kc_h

利用C_API的基于RTW实时仿真系统在线调参(C_API the use of real-time simulation-based RTW Online Scheduling System)

能够把输入信号分解为多个IMF分量，并进行Hilbert变换，求得信号的时频分布谱图。(Be able to input signal is decomposed into several IMF components and carry out Hilbert transform, time-frequency distribution obtained spectrum.)

刘金琨教授写《滑模变结构控制matlab仿真》随书程序源码(Professor Liu Jinkun write " Sliding Mode Control matlab simulation" program source code with the book)

基于VUMAT的粘弹性本构模型应力更新编程和单元失效准则以及失效单元删除(element delete)

说明：  回波数据进行二位FFT处理结果和CFAR处理后结果对比(Comparison of the results of two-bit FFT and CFAR processing for echo data)

1,通用变频器的建模和参数设置 2,通用变频器的工作原理介绍(1，Universal inverter modeling and parameter set 2, Universal inverter works)

利用Matlab软件编写的轨道不平顺数据分析程序能够对轨检车测得的不平顺数据进行处理,得到功率谱密度分布函数.轨道不平顺分析程序包括轨道不平顺数据预处理、轨道不平顺谱分布函数计算以及根据实测的车体振动加速度,对轨道不平顺与车体振动加速度进行相干分析、提出对行车运行有不利影响的不平顺波长范围等.研究结果表明:车辆的动力特性与轨道不平顺有密切关系.高低不平顺对车体垂向振动影响显著,轨向不平顺对车体水平振动影响显著,水平不平顺对列车垂向、横向振动均有显著影响.(Matlab software written track irregularity data analysis program able to track inspection car irregularity measured data are processed to obtain the power spectral density function. Track Irregularities track irregularity analysis procedures including data preprocessing, track irregularity spectrum distribution function calculations, and based on the measured vibration acceleration of the vehicle, with the body of track irregularity acceleration coherent analysis, have an adverse impact on traffic running irregularity wavelength range, etc. the results show that: the dynamic characteristics of the vehicle and the track irregularity closely related. rough along the vertical vibration of the vehicle significantly, rail irregularity vibration to levels significantly affect the body, the level of irregularity to train the vertical and horizontal vibration significantly affected.)

Matlab Fuzzy k-Nearest Neighbor 分类算法(Fuzzy k-Nearest Neighbor Classification Algorithm)

（7，4）汉明码的编译码程序，基于MTLAB语言(Encoding and decoding procedures of （7，4）Hamming code)

matlab code for Fit all valid parametric probability distributions to data