fusion_WT

A sample code for matrix multiplication in C

实现多模态过程监测功能,包括数据的预处理，标准化处理等(multimode process detection)

针对三相桥式整流电路的谐波和无功功率的特点，提出几种滤波方案，并进行比较，最终确定了用有源滤波方案。对于有源滤波器，本论文从结构上比较后选用并联电压型有源滤波器。(The thesis introduces several kind of filter schemes, which is aimed at the harmonic characteristic of three-phase bridge rectifier circuit .After comparison,the thesis chooses the active filter scheme,in view of the active filter, after the comparesion of structure,finally, the thesis chooses the parallel-voltage active filter.)

How to avoid overfitting in neural networks

本代码实现了人工鱼群算法（ASFA.m）,并用该算法寻找Sphere函数的极小值(This is a ASFA .)

粒子滤波案例，结构有待改进,希望大家提点意见谢谢(the particle filtering method which needs to be modified by others)

ECG on mathematical test taken on 250 Hz (sampling frequency) You can use in order to obtain (and compare) the stress (from HRV)

Cross entropy program for mvgm

this is the matlab simulation for BER exaction

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)