toolbox_nlmeans

最小均方（LMS）自适应算法就是一中已期望响应和滤波输出信号之间误差的均方值最小为准的，依据输入信号在迭代过程中估计梯度矢量，并更新权系数以达到最优的自适应迭代算法。LMS算法是一种梯度最速下降方法，其显著的特点是它的简单性。这算法不需要计算相应的相关函数，也不需要进行矩阵运算。(Minimum mean-square (LMS) adaptive algorithm is that one has to respond to the expectations and filtering the output signal of the mean square error between the value of the minimum-based, based on the input signal is estimated in the iterative process of gradient vector, and to update the weights in order to achieve the most Adaptive iterative algorithm gifted. LMS algorithm is a steepest descent gradient method, and its significant features is its simplicity. This algorithm does not require calculation of the corresponding correlation function, nor the need for matrix calculation.)

DFIG 模型 带简化版的crowbar。其中包括convertors与其相应的控制。(dfig model with simple crowbar)

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. )

matlab 语言，《先进pid控制matlab仿真》光盘源码(matlab code，《Advanced Matlab PID control similution》DVD original code.)

matlab code for beging cc motor...

system encryption matlab code using advanced system

calculate joint entropy of two images

LDA是人脸识别中比较基础的一个算法，在人脸识别中使用较广(Comparison of LDA in face recognition are based on an algorithm used in face recognition broader)

说明：  用matlab做成的维纳滤波器程序，跟踪先验信噪比使用直接判决的方法进行滤波(Made use of the Wiener filter matlab program to track a priori signal to noise ratio using a direct method of filtering decision)

用蚁群算法解决中国旅行商问题，用matlab编程，内含数据，已经运行了(China solving the traveling salesman problem with ant colony algorithm, matlab programming, containing the data, has been running)