资源列表
wavlet2d
- 对于一幅输入的图形进行特征提取基于gabor小波变换-For an input graphics gabor feature extraction based on wavelet transform
xiaobobianhua
- 利用小波变换检测突变点实验的实例，程序最后生成3个图像演示了该算法，分别为原数字信号、高斯函数作为基函数、高斯函数的一阶导数作为基函数的小波变换。-Mutation detection using wavelet transform examples of experimental points, the program generates the final three images to demonstrate the algorithm, namely, the original digi
wavelet_transformation
- 简单的小波压缩变换工作的原理如下: 信号和求导信号,形成的求同信号序列和求导信号序列的长度均为输入信号的长度的一半.如果输入信号序列是A={a(1),...,a(n)}求同信号S={s(1),...,s(n/2)}和求异信号D={d(1),...,d(n/2)}的计算方式为: for i=1,...,n/2 s(i)=a(2*i-1)+a(2*i) d(i)=a(2*i-1)-a(2*i) 例如输入信号是: 5,2,3,2,5,7,9,6
ppanalysis
- 功率谱分析，用于序列的周期识别。将一序列用不同周期的谐波分解,并用F检验进行周期检验。-Power spectrum analysis for identification of sequence cycles. One sequence will be different harmonic decomposition cycle and test cycle with F test.
DWT1D
- 一维正交小波变换(二进小波变换）包括分解与重构-this program compute the one-dimensional orthogonormal wavelets transform of the signal in a data file and reconstruct the original signal from its wavelet decomposition using the Mallat s pyramidal algorithm.
Untitled2
- 小波滤波，可用于心电信号、脉搏波信号的滤波-Wavelet filtering, can be used for ECG, pulse wave signal filtering
xiaobo
- 该程序实现了小波变换对音频信号的降噪处理，简单实用！程序运行时需要一个.wav格式的音频信号。-Procedures for the implementation of the wavelet transform of the noise reduction audio signal processing, simple and practical! Procedures required a run-time. Wav format audio signal.
som
- MRI Brain Tumour Classification - SOM ( Self Organized Map)-MRI Brain Tumour Classification- SOM ( Self Organized Map)
Example2_6_1
- 对图像的小波分解与重构，并且进行阈值滤波，对滤波前后的图像进行了对比-The image of the wavelet decomposition and reconstruction, and the threshold to filter the images before and after filtering were compared
Waveletthresholddenoising
- 实现小波阈值去噪的程序，希望对大家有帮助-Wavelet threshold denoising
DWT
- 实现通用小波变换，包含主要的几种小波基。代码环境为MFC-Wavelet transform to achieve common, including several major wavelet. MFC code environment
xiaobobao
- 对信号进行小波包分解并求取各个分量的功率谱-The signal wavelet packet decomposition and obtain the power spectrum of the various components