资源列表
PCM_model
- pcm的编码与译码，适合通信专业的同学，代码很清楚明了-pcm encoding and decoding for communications professional students, the code was clear and
faceRecognitionBasedOnWavelet
- 基于小波变换和神经网络的人脸识别：本论文围绕人脸识别问题对人脸特征提取及识别技术进行了研究。主要有：对人脸识别的研究工作进行了综述；在KL算法的基础上提出了新的基于KL的特征提取方法，克服了KL算法计算量大，计算时间长的缺点，-Based on Wavelet Transform and Neural Network Face Recognition: In this paper, issues surrounding the face recognition feature extractio
waveletanalysisandapplication
- 小波分析及其应用，详细介绍了小波变换原理和基本方法，还重点介绍小波变换在语音和图像处理、信号检测、多尺度边缘提取等领域的应用。-Wavelet analysis and applications, described in detail wavelet transform principles and basic methods, but also focuses on Wavelet Transform in the voice and image processing, signal det
contourletHMT
- contourlet隐马尔科夫变换的源代码-Hidden Markov Contourlet Transform source code
wavelet-transform
- 一个wavelet-transformation的应用界面C程序-A wavelet-transformation process of the application interface C
wavelet
- 关于小波矩神经网络识别的硕士论文，可以参考一下!-On wavelet moment neural network master s thesis, you can refer to!
wavelet_code
- vc++开发的第一代小波变换源代码，其中包含了小波变换部分，并且提供了一个利用小波变换去除噪声的例子。-vc++ developed the first generation wavelet transform source code, which contains part of the wavelet transform, and provides a use of wavelet transform to remove noise examples.
wavelet
- 转载小波压缩图象编码文档。包括EZW的详细过程。-Reprint wavelet compression image coding documents. Including the detailed process EZW.
wavelet(Chinese)
- <小波十讲>中文版.小波入门经典书籍.想学习小波的可以看看,相当不错的译本书籍,关键还是中文版的.-<Wavelet Ten Lectures> Chinese version. Wavelet entry classic books. Want to learn Wavelets can look pretty good translation of books, or the Chinese version of the key.
switch
- 图像的正交变换，包括傅里叶变换，小波变换。沃尔什变换等-Images orthogonal transformation, including the Fourier transform, wavelet transform. Walsh transformation
73462697
- 进行小波变换的各种程序，包括db小波等几种小波的。方便实用，易于操作。-Wavelet transform for a variety of procedures, including several such as db wavelet wavelets. Convenient and practical, easy to operate.
cankaowenxian
- 关于小波变换进行谐波分析的文献，讲解了各种小波变换的，资料很全-Wavelet transform on harmonic analysis of the literature on a variety of wavelet transform, the data is very wide