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分解与合成
- 用Matlab中的Haar和Db9小波对图像进行分解和重构,并在不同阈值下用PNG格式存储重构的图像.-Matlab Haar and the right image Db9 wavelet decomposition and reconstruction, and under different thresholds with PNG format image storage remodeling.
CCMethod_luzhenbo
- C-C法重构相空间文件夹说明1.CC_Method_main.m - 程序主文件 2、LorenzData.dll - 产生Lorenz离散数据 3、normalize_1.m - 信号归一化 4、ccFunction.dll - 计算S(m,N,r,t)-C-C method reconstruction phase space folders note 1.CC_Method_main.m-procedure two main documents, LorenzData.dll
CorrelationDimension_luzhenbo
- 计算关联维的 Matlab 程序 - (mex 函数，超快) ----------------------------------- 文件夹说明： 1、CorrelationDimension_main.m - 程序主文件 2、LorenzData.dll - 产生Lorenz离散数据 3、normalize_1.m - 数据归一化 4、PhaSpaRecon.m - 相空间重构 5、CorrelationDimension.dll - 计算关联积分函数
Lyapunov_exponents_luzhenbo
- 1、LargestLyapunov_example1.m 程序主文件1，直接运行此文件即可 2、LargestLyapunov_example2.m 程序主文件2，直接运行此文件即可 3、LorenzData.dll 产生 Lorenz 离散数据 4、PhaSpaRecon.m 相空间重构 5、Lyapunov_luzhenbo.dll Lyapunov 计算主函数 6、lyapunov_buffer.dll Lyapunov 计算缓存
Mutual_Information
- 利用互信息法求得混沌时间序列相空间重构最优化时延的Matlab程序-use of mutual information obtained chaotic time series reconstruction phase space optimization procedures Matlab Delay
EmbeddingDimension_Cao
- 基于Cao方法求得混沌时间序列相空间重构的最优化嵌入维的Matlab程序-Cao method, based on the chaotic time series reconstruction phase space optimization of the embedded peacekeeping procedures Matlab
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)
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
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
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
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.
work4_1
- 基于Mallat的二维Haar小波分解与重构算法的C语言实现-Mallat Haar wavelet decomposition and reconstruction algorithm in C Language
xiaobo
- 对故障数据的小波包分解与信号重构、小波包能量特征提取 暨 小波包分解后实现按频率大小分布重新排列，并进行降噪处理。(After wavelet packet decomposition and signal reconstruction, wavelet packet energy feature extraction and wavelet packet decomposition, the fault data can be rearranged according to the frequ