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自写的3D欧几里德距离空间变换源码，参考Distance Transform of Sampled Functions,优点速度快（附相应的参考文章）(Since writing space 3D Euclidean distance transform source, reference Distance Transform of Sampled Functions, the advantages of speed (with the corresponding reference article))

QPSK高斯噪声信道下的星座点和比特误码率仿真曲线(QPSK constellations point under gaussian noise channel and the bit error rate curve simulation)

用Parzen窗法或者kn近邻法估计概率密度函数，得出贝叶斯分类器，对测试样本进行测试，比较与参数估计基础上得到的分类器和分类性能的差别.2． 同时采用身高和体重数据作为特征，用Fisher线性判别方法求分类器，将该分类器应用到训练和测试样本，考察训练和测试错误情况。将训练样本和求得的决策边界画到图上，同时把以往用Bayes方法求得的分类器也画到图上，比较结果的异同。3．选择上述或以前实验的任意一种方法，用留一法在训练集上估计错误率，与在测试集上得到的错误率进行比较。(Use Parzen Windows method or the kn neighbor method estimated probability density function, draw the bayes classifier, to test sample to test, and the parameter estimation is based on the classifier and get the difference of classification performance. 2. At the same time the height and weight data as the characteristic, with Fisher identification method for linear classifier, and the application of the classifier to training and test sample, investigation and test training error condition. Will the training sample and utility of decision on the drawing boundary paint, and at the same time before the Bayes method with optimal classifier also paint chart, the result of the comparison of the similarities and differences. 3. Select the above or before any a kind of method of experiment, with a method for training set in the estimation error rates, and on the test set get error rates are compared.)

The VLFeat open source library implements popular computer vision algorithms specializing in image understanding and local featurexs extraction and matching. Algorithms incldue Fisher Vector, VLAD, SIFT, MSER, k-means, hierarchical k-means, agglomerative information bottleneck, SLIC superpixes, quick shift superpixels, large scale SVM training, and many others. It is written in C for efficiency and compatibility, with interfaces in MATLAB for ease of use, and detailed documentation throughout. It supports Windows, Mac OS X, and Linux. The latest version of VLFeat is 0.9.19.

tracking of step trajectory bu wheeled mobile robot

鉴于本人去年7月份发布的《关于粗糙集和邻域粗糙集的基本理论和程序算例》其中有一些错误，可能给相关研究人员带来了误解，在此向大家道歉！ 同时在此资源中新增加了本人编写的邻域粗糙集的matlab计算程序，包括正域计算，约简计算，重要度计算，权重计算。 欢迎大家下载并交流学习！ 我所发布的两个版本的说明，以第二版本为主，第一个版本就不要下载了。 版权所有，除百度文库和中国程序员联合开发网上能下载到相关资源外，其他网站上的均为盗用。请尊重知识产权！(Given that I released last July, " the basic theory and procedures for rough sets and neighborhood rough set of examples," of which there are some errors, researchers may be brought to the relevant misunderstanding here to apologize! While a new addition to this resource I prepared matlab calculation procedures neighborhood rough set, including the positive domain calculation, reduction calculation, it is important calculation, the weight calculation. Welcome to download and share their knowledge! Two versions of the instructions I have released the second version of the main, the first version, do not download. Copyright, except Baidu library and Chinese programmers can be downloaded to the joint development of Internet-related resources, are stolen on other sites. Please respect the intellectual property rights!)

此文件是弹性地基梁计算程序。可通过输入梁与荷载的初始参数，计算弹性地基梁的内力、位移、反力分布。(This paper Xi River rudder is the Laos regulatory ?у Ban Tian the bake ? Cong $ Cheng Fu example, Shi. Efficiency Chi Adoption Input percent and Ya drilling crazy poured Fei Fan Wai-Pu example, parameters to help Rencong calculation Laos regulatory ?he у Pannuo bake ? the Fei Fanqiang E ?certificate Xian hand crepe Meeting ?Huoshe Mechanics distribution Kou ?

This is the matlab code of multi class common spatial pattern.

魏格纳时频分布，非平稳随机信号离散时间wvd仿真处理(Wigner time-frequency distribution, non-stationary random signal processing discrete-time simulation wvd)

MATLAB优化应用书籍，书中详细讲述了MATLAB中优化方面，是一本难得的资料，书中有详细的案例和具体的操作过程是学习MATLAB优化的首选资料(MATLAB optimization of application of books, book detail in MATLAB, optimization, is a rare data, the book detailed the case and specific course of action is to learn MATLAB optimization of the preferred data)