资源列表
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.
QPSKcyclicspectral
- MPSK信号基于高阶循环谱估计载波频率matlab的代码-MPSK signals based on higher-order cycle of the carrier frequency spectrum estimation matlab code
signal_decomposition_MP
- 稀疏信号分解利用匹配追踪算法，主程序+调用函数-Sparse signal decomposition, the main program calls the function+
XMicroWaveJiXian
- ＭＯＲＬＥＴ小波脊线提取程序，实现信号小波脊线提取-MORLET wavelet ridge extraction procedures to achieve wavelet ridge extraction
Levenberg-Marquardt
- Levenberg-Marquardt 信赖域方法求解非线性方程组的Matlab程序-Levenberg-Marquardt trust region method for solving nonlinear equations of the Matlab program
eemd
- 这是2009年huang在EMD基础上改进的算法EEMD的matlab代码！-the matlab code for EEMD！
read_file.dat_and_file.hea_by_matlab
- 使用matlab读取心电、血压等采集数据.dat和.hea文件，并分图标注显示。内有详细程序说明和读取实例-Using matlab to read ECG, blood pressure and other data collection. Dat and. Hea files and sub-icon Note display. There are detailed instructions and read the example programs
MATLAB-ISAR-Turntable-imaging
- 仿真了转台目标，并进行了R-D算法仿真。 -Simulation of the turntable-goal and the RD algorithm simulation.
bsscompare
- 瞬时混合盲信号分离问题的自适应算法比较。 有论文，有程序，自己写的，有输入波形，有输出结果，适合完成学习盲分离。-Instantaneous Blind Signal Separation Mixed Adaptive Algorithm for comparison. A paper, a procedure that he wrote with input waveforms, the results are output for the completion of learning b