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tuxiangchuli
用matlab做图像处理的代码，主要是用函数处理图像(Image processing code)
- 2010-07-03 11:02:17下载
- 积分：1
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zuixiaoerchengsuanfa
这个是最小二乘算法的一个重要用途，在实际操作中有广泛的应用，可以处理很多问题！(This is an important use of least squares algorithm, in practice a wide range of applications, can handle a lot of problems!)
- 2011-04-28 19:48:43下载
- 积分：1
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ActivityGroupDome
不错的动画效果的demo，真诚希望对大家有帮助，也希望大家来点人气，谢谢。(A good animation demo, sincerely hope to have the help to everybody, also hope to some popularity, thank you.)
- 2013-12-10 11:33:26下载
- 积分：1
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3
说明： malloc项目第三阶段：优化，用哈希表实现，同时加深对数据结=结构的理解(malloc Project Phase III: optimization, with the hash table to achieve at the same time deepen the understanding of the structure of the data node =)
- 2010-07-28 16:03:16下载
- 积分：1
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digitalsignalprocessing
数字信号处理关于数字滤波器的设计，并用matlab实现(Digital signal processing on the digital filter design and realization of matlab)
- 2009-06-07 15:13:33下载
- 积分：1
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equizer
说明： HART协议的均衡器设计 DCT LMS 设计 + 位同步设计，仿真证明了设计的有效性(HART protocol design DCT LMS equalizer design+ Bit synchronous design, simulation proves the validity of the design)
- 2008-10-01 21:06:01下载
- 积分：1
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onepoint
说明： 合成孔径雷达图像处理中最简单的情况，单个点目标的回波模型(sar)
- 2010-04-10 20:38:58下载
- 积分：1
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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
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SAS-exp
说明： 生存分析，学习总结资料和SAS实验.ppt(Survival analysis, study summarizes experimental data and SAS. Ppt)
- 2011-04-07 11:18:58下载
- 积分：1
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CompareTo
Compare To Source Code for Andriod.
- 2014-01-01 11:14:59下载
- 积分：1
