xiebodiejia

大多数FAT的资料是英文的，这份中文的FAT资料对初学者一定很有帮助(Most of the FAT information is in English, the Chinese FAT data will be helpful for beginners)

说明：  最优化方法: 共轭方向法 matlab源代码 需要改变原函数及其梯度(Optimization: Conjugate Method need to change the original function and its gradient)

说明：  同态滤波器，用于增强图像的细节部分，灰度级扩展，边缘细节增强(Homomorphic filter, used to enhance the details of the image, gray-scale expansion, edge detail enhancement)

LDA学习用到的算法，不是自己写，别人的，拿来学习用(LDA learning algorithm is used, not her own writing, others, used to learn)

Tool for Model-Based Design Tool for Analysis How Simulink Software Interacts with the MATLAB Environment

matlab检测直线交点源程序在matlab6.5下已调试通过(Matlab line detection of the source matlab6.5 Nodal has been under debugging through)

K最邻近密度估计技术是一种分类方法，不是聚类方法。 不是最优方法，实践中比较流行。 通俗但不一定易懂的规则是： 1.计算待分类数据和不同类中每一个数据的距离（欧氏或马氏）。 2.选出最小的前K数据个距离，这里用到选择排序法。 3.对比这前K个距离，找出K个数据中包含最多的是那个类的数据，即为待分类数据所在的类。(K nearest neighbor density estimation is a classification method, not a clustering method. It is not the best method, but it is popular in practice. Popular but not necessarily understandable rule is: 1. calculate the distance between the data to be classified and the data in each other (Euclidean or Markov). 2. select the minimum distance from the previous K data, where the choice sorting method is used. 3. compare the previous K distances to find out which K data contains the most data of that class, that is, the class to which the data to be classified is located.)

脑电信号的复杂度计算，有文档和多个matlab程序实例(EEG complexity calculation, there are documents and multiple instances of matlab program)

实例10：阶梯图 实例11：枝干图 实例12：罗盘图 实例13：轮廓图 实例14：交互式图形 实例15：变换的傅立叶函数曲线(Example 10: Ladder Diagram Example 11: Example branches Figure 12: Compass Chart Example 13: The contour map instance 14: 15 Interactive graphic example: the Fourier transform function curve)

一个基于DCT的数字水印源码想要的可以下载看看。(A DCT-based digital watermarking can download source code you want to see.)