needell-dissertation

SIFT双向匹配代码，基于matlab版本的代码(dual-matching of SIFT)

ieksu saze 3faze in matlab simulink

这是John Wiley出版的<Computational Colour Science using MATLAB.e2ban>教科书书附带的程序代码,自成一体为Matlab下的色度学工具箱. 建议将解压文件放到本地机已经安装Matlab的路径中,在toolbook文件夹下自己创建一个名为colour的文件夹中.比如:For example, this may be c:Program FilesMATLABp65 oolboxcolour 但具体路径取决于Matlab在你机器中的安装路径. 如果你将该colour文件夹加入Matlab环境路径中,该工具箱就与其它工具箱一样使用.-This is John Wiley published(It is published by John Wiley <Computational Colour Science using MATLAB.e2ban> Textbook book accompanying program code, self-contained for the colorimetric under Matlab toolbox. Suggested extracting file on the local machine has been installed in the path of Matlab in toolbook folder create yourself a folder named colour For example: For example, this may be c: Program Files MATLABp65 toolbox colour but the exact path depends on your machine Matlab installation path if you join the colour folder path in the Matlab environment, the tool box to use the same connection with other toolkits.-This is John Wiley published)

用不同的函数求得阈值进行消噪，希望对大家有用(The threshold denoising obtained with the different functions the hope that useful)

Survey about robot soccer strategies

matlab 16QAM调制解调程序 来自杜勇编著的数字调制解调技术的MATLAB与FPGA实现(The MATLAB 16QAM modulation and demodulation program comes from the MATLAB and FPGA implementation of digital modulation and demodulation technology compiled by Du Yong.)

有借鉴意义哦，是国外的成品模型，一些自适应信号处理的算法，使用matlab实现智能预测控制算法，是学习PCA特征提取的很好的学习资料。( There are reference Oh, Foreign model is finished, Some adaptive signal processing algorithms, Use matlab intelligent predictive control algorithm, Is a good learning materials to learn PCA feature extraction.)

matlab的入门程序，包含图像处理模块(matlab for the young,including the image recognition modules)

RUGGEDCOM USER GUIDE

首先从n个数据对象任意选择 k 个对象作为初始聚类中心；而对于所剩下其它对象，则根据它们与这些聚类中心的相似度（距离），分别将它们分配给与其最相似的（聚类中心所代表的）聚类；然后再计算每个所获新聚类的聚类中心（该聚类中所有对象的均值）；不断重复这一过程直到标准测度函数开始收敛为止。一般都采用均方差作为标准测度函数. k个聚类具有以下特点：各聚类本身尽可能的紧凑，而各聚类之间尽可能的分开。(First, a data object from the n choose k objects as initial cluster centers and for the rest of the other objects, according to their similarity with the cluster center (distance), respectively, assign them to their most similar (represented by cluster center) clustering then calculated for each cluster center received a new clustering (all objects in the cluster mean) repeats this process until the convergence criteria begin until the measure function. Standard deviation is generally used as a standard measure function. K a cluster has the following characteristics: the cluster itself as a compact, but separated as much as possible between each cluster.)