try_fxlms

此程序功能运行后可以得到比较好的结果，请好好运行下！(matlab)

自动控制经典 S离控制模型 matlab S sample control (matlab S sample control )

电力线通信是现在家用通信的一种，在PLC通信的研究中，对信道的研究是至关重要的。改代码主要包括多径信道和噪声模型matlab代码，是目前最常用的模型。(Power line communication is now a kind of home communication, in the PLC communication research, the channel research is essential. Change the code mainly include multipath channel and noise model matlab code, is the most commonly used model.)

利用小波变化，实现两幅前后景清晰度不同的图像的融合，获得一副清晰图像(Using wavelet transform, to achieve two different images before and after the King definition of integration, access to a clear picture)

拉格朗日内插法的matlab实现 改进后可用于多种用途(Matlab Lagrange interpolation method can be used to achieve the improved multi-purpose)

The algorithms are coded in a way that makes it trivial to apply them to other problems. Several generic routines for resampling are provided. The derivation and details are presented in: Rudolph van der Merwe, Arnaud Doucet, Nando de Freitas and Eric Wan. The Unscented Particle Filter. Technical report CUED/F-INFENG/TR 380, Cambridge University Department of Engineering, May 2000. After downloading the file, type "tar -xf upf_demos.tar" to uncompress it. This creates the directory webalgorithm containing the required m files. Go to this directory, load matlab5 and type "demo_MC" for the demo. (The algorithms are coded in a way that makes it trivial to apply them to other problems. Several generic routines for resampling are provided. The derivation and details are presented in: Rudolph van der Merwe, Arnaud Doucet, Nando de Freitas and Eric Wan. The Unscented Particle Filter. Technical report CUED/F-INFENG/TR 380, Cambridge University Department of Engineering, May 2000. After downloading the file, type "tar-xf upf_demos.tar" to uncompress it. This creates the directory webalgorithm containing the required m files. Go to this directory, load matlab5 and type "demo_MC" for the demo. )

This a a sphere decoding function. It has low complexity.

是一个人脸识别系统，过程非常详细，对学习非常有帮助(Is a face recognition system, the process is very detailed and very helpful in learning)

rayleigh channel simulation

K-mean clustering. hope you enjoy