tiaoping

判断两幅图是否一样（包括相似图像的判断和完全不一样的图像判断）(Determine whether the two images the same (including judgments and similar images of a completely different image to check))

This is a fast non-iterative ellipse fit, and among fast non-iterative ellipse fits this is the most accurate and robust. It takes the xy-coordinates of data points, and returns the coefficients of the equation of the ellipse: ax^2 + bxy + cy^2 + dx + ey + f = 0, i.e. it returns the vector A=(a,b,c,d,e,f). To convert this vector to the geometric parameters (This is a fast non-iterative ellipse fit, and among fast non-iterative ellipse fits this is the most accurate and robust. It takes the xy-coordinates of data points, and returns the coefficients of the equation of the ellipse: ax^2+ bxy+ cy^2+ dx+ ey+ f = 0, i.e. it returns the vector A=(a,b,c,d,e,f). To convert this vector to the geometric parameters )

MIMO多天线系统仿真程序，分别仿真比较了 AWGN信道 , SISO瑞利衰落信道 , 2发1收Alamouti方案 , 2发2收Alamouti方案 (MIMO multi-antenna system simulation program, were simulated and compared the AWGN channel , SISO Rayleigh fading channels , two fat a close Alamouti scheme , two 2 admission Alamouti scheme )

AVRSTUDIO设置熔丝位加密内容，希望对大家有帮助！(AVRSTUDIO set fuse bits encrypted content, we want to help!)

fast ICA的源文件 独立成分分析 MATLAB工具箱里也有 可以下载到工具箱 安装后就可以使用了(fast ICA Independent component analysis of the source file MATLAB toolbox is also available for download to install, ready to use the toolbox)

说明：  bpsk仿真中间有两个方面的内容，很好的仿真软件(There are two files in the zip folder. bpsk_spread.m and jakesmodel.m Steps for simulation: 1] Run jakesmodel.m first 2] Then run bpsk_spread.m . 3] Note that during the first run bpsk_spread.m has no rayleigh fading.This is because the corresponding code has been commented 4] The resulting performance is stored in BER_awgn. 5] Now uncomment the Rayleigh Fading code in bpsk_spread.m file. 6] Same time comment BER_awgn (line 112) and uncomment BER_ray variable. 7] Run the simulation. )

MIT归一化算法，基于MIT自适应律的模型参考自适应模型，对自适应律进行了归一化处理，消除输入对系统稳定性的影响(MIT normalization algorithm, MIT adaptive law based model reference adaptive model of adaptive law were normalized to eliminate the influence of input on system stability)

alamouti encoding schemes

2X2 MIMO系统使用ML（最大似然）接受。（验证可用）(2X2 MIMO system using the ML (maximum likelihood) to accept. (Verification can be used))

Recognition of face images