Gaussian

canny算子边缘检测源码，用matlab实现，如果需要，请及时下载(canny edge detection source, using matlab to achieve, if you need, please download)

说明：  On empirical mode decomposition and its algorithms.pdf

RSA公钥密码加密算法程序实现，matlab程序，运行正确。(The algorithm program, RSA public key cipher encryption matlab program, run the correct.)

3GPP组织给出的LTE系统高层无线资源控制RRC层规范，希望帮到LTERRC层爱好者。(3GPP LTE system tissue senior radio resource control (RRC) layer specification given, I hope to help LTERRC layer enthusiasts.)

IEC61400-1第三版 极限载荷外推(wind turbine load extrapolation for iec 61400-1,2005)

实现PET/SPECT 幻影图像regression的matlab源代码 algorithms for Poisson emission tomography PET/SPECT/ Poisson regression eml_ emission maximum likelihood eql_ emission quadratically penalized likelihood epl_ emission penalized likelihood(The realization of PET/SPECT images Mirage regression of matlab source code algorithms for Poisson emission tomography PET/SPECT/Poisson regression eml_ emission maximum likelihood eql_ emission quadratically penalized likelihood epl_ emission penalized likelihood)

Demodulating a BPSK using Costas Loop

Matlab implmentation of Golden Section method used in unconstrained optimization for a single variable

1. It is necessary you have defined on Matlab the X - data matrix. Size of matrix must be n-by-(1+p) sample=column 1, variables=column 2:p). And alpha - significance (default = 0.05). 2. For running this file it is necessary to call the rafisher function as PROFANA(X,alpha). Please see the help PROFANA. 3. Once you input the arguments, it will appears your results. ( 1. It is necessary you have defined on Matlab the X- data matrix. Size of matrix must be n-by-(1+p) sample=column 1, variables=column 2:p). And alpha- significance (default = 0.05). 2. For running this file it is necessary to call the rafisher function as PROFANA(X,alpha). Please see the help PROFANA. 3. Once you input the arguments, it will appears your results. )

系统辨识函数的介绍，包括最小二乘法，和辅助变量法(Introduction to system identification function, including the least squares method, and the instrumental variable method)