-
Untitled7
基于matlab的车牌识别系统设计源码，由于对硬件的要求，只能识别特定环境下拍摄到的车牌(Based on the license plate recognition matlab source system design, because of hardware requirements, can only identify the specific circumstances of the license plates photographed)
- 2009-05-30 10:41:37下载
- 积分：1
-
discrete_rnd
说明： 本代码可实现在MATLAB环境下获取随机分布的数(This code can be realized in the MATLAB environment to obtain the probability of paper, to facilitate data analysis and processing)
- 2009-08-23 16:41:16下载
- 积分：1
-
DESARROLLO-DEL-CODEC-DE-VOZ-G
Codificador de voz a 8 kbps implementado en microblaze.
- 2011-05-15 02:39:52下载
- 积分：1
-
Lab-RGB
RGB和Lab颜色空间互相转换Matlab代码，亲测，非常好(Codes to transfer between RGB and Lab color space. Perform perfectly)
- 2013-11-16 17:20:32下载
- 积分：1
-
paikai_v85
中介真值程度度量，基于中介真值程度度量的图像分割部分实现了追踪测速迭代松弛算法，人脸识别中的光照处理方法。( The true extent of the value of the intermediary measure, measure the true extent of the agency based on the value of image segmentation Partially achieved tracking speed iterative relaxation algorithm, Face Recognition light treatment method.)
- 2016-05-31 09:57:03下载
- 积分：1
-
DE-差分进化算法
说明： 差分进化算法的pdf和完整代码，差分进化算法包括变异、交叉和选择三大操作(Differential Evolution Algorithm PDF and complete code, differential evolution algorithm includes mutation, crossover and selection of three major operations)
- 2020-11-06 08:59:50下载
- 积分：1
-
FFT_IFFT
自己编的程序，实现快速傅里叶变化，结果和matlab自带的fft2一样。(Own series of programs, fast Fourier transform, results and matlab native fft2 the same.)
- 2010-07-05 22:47:09下载
- 积分：1
-
MATLABbook
matlab教程从数据类型讲起由浅入深到simulink仿真(I start from the data type matlab tutorial progressive approach to the simulink simulation)
- 2010-12-03 22:31:18下载
- 积分：1
-
HoughGrd
说明： 使用hough 变换检测直线，参数可以任意设定，程序说明详细。(Using the hough transform to detect straight lines, the parameter can be set, detailed description of the procedures.)
- 2011-03-28 11:25:24下载
- 积分：1
-
NewK-means-clustering-algorithm
说明： 珍藏版，可实现，新K均值聚类算法，分为如下几个步骤：
一、初始化聚类中心
1、根据具体问题，凭经验从样本集中选出C个比较合适的样本作为初始聚类中心。
2、用前C个样本作为初始聚类中心。
3、将全部样本随机地分成C类，计算每类的样本均值，将样本均值作为初始聚类中心。
二、初始聚类
1、按就近原则将样本归入各聚类中心所代表的类中。
2、取一样本，将其归入与其最近的聚类中心的那一类中，重新计算样本均值，更新聚类中心。然后取下一样本，重复操作，直至所有样本归入相应类中。
三、判断聚类是否合理
采用误差平方和准则函数判断聚类是否合理，不合理则修改分类。循环进行判断、修改直至达到算法终止条件。(NewK-means clustering algorithm ，Divided into the following several steps:
A, initialize clustering center
1, according to the specific problems, from samples with experience selected C a more appropriate focus the sample as the initial clustering center.
2, with former C a sample as the initial clustering center.
3, will all samples randomly divided into C, calculate the sample mean, each the sample mean as the initial clustering center.
Second, initial clustering
1, according to the sample into the nearest principle clustering center represents the class.
2, as this, take the its recent as clustering center of that category, recount the sample mean, update clustering center. And then taking off, as this, repeated operation until all samples into the corresponding class.
Three, judge clustering is reasonable
Adopt error squares principles function cluster analysis.after clustering whether reasonable, no reasonable criterion revisio)
- 2011-04-06 20:45:56下载
- 积分：1
