PTSingleNovel_v2.1.4

资料：matlab数字图像处理语言整理汇总，实用全面(matlab image processing language order summary)

ni5641r模拟输入代码，并画功率谱估计。(ni5641r analog input,and draw power spectrum estimation.)

说明：  小波变换的matlab程序，包括离散小波变换，多尺度变换，小波包分析，小波用于图像压缩、水印、去噪(Matlab wavelet transform procedures, including the discrete wavelet transform, multi-scale transform, wavelet packet analysis, wavelet image compression, watermarking, denoising)

Cert Path Validator Test for Andriod.

matlab code for qpsk modulation technique

小波神经网络研究的进展用于预测和函数逼近，希望可以抛砖引玉(Wavelet neural network for predicting the progress of the study and function approximation, hoping to start)

Introduction to channel estimation by using LS and MMSE.

Brodatz Album 库中任取10幅图像，每幅图分成四小块，得到40幅小图像，取其中一幅小图像，对大图中其余三幅小图进行检索(image retrieval)

聚类算法，不是分类算法。分类算法是给一个数据，然后判断这个数据属于已分好的类中的具体哪一类。聚类算法是给一大堆原始数据，然后通过算法将其中具有相似特征的数据聚为一类。这里的k-means聚类，是事先给出原始数据所含的类数，然后将含有相似特征的数据聚为一个类中。所有资料中还是Andrew Ng介绍的明白。首先给出原始数据{x1,x2,...,xn}，这些数据没有被标记的。初始化k个随机数据u1,u2,...,uk。这些xn和uk都是向量。根据下面两个公式迭代就能求出最终所有的u,这些u就是最终所有类的中心位置。(Clustering algorithm, not a classification algorithm. Classification algorithm is to give a figure, and then determine the data belonging to a specific class of good which category. Clustering algorithm is to give a lot of raw data, and then through the algorithm which has similar characteristics data together as a class. Here k-means clustering, is given in advance the number of classes contained in the raw data, then the data contain similar characteristics together as a class. All information presented in or Andrew Ng understand. Firstly, raw data {x1, x2, ..., xn}, the data is not labeled. K random initialization data u1, u2, ..., uk. These are the vectors xn and uk. According to the following two formulas can be obtained final iteration all u, u is the ultimate all these classes the center position.)

详细描述了使用KSVD算法训练完备字典的图像处理方法，精华版(Use KSVD algorithm training complete dictionary)