提升格式下几种去噪方法的比较

本文比较了四种去噪声的效果,利用提升格式设计的灵活性,通过预算子或更新算子的设计最优匹配特定的信号,比较了软阈值函数、硬阈值函数、比例萎缩LAWML法和小波域中值滤波四种去噪方法.     

基于小波变换的图像去噪方法的研究

小波变换能有效的去除高斯噪声,中值滤波能有效的去除脉冲噪声,两者结合可以更有效的去除高斯噪声和脉冲噪声的混合噪声.当医学图像去除混合噪声时,先进行中值滤波再进行小波去噪的方法优于先进行小波去噪后再进行中值滤波的方法,且去噪后图像视觉效果较好,而且图像均方误差(M SE)也较小.在图像去噪处理中这种方法具有实际应用价值.     

基于小波分析的价格周期识别——以天然橡胶和合成橡胶价格为例

使用1997年1月到2009年12月国内天然橡胶、国内合成橡胶、国际天然橡胶的月平均价格数据,运用小波去噪方法、H-P滤波法、B-K滤波法识别了各类价格的周期性并进行了比较.研究结果表明:不同方法得到的周期变化基本一致,小波去噪和BK滤波下周期相对多,HP滤波下波动幅度大;小波去噪法下各类价格对PPI具有最强的预测力,在此方法下国内天然橡胶、合成橡胶价格的平均周期长度约为22个月,国际天然橡胶约为21个月.     

利用提升格式构造稳定的对偶小波

近年来 ,产生了一种称为“提升格式”的新的小波构造方法 [7,8,9] ,它从一个较简单的多尺度分析 (MRA)出发 ,利用尺度函数相同的多尺度分析之间的相互关系 ,逐步地得到所需性质的多尺度分析 .本文仅考虑双正交滤波的提升格式 .当选定一初始双正交滤波后 ,利用提升格式构造的双正交滤波仍是双正交的 ,而这双正交滤波能否生成双正交小波 Riesz基即稳定的对偶小波 ?更进一步 ,如何从一些较为简单的不能生成双正交小波 Riesz基的双正交滤波出发 ,利用提升格式构造出具有 Riesz基性质的双正交滤波 ?这在目前有关提升格式的文章中没作回答 .本…     

偏微分方程在图像去噪中的应用

本文介绍用于图像去噪的偏微分模型、方法的发展历程．从理论上分析了线性模型、简单非线性模型、复杂非线性模型、多步处理模型出现的背景和优缺点，并从空域和频域上对偏微分方程模型的去噪原理进行了分析．最后，指出了偏微分方程去噪与小波去噪结合的途径，据此对偏微分方程未来的发展方向进行了展望．     

求解非线性算子方程的加速迭代格式

研究非线性算子方程的近似求解方法.首先对通常的求解非线性方程加速迭代格式进行推广,得到高阶收敛速度的加速迭代格式,最后把这种加速迭代格式推广到非线性算子方程的求解中去,利用非线性算子的渐进展开,证明了这种加速格式具有三阶的收敛速度.     

一种基于小波分析的各向异性图象去噪方法

本文利用非线性各向异性扩散方程结合小波变换提出一种图象去噪的方法。首先对图像进行离散小波变换,然后对其各个分量分别用各向异性的方法实现去噪。实验结果表明,该方法能够较好的去除噪声的同时,很好的保留边缘信息。     

一种改进的四阶偏微分方程图像去噪模型

针对四阶偏微分方程图像去噪模型对图像平滑区域处理造成不平整现象,以及无法去除椒盐噪声的问题.首先对含噪图像进行高斯滤波,然后通过修改扩散系数得到一个改进的四阶偏微分方程图像去噪模型.MATLAB仿真结果表明:新模型与原四阶偏微分方程去噪模型相比,其去噪图像不仅视觉效果好;而且峰值信噪比也高;另外,新模型还能有效去除椒盐噪声.     

基于HHT-SVR模型的汇率数据去噪与预测

由于存在噪音污染、具有非线性、混沌等特征,汇率预测一直是现代时间序列预测方法的重要而最具挑战的研究领域之一。本文结合变点理论,提出了基于自相关函数均值变点的HilbertHuang变换自适应去噪方法。基于该方法去噪之后的汇率日交易数据建立的SVR模型,具有较高的预测精度,稳定性较强。特别的,该方法具有很好的数据自适应性,无需要主观参与,即可自动完成去噪过程。该方法的提出,为金融时间序列去噪提供了新途径。     

Burgers方程的一个三层Fourier拟谱格式

1. 引言 谱方法为非线性偏微分方程的求解提供了新的技巧.由于拟谱方法比谱方法便于实施,计算量小,所以应用更为广泛.但它有时会产生非线性不稳定性.为此,一些滤波和抑制方法接连出现.本文对Burgers方程的周期边界问题,建立了一个带抑制算子的三层拟谱格式,同时证明了格式的广义稳定性.在一定的条件下,由此稳定性可得到收敛性。     

二进小波的构造方法研究

提出两种二进小波的构造方法.首先,将Mallat构造的B-样条二进小波推广得到一种构造B-样条二进小波的新方法;其次,基于二进提升方案提出构造二进小波的另一种新方法—–构造定理,并通过调整定理中提升参数的形式、以新的B-样条二进小波作为初始二进小波,具体构造了具有有限长单位脉冲响应、高阶消失矩、线性相位的提升二进小波,这些提升二进小波不能由Sweldens提升方案得到.     

Biorthogonal M-band filter construction using the lifting scheme

The lifting scheme has been proposed as a new idea for the construction of 2-band compactly supported wavelets with compactly-supported duals. The basic idea behind the lifting scheme is that it provides a simple relationship between all multiresolution analyses sharing the same scaling function. It is therefore possible to obtain custom-designed compactly supported wavelets with required regularity, vanishing moments, shape, etc. In this work, we generalize the lifting scheme for the construction of compactly-supported biorthogonal M-band filters. As in the previous case, we used the flexibility of the scheme to exploit the degree of freedom left after satisfying the perfect-reconstruction conditions in order to obtain finite filters with some interesting properties, such as vanishing moments, symmetry, shape, etc., or that satisfy certain optimality requests required for particular applications. Moreover, for these lifted biorthogonal M-band filters, we give an analysis-synthesis algorithm which is more efficient than the standard algorithm realized with filters with similar compression capabilities. This revised version was published online in June 2006 with corrections to the Cover Date.     

Lifting inequalities: a framework for generating strong cuts for nonlinear programs

In this paper, we introduce the first generic lifting techniques for deriving strong globally valid cuts for nonlinear programs. The theory is geometric and provides insights into lifting-based cut generation procedures, yielding short proofs of earlier results in mixed-integer programming. Using convex extensions, we obtain conditions that allow for sequence-independent lifting in nonlinear settings, paving a way for efficient cut-generation procedures for nonlinear programs. This sequence-independent lifting framework also subsumes the superadditive lifting theory that has been used to generate many general-purpose, strong cuts for integer programs. We specialize our lifting results to derive facet-defining inequalities for mixed-integer bilinear knapsack sets. Finally, we demonstrate the strength of nonlinear lifting by showing that these inequalities cannot be obtained using a single round of traditional integer programming cut-generation techniques applied on a tight reformulation of the problem.      

Construction of Biorthogonal Discrete Wavelet Transforms Using Interpolatory Splines

We present a new family of biorthogonal wavelet and wavelet packet transforms for discrete periodic signals and a related library of biorthogonal periodic symmetric waveforms. The construction is based on the superconvergence property of the interpolatory polynomial splines of even degrees. The construction of the transforms is performed in a “lifting” manner that allows more efficient implementation and provides tools for custom design of the filters and wavelets. As is common in lifting schemes, the computations can be carried out “in place” and the inverse transform is performed in a reverse order. The difference with the conventional lifting scheme is that all the transforms are implemented in the frequency domain with the use of the fast Fourier transform. Our algorithm allows a stable construction of filters with many vanishing moments. The computational complexity of the algorithm is comparable with the complexity of the standard wavelet transform. Our scheme is based on interpolation and, as such, it involves only samples of signals and it does not require any use of quadrature formulas. In addition, these filters yield perfect frequency resolution.     

关于小波正则性的几个问题

本文给出了确定尺度函数正则指数的一个公式,证明了正交的四系数滤波中Daubechies小波正则性最优,并结合B-样条对应的双正交滤波,应用提升格式,增加对偶小波的正则性.     

A Method for the Construction of Families of Biorthogonal Filters with Prescribed Properties

Some necessary and sufficient conditions are given in order to obtain biorthogonal wavelet filters with properties which are usually required in applications, such as symmetry and regularity order, by appropriately choosing the parameters in the lifting scheme. A special class of filters extending the biorthogonal B-spline filters is then proposed and analyzed.     

适合于图像压缩的7/5小波基的构造

通过利用提升算法和检验双正交小波稳定性的充分必要条件Cohen-Daubechies准则,构造了一个适合于图像压缩的7/5双正交小波基.为了便于小波变换的硬件实现,选取四个提升系数中的三个为二进制分数,而另一提升因子为1/10的倍数.本文中所构造的7/5小波基虽然在压缩性能上低于CDF9/7小波,但由于提升系数为二进制分数和1/10的倍数,所以该小波基的小波变换更易于采用硬件来实现,并且其小波变换速度比CDF9/7小波要快.实验的结果表明该小波的压缩性能优于Daubechies5/3小波,同时与[6]所构造的两组7/5小波基相比较,该小波变换不仅能方便于硬件的实现,而且其压缩性能优于或相当于[6]中的两组7/5小波基.     

Multi-step prediction of time series with random missing data

Multi-step prediction is still an open challenge in time series prediction. Moreover, practical observations are often incomplete because of sensor failure or outliers causing missing data. Therefore, it is very important to carry out research on multi-step prediction of time series with random missing data. Based on nonlinear filters and multilayer perceptron artificial neural networks (ANNs), one novel approach for multi-step prediction of time series with random missing data is proposed in the study. With the basis of original nonlinear filters which do not consider the missing data, first we obtain the generalized nonlinear filters by using a sequence of independent Bernoulli random variables to model random interruptions. Then the multi-step prediction model of time series with random missing data, which can be fit for the online training of generalized nonlinear filters, is established by using the ANN’s weights to present the state vector and the ANN’s outputs to present the observation equation. The performance between the original nonlinear filters based ANN model for multi-step prediction of time series with missing data and the generalized nonlinear filters based ANN model for multi-step prediction of time series with missing data is compared. Numerical results have demonstrated that the generalized nonlinear filters based ANN are proportionally superior to the original nonlinear filters based ANN for multi-step prediction of time series with missing data.     

用自适应提升格式对信号精确重构

本文分析了几种自适应提升格式在信号精确重构中的应用 ,在其计算过程中 ,它们均无须考虑当前步骤之前的数据。并分析了它们的优缺点。最后 ,提出一种构造自适应提升格式的方法 ,通过计算表明 ,此方法能取得更好的效果