1.Bayesian-Reasoning-and-Machine-Learning

用matlab写的BP网络辨识函数，非常有用。(this is a program with matlab)

对平面波通过结构的仿真，有TE模和TM模两种模式(Plane wave through the structure of the simulation, the TE mode and TM mode in two modes)

描述旋转体目标的微动特性，完成对旋转体目标的微多普勒仿真(Micro-Doppler Signature of a Spining Target)

plot bit error rate at differnt SNR

LDPC仿真的一些列子，自己编写的，可能有一定错误，需要修改(Some Lie LDPC simulation, their preparation, may have some errors, you need to modify)

优点：1.对于信噪比高的信号滤波效果好； ％ 2.对于边沿的保护强过阈值滤波，不会产生阈值滤波情况下的过于平滑与Gibbs现象。 ％缺点：1.由于对边沿信号没做任何处理，所以边沿可能会有脉冲噪声保留下来； ％ 2.计算相关系数中，如果计算出来的小波系数点位置偏差大，则相关系数计算受影响； ％ 3.需要迭代运算，迭代的噪声能量阈值选取很重要，这里以开始段无信号处估计噪声； ％ 4.需要迭代运算，所以运算量比阈值法大； ％ 5.受分解层次影响，在大尺度上小波系数点位置偏差更大，相关系数计算不准确。 ％需要具体调整的地方：1.分解的尺度；()

认知无线电当中非合作吞吐量与感知时间的关系，可以在Matlab环境中运行(Cognitive radio which the throughput of non-cooperation with the relationship of perceived time, you can run in the Matlab environment)

稀疏表示经典著作 John Wright et al, Robust Face Recognition via Sparse Representation , PAMI 2009的程序(# impFaceRecognition A Matlab implementation of Face Recognition using Sparse Representation the original paper: John Wright et al, Robust Face Recognition via Sparse Representation , PAMI 2009. In our implementation, we propose a Multi-scale Sparse Representation to improve the performance compared to the original paper. If you use our code, please cite the paper: Multi-scale Sparse Representation for Robust Face Recognition )

this is a folder containing algorithms and source codes for face recognition

svpwm的源代码实现，对于正在做矢量控制系统的同志很有帮助，大家支持呀。(svpwm the source code for the vector control system is doing useful comrades, we support ah.)