基于小波的医学图像去噪方法研究

为有效地表现医学图像原有信息中有用的信息,降低医学图像受噪声干扰的现象,减少诊断误差,本文将现有的小波图像去噪方法运用于医学图像,并对各种方法进行实验分析比较,以提供医学参考。实验发现,与较常用的均值滤波与中值滤波相比,小波去噪方法有效提高了医学图像的去噪PSNR值。     

对南方山地勘探激发试验实施方式的新思考

针对南方山地野外地震采集过程中关于如何实施激发试验提出了两点疑问,并对疑问进行了深入的思考,同时在CXN地区进行了一系列激发试验研究探讨,主要研究了传统的井深试验、药量试验的特点,指出其存在的欠科学性,并对这些问题进行了重点分析,提出了相应的解决方法。     

改进的基于移动小波树的数据流异常检测方法

针对移动小波树数据流异常检测算法的不足,提出了一种改进的移动小波树异常检测方法,利用比率阈值去除颠簸数据的干扰,提高了检测精度;利用二分查找检测算法,提高了检测的效率;结合实时增量更新算法满足了数据流在线处理的要求;改进了阈值设定方法,可实现双边异常检测。用射线数据和电能质量扰动数据进行仿真实验,结果验证了方法的有效性。     

Gasoline quality prediction using gas chromatography and FTIR spectroscopy: An artificial intelligence approach

This paper reports on analysis of 45 gasoline samples with different qualities, namely, octane number and chemical composition. Measurements of data from gas chromatography and IR (FTIR) spectroscopy are used to gasoline quality prediction and classification. The data were processed using principal component analysis (PCA) and fuzzy C means (FCM) algorithm. The data were then analyzed following the neural network paradigms, hybrid neural network and support vector machines (SVM) classifier. The IR spectra were compressed and de-noised by the discrete wavelet analysis. Using the hybrid neural network and multi linear regression method (MLRM), excellent correlation between chemical composition of the gasoline samples and predicted value of the octane number was obtained. About 100% correct classification for six different categories of the gasoline was achieved, each of which has different qualities.     

小波变换降噪技术及其在Matlab中的实现

小波降噪含模极大值、尺度空间滤波、域值滤波三种方法.域值滤波法只对低频部分进一步分解,不考虑高频部分,因而用小波函数进行处理.域值滤波方法的处理过程为:对信号进行小波分解;小波分解高频系数的域值量化;信号重组.对潜艇获得的测量方位信号仿真结果分析表明,该方法可行.     

基于小波包自组织神经网络的图像数据融合

基于小波包与模糊自组织特征映射神经网络的图像数据融合,将图像在小波包最优基下展开,利用小波包最优基空间、尺度定位性提高分辨率,获得更好的去噪效果;再采用具有很强聚类功能的自组织特征映射网络进行图像数据的聚类;最后通过计算图像像素点的灰度均值来得到图像数据的融合结果.     

基于奇异值分解的惯性测量组合减振系统非线性刚度识别

介绍了基于奇异值分解的复解析小波脊线提取方法,并用仿真算例进行了验证.设计了基于冲击响应的非线性刚度识别程序.采用半正弦冲击对惯组减振系统的非线性特性进行试验研究,验证了方法的可行性,分析了非线性系统刚度和阻尼的变化规律.对于非线性特征比较明显的结构,使用该方法的参数识别结果具有较高精度.     

Online Wavelet Complementary velocity Estimator

In this paper, we have proposed a new online Wavelet Complementary velocity Estimator (WCE) over position and acceleration data gathered from an electro hydraulic servo shaking table. This is a batch estimator type that is based on the wavelet filter banks which extract the high and low resolution of data. The proposed complementary estimator combines these two resolutions of velocities which acquired from numerical differentiation and integration of the position and acceleration sensors by considering a fixed moving horizon window as input to wavelet filter. Because of using wavelet filters, it can be implemented in a parallel procedure. By this method the numerical velocity is estimated without having high noise of differentiators, integration drifting bias and with less delay which is suitable for active vibration control in high precision Mechatronics systems by Direct Velocity Feedback (DVF) methods. This method allows us to make velocity sensors with less mechanically moving parts which makes it suitable for fast miniature structures. We have compared this method with Kalman and Butterworth filters over stability, delay and benchmarked them by their long time velocity integration for getting back the initial position data.     

基于小波变换的图像边缘检测方法

基于小波变换的图像边缘检测,其图像平滑度与尺度增大成正比:尺度增大,高频受到强抑制,输出图像的信噪比提高,图像边缘平滑变粗,定位精度降低;反之边缘定位精度可提升.小波基函数的选取应保证检测精度,故用大尺度滤波器抑制原图像噪声.同时用小尺度滤波器为图像边缘精确定位,即依据边缘检测的小波母函数一般准则,构造二次B样条小波,并采用自适应阈值图像边缘检测法检测图像边缘.     

基于小波变换的影像融合算法与效果评价

在众多的图像融合技术中，基于小波变换的图像融合方法已成为目前研究的一个热点。小波变换具有多分辨率等特点，可以有效地将特征明显、分辨率高的图像融合在一起，得到比任何一幅源图像效果都好的图像。在阐述小波变换的Mallat算法的同时，对遥感影像融合的分析与评价进行了深入的探讨，提出了综合利用3类统计参数进行评价的方法。经实验，评价结果与理论分析结果和目视效果相吻合，说明这些参数可以作为遥感影像融合客观效果的评价准则。