-
add_gauss_white_noise_or_salt_and_pepper_noise
使用这个matlab程序,你可以对图像实现加高斯白噪声或者椒盐噪声(whth this matlab code,You can add Gaussian white noise or salt and pepper noise on the purpose image )
- 2010-10-22 21:22:17下载
- 积分:1
-
2
说明: 采用M语言进行卡尔曼滤波器仿真matlab程序(M language Kalman filter simulation)
- 2012-05-25 13:00:13下载
- 积分:1
-
matmatlab
Digital Signal Processing, developped in matlab short examples for processing
- 2015-03-17 18:14:44下载
- 积分:1
-
GrTheory
博弈论的相关工具程序,是个经济的工具箱,功能很多(Games)
- 2010-10-15 16:57:51下载
- 积分:1
-
SLToolKit
SLToolKit Silverlight图片展示(SLToolKit Silverlight)
- 2010-01-05 13:09:55下载
- 积分:1
-
qinzhende
图像去噪 使用小波 curlet变换处理信号(The image denoising wavelet curlet transform)
- 2013-04-05 16:22:58下载
- 积分:1
-
DIJKSTRAs
这是一个求最短路的算法,用DIJKSTRA的方法(This is a shortest path algorithm for)
- 2009-04-09 23:45:54下载
- 积分:1
-
matlab-program-pca
基于PCA的人脸识别代码,识别率可达88 (PCA-based face recognition code, the recognition rate up to 88 )
- 2011-04-27 11:07:21下载
- 积分:1
-
ART
ART1自适应谐振网,已经通过测试,分类性能良好并且准确,此程序已经完成了运行,希望大家好好利用(ART1 adaptive resonance network, has passed the test, the classification performance is good and accurate, this program has completed running, I hope you make good use of)
- 2013-07-19 13:07:30下载
- 积分:1
-
matlab
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.)
- 2014-02-18 09:59:02下载
- 积分:1