m_k_plot

This program is used to analyze the effects of the spreading factor on the performance of MC-CDMA system.

matlab小程序，实现曲线的自动拟合，采用傅里叶拟合方程(matlab small program to achieve the automatic curve fitting, Fourier fitting equation)

利用matlab建立了一个混合动力电动汽车模型，其中包括电子、动力传动系统、电气系统的物理模型仿真模块组，可配置为系统级测试或电能质量分析。压缩包内含2011-2016各版本，具体可阅读自述文件。(Using matlab built a hybrid electric vehicle models, including the physical model simulation module group in electronics, powertrain, electrical system can be configured for system level testing or power quality analysis. 2011-2016 archive contains versions, specifically, read the README file)

基于MATLAB,用PQ分解法计算电力系统潮流(Solutions trend calculated using PQ decomposition method)

说明：  按照信息论基本原理的解释，信息是系统有序程度的一个度量，熵是系统无序程度的一个度量；如果指标的信息熵越小，该指标提供的信息量越大，在综合评价中所起作用理当越大，权重就应该越高。因此，可利用信息熵这个工具，计算出各个指标的权重，为多指标综合评价提供依据。(According to the interpretation of the basic principles of information theory, information is a measure of the degree of orderliness of the system, and entropy is a measure of the degree of disorder of the system. If the information entropy of the index is smaller, the amount of information provided by the index is larger, and the role of the index in the comprehensive evaluation should be greater, the weight should be higher. Therefore, we can use the tool of information entropy to calculate the weight of each index, and provide a basis for the comprehensive evaluation of multiple indicators.)

Image warping Face.It is done in matlab.

永磁同步电机系统的滑模观测器设计，非常实用，算法很先进(Sliding model observer based Permanent Magnet Synchronous Motor)

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)

matlab matrix processing functions

采用GA对神经网络的权值与阀值进行优化，得到效果更好的网络(GA uses neural networks for weights and thresholds are optimized to get better network)