adaboost1

详细的MATLAB 设计参考，不错的参考资料 ！！！！！！！！！(very good)

matlab仿真的，功能是实现相关峰值的提取。能够在低信噪比下得到效果较好的相关峰(matlab simulation, feature extraction is to achieve correlation peak. Able to get better low SNR correlation peak)

用Matlab实现小波变换，进行图像压缩(Using Matlab achieve wavelet transform for image compression)

实现单端反激的matlab实现，运行过好用的源程序(Single-ended flyback realize matlab, run over useful source)

That code is done for Load flow.the basic tool for power system, based on Newton Raphson method

基于矩阵理论，根据最小二乘法进行的椭圆曲线拟合的matlab程序(ellipse fit theory of matrix least square)

Smooths a matrix (with/without NaN s) via recursive moving average method and eliminates data gaps. (MOVING_AVERAGE(X,F) smooths the vector data X with a boxcar window of size 2F+1, i.e., by means of averaging each element with the F elements at his right and the F elements at his left. The extreme elements are also averaged but with less data, obviously. Leaving the edges intact. The method is really fast. MOVING_AVERAGE2(X,M,N) smooths the matrix X with a boxcar window of size (2M+1)x(2N+1), i.e., by means of averaging each element with its surrounding elements that fits in the mentioned box centered on it. This one is also really fast. The elements at the edges are averaged too, but the corners are left intact. NANMOVING_AVERAGE(X,F) or NANMOVING_AVERAGE(X,F,1) accept NaN s elements in the vector X the latter interpolates also those NaN s elements surrounded by numeric elements. NANMOVING_AVERAGE2(X,M,N) or NANMOVING_AVERAGE2(X,M,N,1) accept elements NaN s in the matrix X the latter interpolates also those NaN elements surrounded by numeric elements.)

matlab仿真命令集，我的资料和大家共享一下，希望对大家能够有所帮助(Matlab simulation command set, and the information I share that hope to be able to help you)

This is code for QRS peak detection in ECG signal. An ECG signal is generated and it is been filtered. The output is Filtered output.

实现灰色关联分析的简单有效的matlab程序，运用熵权法求各指标的权重(Gray correlation analysis to achieve a simple and effective matlab program, using entropy method the weights of each index)