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springquick
- Spring 快速入门教程 ──开发你的第一个Spring程序 翻译整理：Hantsy Bai<hantsy@tom.com> 本章学习用struts MVC框架作前端，Spring做中间层，Hibernate作后端来开发一个 简单的Spring应用程序。在第4章将使用Spring MVC框架对它进行重构。-Spring Quick Start Guide -- your first developed a procedure Spring translated :
Volterra_luzhenbo
- Volterra自适应预测的 matlab 程序,用于自适应预测测试和混沌序列的相空间重构（转）-Volterra adaptive prediction Matlab procedures for testing and adaptive prediction chaotic sequence of phase space Reconstruction (switch)
DesigningwithWebStandards
- <网站重构-应用web标准进行设计>一本关于web标准的书 感觉很好 很辛苦在找到电子版的 和大家共享-lt; Reconstruction Site-standard web application design gt; A web standards on the books feel very very hard to find the electronic version and share
csjtooth
- 用opengl做的牙齿的重构，很适用的，构建opengl，以及重构的算法实现-opengl do with the reconstruction of the teeth, very applicable, opengl Construction and Reconstruction Algorithm
waveletspectrum
- 用于小波滤波器的谱分析，mallat分解法。实现信号的重构-for wavelet spectral analysis, Mallat decomposition. Signal Reconstruction
C-CMethod
- C-C法重构相空间，源自研学论坛-C-C method reconstruction phase space, from the Institute Science Forum
a-Blog(AlparBlog)v1.29
- 功能更新: - 修正1128版本部分已知BUG - 后台一般设置增加\"备案信息\",\"站长昵称\",\"站长邮件地址\" - 修正连接管理及验证页面过滤不严 漏洞！ - 增加 多媒体文件自动播放功能 - 将换肤组件升级为 kaichun开发地“无刷新JS版” - 高亮关键字中文编码化 - 增加日志归档， 默认为隐藏；点击页顶导航栏“日志归档”在侧边栏显示！ - 修改
Volterra_MultiStepPred_luzhenbo
- 基于Volterra滤波器混沌时间序列多步预测 作者：陆振波，海军工程大学 欢迎同行来信交流与合作，更多文章与程序下载请访问我的个人主页 电子邮件：luzhenbo@sina.com 个人主页：luzhenbo.88uu.com.cn 参考文献： 1、张家树.混沌时间序列的Volterra自适应预测.物理学报.2000.03 2、Scott C.Douglas, Teresa H.-Y. Meng, Normalized Data Nonlineariti
Example6_2
- 用MATLAB实现对一语音信号用不同小波进行分解，提取各层的高低频系数，画出各系数波形，并重构。-MATLAB voice signal to a different wavelet decomposition, from the high levels of low-frequency coefficients. he painted the waveform coefficients, and Reconstruction.
Example6_8
- 用MATLAB对一语音信号进行小波分解，然后对其各层系数进行处理以达到小波抑制的目的，重构处理后的信号，画出波形分析。-MATLAB to a voice signal wavelet decomposition, its floors coefficient then processed to achieve the purpose of inhibiting Wavelet, reconstruction after the signal waveform analysis paint.
Example2_4_1
- 用MATLAB对一图象分别用单尺度和二维小波分解，观察各高低频部分，对图象进行重构和压缩。-MATLAB image of a single yardstick were used and two-dimensional wavelet decomposition, the high-low frequency observation, right image reconstruction and compression.
Example2_6_1
- 用MATLAB对一图象分别用不同小波分解，观察高低频部分进行重构，比较重构误差，再进行阈值消噪，比较消噪前后图象。-MATLAB right one image with different wavelet decomposition, high-low-frequency observations for some remodeling, more reconstruction error and then de-noising, compared before and after image
edege_detection
- 基于小波变换模极大的多尺度图像边缘检测matlab源代码，该算法采用的是样条小波，为了更好的检测边缘，用多孔算法代替了mallat算法。该算法和mallat快速算法主要区别： 1 多孔算法不需要抽取偶数样本，所以奇异检测定位更准确，相应的重构是不需要插零。2 多孔算法需要对滤波器进行伸缩。-based on wavelet transform modulus maxima of multiscale edge detection Matlab source code, The algori
mallat_algorithm
- 自编的快速小波变换mallat算法，使用‘db1’小波函数，在卷积时使用wkeep命令进行了数据截取。重构信号和原信号比较误差较小。-self fast wavelet transform Mallat algorithm, the use of 'db1' wavelet function, Convolution in the use of wkeep order the interception of data. Reconstruction of the original
fenjie
- 图像的分解与重构,运用高斯函数对图像进行分解和重构,较简单-image decomposition and reconstruction, using Gaussian function right image decomposition and reconstruction, a simpler
signal-de-noise
- 采用db1基本小波来分解信号,比较第三层近似信号与原始信号,重构最大误差,比较第三层近似信号与原始信号.-used db1 to the basic wavelet decomposition signal, the third layer approximate comparison with the original signal signal, the largest reconstruction error Comparing the third layer similar to the
MarchCube
- MatchCube 三维网格数据等值表面重构算法。使用查表方式进行。-MatchCube 3D mesh surface contour data reconstruction algorithm. The use of look-up table method.
decomposeAndrevaluationOfWavelet
- 小波在信号处理中的应用，利用小波对信号进行分解和重构，而且对信号进行噪声的阈值处理。-Wavelet in signal processing applications, the use of wavelet decomposition and reconstruction. but for the noise signal processing threshold.
xiaobaobianhuan
- 这是用小波变换重构信号的matlab源码，拿出来和大家共享-This is the wavelet transform Reconstruction signal source Matlab, and to take share
xiaobofenjieyuchonggou
- 这是关于小波图像分解与重构的代码希望给大家帮助-This is the image of wavelet decomposition and reconstruction of the code we hope to help