dddf

非常好的MATLAB学习书籍，图像处理.非常值得下载，一定能对用户有很大帮助。(A very good book to learn MATLAB, image processing. Well worth downloading certainly of great help to users.)

正态分布表的PZ值转换。可以输入P矩阵得到Z值(PZ transfer)

levelset的matlab工具箱。内涵说明文档，有实例程序(levelset the Matlab toolbox. Connotations of documentation, sample program)

本代码根据noiselets算法编写，可以生成NXN的任意矩阵(To write the code according to the noiselets algorithm, you can generate an arbitrary matrix of NXN)

二维码的规范，详细说明了二维码的编码方式和过程(qrcode specification)

K-SVD算法训练字典的源码，可以直接调用，也可以修改迭代次数等参数。(K-SVD algorithm to train the dictionary source, can be called directly, or you can modify parameters such as the number of iterations.)

关于径向基的预测，本篇为能见度的预测，可添加其他数据进行其他方面预测。(For the prediction of radial basis, this article is a prediction of visibility, and can add other data to predict other aspects.)

基于卡尔曼滤波的系统目标追踪仿真,其中包括卡尔曼滤波函数、偏差分析函数、状态仿真功能块函数、以及目标追踪系统的simulink.(Including kalman filter function, deviation analysis functions, state simulation function block, and target tracking system of simulink)

传统的kmeans聚类算法不能保证时间序列聚类结果的时序性；基于warp-kmeans聚类算法可以有效处理时间序列的聚类问题，而且复杂度低，迭代次数少。 ，输出有目标函数在每次迭代后的值，聚类中心以及聚类区间。内有测试数据和相关文献，点击 test.m 可以完美运行(The traditional kmeans clustering algorithm can not guarantee the time series of the time series clustering results. The warp-kmeans clustering algorithm can effectively deal with the clustering problem of time series, and the complexity is low, and the number of iterations is less. The output has the value of the target function after each iteration, the clustering center and the clustering interval. There are test data and related documents, click test.m can be perfect operation.)

图论通用工具箱总汇： GraphTheory Toolbox for MATLAB MATLAB图论通用工具箱Studio大集成版 使用说明: 本工具包包含图论常用算法，经过本人测试通过， 其运行效率很高。用户不妨随机产生100*100、 500*500。1000*1000、5000*5000 等等超大型矩阵尝试。 另外本工具包中还附录了一些求解优化问题的程序。(图论通用工具箱总汇： The graph of general toolbox confluence: GraphTheory Toolbox for MATLAB GraphTheory Toolbox for MATLAB MATLAB图论通用工具箱Studio大集成版 General MATLAB graph theory toolbox of Studio integrated version 使用说明: Instructions for use: 本工具包包含图论常用算法，经过本人测试通过， The kit includes the graph theory algorithms, after I test, 其运行效率很高。用户不妨随机产生100*100、 Its operating efficiency is very high. The user can randomly generated 100*100, 500*500。1000*1000、5000*5000 等等超大型矩阵尝试。 500*500. 1000*1000, 5000*5000 and so on super large matrix try. 另外本工具包中还附录了一些求解优化问题的程序。 In addition, the toolkit also appendix some optimization problem solving program. )