资源列表
MIMO-OFDM
- 内含多个MIMO-OFDM信道评估程序：MIMO-OFDM不同信道估计的对比、OFDMexample(程序源码和SIMULINK平台仿真)等！-Contains multiple MIMO-OFDM channel assessment procedure: MIMO-OFDM channel estimation with different contrast, OFDMexample (program source code and SIMULINK simulation platform)
yalmip
- 国外专家做的求解LMI鲁棒控制的工具箱,可以相对高效的解决LMI问题-foreign tool box of matlab,good method to solve problem of robust LMI
StereoMatching
- 在Matlab平台上，通过NCC SSD SAD算法双目立体图像求视差图-In the Matlab platform, through the NCC SSD SAD algorithm for stereo disparity map image requesting
WuYufei_matlab
- turbo码研究人员不可避免的吴宇飞的升级版程序，对turbo码的算法和其他思想的结合，仿真效果对学好turbo码是一个捷径-turbo codes researchers an upgraded version of inevitable Wu Yufei procedures, turbo code algorithm and a combination of other ideas, simulation results of turbo code is a shortcut to lea
matlab
- C-W节约法的matlab实现源代码，解决vrp问题-CW Conservation Act of matlab implementation source code, to solve the problem vrp
vsp_forward
- 井中地震正演程序，matlab程序编写-Borehole seismic forward procedure, matlab programming
ssim
- matlab code of ssim of image quality
压缩感知的几种重构算法比较的源代码
- 压缩感知的几种重构算法比较的源代码 有OMP CoSaMP SP等 现有算法包括的比较全-Several compressed sensing reconstruction algorithm to compare the source code has OMP CoSaMP SP comparison of other existing algorithms, including full-
SAMP
- 压缩感知中的稀疏度自适应算法，针对稀疏度未知的情况进行迭代-sparsity adaptive matching pursuit
HOG
- 这是最简洁，注释得最好的HOG(Histogram Oriented Gradient)算法的matlab实现。可用于行人识别和物体跟踪。-This code is well commented, which enables the adjusting of the HOG parameters. This code was developed for the work: O. Ludwig, D. Delgado, V. Goncalves, and U. Nunes, Trainable
parzen
- 二维数据集Parzen方窗非参数估计PDF(概率密度函数)，三维结果显示，有图，有完整说明文档和程序运行说明，matlab编程环境，此为模式识别小作业 parzen-Dimensional data set Parzen Window non-parametric estimation side PDF (probability density function), three-dimensional results show that map, with complete documentat
HHTMatlab
- 该文件中包含HHT（希尔伯特黄变换）的三种MATLAB程序，可以直接使用，非常方便，效果也不错。并附有相关网站。-The file contains the HHT (Hilbert-Huang Transform) of the three MATLAB program that can be used directly, very convenient with good results. Together with related sites.