combind-program

內有Directional以及Derivative Constraints的形式，讓LCMV和LPMV 能夠更精準估測出其JAMMER之位置(There are Directional and Derivative Constraints in the form, so that LCMV and LPMV to more accurately estimate the location out of their JAMMER)

MA（q)模型新息估计方法MATLAB例程(MA (q) model is estimated that the new method of income MATLAB routine)

基于模型的风力发电机资料，有需要的学习一下吧(Model-based wind turbine data, there is a need to learn about it)

matlab 关于association rule 的自己写的函数，有3个文件, association.m：h = association(m, i, j) i=>j, m是数据，h是support和confidence，该函数只适用于单个数据 ass_item: h=ass_itset(m, a, b) 同上，但是可用于多个数据（m为数组） assrule: h = assrule(m, threshold1, threshold2) 该函数用于classification， 得到规则，threshold1为要求的support,threshold2为要求的confidence，h 则为符合要求的规则及其support和confidence，前2列为规则，后2列为其support和confidence (matlab on the association rule to write functions, there are 3 files, association.m: h = association (m, i, j) i => j, m is the data, h is the support and confidence, this function applies only to a single Data ass_item: h = ass_itset (m, a, b) it is the same as above, but it can be used for multiple data (m can be matrix) assrule: h = assrule (m, threshold1, threshold2) the function used for classification,get the rules, threshold1 is the require of support, threshold2 is the required of confidence, h is the rules and their support and confidence, the former two columns as a rule, the latter two columns as one of its support and confidence)

malarial detention parasites related matlab code you can find image segmentation techniques

一个自己搭建的普通的pscad仿真模型，方便初学者了解pscad相关的原件(One he has built himself an ordinary pscad simulation model, easy for beginners to understand the relevant original pscad)

this is an important project for the identification of a a servo motor for a sun tracker

这是偏微分方程在图像处理中的应用一书的配套光盘，非常好的东东哦(This is a partial differential equations in image processing applications supporting CD-ROM book, very good stuff oh)

matlab数字信号与应用源代码4，对初学者有帮助(and application of digital signal matlab source code 4, help for beginners)

两信号的互相关一致性的分析,很有用处,用在高阶谱方面的(two inter-related signals in the consistency of analysis, useful, the use of higher-order spectrum)