查询词典 wavelet

By making up of time-frequency local property and multi-scale analytical capability of wavelet transformation and self-learning and prediction function of artificial neural network,chapter three develops a prediction model loose combining wavelet analysis and Radial Basis Functionsneural network,abbreviated as Wavelet-RBFNN.

第三章利用小波变换的时频局域化特性和多尺度分析能力及神经网络的自学习、预测功能，通过小波分析与神经网络的松散型结合方式，建立小波分析和径向基函数神经网络(Wavelet-RBFNN)预测模型。

Besides, as to inpainting problem in wavelet domain, we introduce a new iterative model. In this model low frequency and high frequency will carry on processing separately, enormous speed up the image repair convergence rate, and even if as high as 90% wavelet coefficient have been lost, this model will also be able to have the very good repair effect. In the old model, to compute the curvature we have to transform the coefficients to the pixel domain, and then transform back to the coefficient domain for several times and this method can solve this problem and speed up the iterative convergence.

其次针对小波域中图像修复的问题，本文提出了一种新的小波域图像修复模型，该模型根据小波变换后系数相关性的特点，将低频和高频分别进行处理，极大的加快了图像修复的收敛速度，并且即使丢失高达90%的小波系数，该模型也会有很好的修复效果，有效的解决了传统的TV- Wavelet模型在计算图像的平均曲率WCURV时，需要反复进行小波分解与重构的计算，迭代速度慢的问题。

In this paper, a speckle reduction method for Synthetic Aperture Radar images based on Dual Tree Complex Wavelet Transform is proposed, for the DTCWT has approximate shift-invariant and good directional selectivity.

利用双树复数小波变换(Dud Tree Complex Wavelet Transform， DTCWT)的近似平移不变性和多方向选择性，提出了一种基于DTCWT变换的SAR图像嗓声抑制方法。

Chapter two studied the Wavelet-Galerkin method tailored to solve the initial boundary value problem of one-dimention heat conduction equation.

第二章研究了一维热传导方程的初边值问题的Wavelet-Galerkin方法。

Firstly, Wavelet-Galerkin algorithm for solving the first kind of singular integral equation with the Hilbert kernel is proposed, we use the characteristic of periodic wavelet on L~2([0,1]) and Hilbert kernel to solve and make stiff matrix lower dimensions and become sparser through thresholding,thus the cost of computation is reduced. Because of the singularity of Hilbert kernel we use Tikhonov regularization method to solve the system of stiff equation. At last the convergence and numerical result of approximate solution are given. Secondly, an approach of regularization based on Fourier is presented for sideways heat equation; we give the theory proof and error estimate.

首先，提出了含Hilbert核的第一类奇异积分方程的小波伽辽金(Wavelet-Galerkin)数值算法，该算法中利用了L~2([0，1])上的周期小波和Hilbert核的特点进行处理，使得刚性矩阵维数降低并且通过阈值使得它更加稀疏，减少了计算量；由于Hilbert核的奇异性，通过Tikhonov正则化方法求解所得到的刚性方程组，给出了收敛性和数值结果；其次，对标准的一维逆热传导方程给出了一种基于Fourier正则化方法，给出了理论证明及其误差估计，解决了文献中算法与理论误差估计的不相匹配的现象，该正则化方法不仅保留了测量数据的部分高频成份，且与文献中的算法具有同样的计算量和误差估计。

Using the estimation of marginal and joint statistical distribution of Contourlet coefficients via the method of maximum likelihood estimator, multiplicative watermarking and blind detection framework is presented in the Wavelet transformation domain and the Contourlet transformation domain.

采用极大似然估计的方法对Wavelet变换和Contourlet变换系数的边缘分布和联合分布进行拟合，提出了一种Wavelet变换域和Contourlet变换域乘嵌入水印及盲检测框架。

The magnitude of sliding mode switching gain is the key reason causing system chattering. Self-recurrent wavelet neural networks is used to estimate sliding mode switching gain on-line, which can reduce chattering caused by sliding mode control effectively.

滑模开关增益的大小是造成系统抖振的关键，采用自回归小波神经网络(Self-recurrent wavelet neural networks， SRWNN)在线估计滑模开关增益的大小可以有效降低滑模控制造成的抖振。

The basic idea of Frequent-Wavelet is to pass time series through the atrous smooth filters set, and then cluster the derived subsequences, so the problem of FTS mining is converted to the problem of FIS mining.

Frequent-Wavelet算法的基本原理是使时间序列通过多孔平滑滤波器组，然后对来自多个尺度序列的子序列进行聚类，从而将时间序列的频繁模式挖掘问题转化为项目序列的频繁模式挖掘问题。

In comparison with the drawbacks related to the Fourier Transform and Smoothed Instantaneous Wave Energy History(SIWEH, the Wavelet Transform will be show to be much better suited for analyzing wave shoaling In which signal is believed to be non-stationary and wide band.

在使用小波转换作为分析波浪工具之前，我们选择 Morlet wavelet、Paul wavelet与Gaussian三种型态之小波函数进行讨论，最终考虑视窗面积之大小、复数型态之小波函数及频率视窗的集中度，而以 Morlet wavelet较适合分析波浪。

LDoS (low-rate denial-of-service) attacks are stealthier and trickier than the traditional DDoS attacks. According to the characteristic of periodicity and short burst in LDoS flows, a detectionsystem DSBWA (detection system based on wavelet analysis) against LDoS attacks has been designed andimplemented based on feature extraction using wavelet transform.

低速率拒绝服务攻击(low-rate denial-of-service，简称LDoS)比传统的DDoS攻击更具隐蔽性和欺骗性，依据其周期性脉冲突发特点，设计实现了一种基于小波特征提取的LDoS 检测系统DSBWA(detection system based on wavelet analysis)。

Kate: I'm sorry I kissed you.

抱歉，我亲了你。

This means giant network to buy long swim the hearsay of the net is complete by checkmate.

这意味着巨人网络收购久游网的传闻彻底被击破。