

为解决EMD-IT去噪算法中阈值难以确定的问题,提出一种基于高斯白噪声能量分布的阈值估计方法。将含噪信号进行经验模态分解并估计各固有模态函数(IMF)中噪声的能量;根据模态单元阈值的含义,在各IMF中利用去除掉的模态单元包含的总能量等于噪声能量这一准则估计阈值。合成数据和实际心电信号的去噪仿真实验验证了该方法的有效性,其是自适应的且避免了阈值选择的主观性。     

基于引力搜索算法的分数阶变异时序回归GSA-TSGM(1,1)模型

为了利用分数阶累加算子在灰色短期预测中的高效性能,首次将分数阶累加算子引入变异时序回归模型以期取得更高的预测精度。主要方法如下：首先取湖北省链子崖某监测点1978—1987年的十年数据作为训练集并使用引力搜索算法确定最佳分数阶累加阶数,而1988—1993年的六年数据作为验证集验证提出的模型;其次对比了经典灰色模型GM(1,1)、分数阶累加灰色模型、变异时序回归模型TSGM(1,1)三种灰色模型。结果如下：首先修正了陈西江等人变异时序回归模型仿真时出现的错误,其次表明了相比于其他的模型,基于引力搜索算法的分数阶累加时序回归模型在进行灰色长期预测中具有较高的预测精度。因此,通过分数阶累加算子提高了灰色理论中长期预测模型的精度,为灰色长期预测提供了指导。