cnvjiaozhi

这是一个讲解OFDM原理及实现的文档，文档最后附上了matlab的OFDM实现(This is an OFDM explain the principle and implementation of the document, the document was last attached matlab implementation of the OFDM)

说明：  轮廓图真彩图与三维表面的MATLAB程序。希望对大家有帮助。(True color contour map and three-dimensional surface of the MATLAB program. We want to help.)

智能控制中的离线模糊计算，用于计算模糊控制表(Intelligent Control of off-line fuzzy calculation，Used to calculate the fuzzy control table)

水声kraken模型程序的使用说明性文章，详细讲解了kraken模型原理以及程序包的使用，非常经典，本站基本找不到类似的！(Acoustic kraken model program using descriptive article gave a detailed kraken model principle and the use of the package, very classic, basic can not find a similar site!)

针对弧齿锥齿轮的matlab编程，不过中间还有些问题(Matlab programming for spiral bevel gears, but the middle still have some questions)

matlab中傅里叶变化的一个例子，希望对大家有用(fourier transform example)

脉冲幅度调制解调 实验操作 实验原理 实验注意事项(Pulse amplitude modulation and demodulation principle experiment experimental experimental operation precautions)

pammode function in matlab

关于turbo码编码的仿真程序，简单实用，是初学者的理想程序(On the turbo coding of the simulation program, simple and practical, is the ideal program for beginners)

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)