home_work

foeward featurrselection

Turbo码仿真程序。有Turbo码的编码，MAP算法，迭代译码，删余和没删余的。(Turbo code simulation program. Turbo codes have coding, MAP algorithm, iterative decoding, censored and no more than delete the remaining.)

摘要:本算法是在经典 Sobel算子基础上 ,结合汽车本身的实际情况 ,增加了 6个方向模板 ,同时利用基于 L范数的各同性扩散去噪模型消除噪声 ,最终得出汽车轮廓图。仿真结果表明:该算法对汽车图像的噪声干扰 有较强的抑制能力 ,汽车轮廓提取定位更准 ,精度更高 ,图像更清晰。 关键词:边缘检测算法 车辆轮廓 噪声 Sobel算子

稳态侧偏刷子模型，考虑了垂直载荷分布情况的不同，分别进行了程序计算。(Tire model for the shuazi model, it can calculate for differnt Fz)

matlab 高级应用的一些例子，希望对大家有所帮助(matlab examples of advanced applications, we hope to help)

说明：  mpc control for systeme

基于MATLAB模糊控制下二阶系统的阶跃响应(MATLAB Fuzzy control based on the step response of second-order system)

It plots the BER vs SNR for PSK and QAM

说明：  盲源分离FastICA、matalab程序，(FAST KERNEL ICA | |--------------------| Version 1.0- February 2007 Copyright 2007 Stefanie Jegelka, Hao Shen, Arthur Gretton This package contains a Matlab implementation of the Fast Kernel ICA algorithm as described in [1]. Kernel ICA is based on minimizing a kernel measure of statistical independence, namely the Hilbert-Schmidt norm of the covariance operator in feature space (see [3]: this is called HSIC). Given an (n x m) matrix W of n samples from m mixed sources, the goal is to find a demixing matrix X such that the dependence between the estimated unmixed sources X *W is minimal. FastKICA uses an approximate Newton method to perfom this optimization. For more information on the algorithm, read [1], and for more information on HSIC, refer to [3]. The functions chol_gauss and amariD are taken from and based on, respectively, code from Francis Bach (available at http://cmm.ensmp.fr/~bach/kernel-ica/index.htm). The derivative is com)

说明：  gmsk调制解调的实现，matlab仿真(gmsk modem implementation, matlab simulation)