BCI competition 2008 dataII

一种基于支撑矢量积（SVM）的码头检测算法，可以针对高分辨率遥感图像。(A plot based on support vector (SVM) of the terminal detection algorithm that allows high-resolution remote sensing imagery.)

P0303：采用灰度变换的方法增强图像的对比度 P0304：直方图均匀化 (P0303: using gray transform method to enhance the contrast of the image P0304: histogram equalization)

A matlab tutorial to design PMSM motor speed control systems

MATLAB主成分分析法,对于数学建模的同学很有帮助(PCA MATLAB)

可以实现血管增强滤波，首先运行初始化文件，然后运行主函数文件（论文参考：Three Dimensional Curvilinear Structure Detection Using Optimally Oriented Flux）(Vascular enhancement filtering can be achieved, first run the initialization file, and then run the main function file)

此程序为解非线性方程组的逆Broyden秩1迭代法，为MATLAB源程序(This procedure for the solution of nonlinear equations inverse Broyden iteration rank 1 for MATLAB source code)

计盒分形维数计算的matlab源代码编程实现过程(Function [Fdgen NoisfreFD ]=fractaldim(y,Q,M) __________________________________________________________________________ Usage: Computes fractal dimension by box counting(BC) method. NOTE: Running the code may take a little time, because it calculates dimensions for all embedding dimensions up to M. This code is based on an algorithm that constructs a box for the first observation and for other observations test which it belongs to previous box(s). If the observation belongs to one of the existent boxes then increases number of points in the relevant box,otherwise makes a new box. the algorithm of this code uses only rounding down and it does not need binary coding, sorting and so on. It uses only transformation data to [0,2^32-1] and finding valid boxes based on Leibovich and Toth(1989). Inputs: y is a vector time series. q stands for generalized dimension q=1 entropy dimension,q=2 correlation dimension and so on. q=0 is box counting dimen)

This file shows CVIP paper

MATLAB implementation of SPIHT (without Arithmatic coding stage). ％ Performance evaluation : this toolbox VS. SPIHT ％ Test image: lena512.raw ％ bpp SPIHT(dB) This code(dB) ％ 0.1000 29.8107 29.3202 ％ 0.2000 32.7202 32.2514 ％ 0.3000 34.5479 34.0331 ％ 0.4000 35.8422 35.4857 ％ 0.5000 36.8623 36.5939 ％ 0.6000 37.6650 37.3759 ％ 0.7000 38.2581 38.0491 ％ 0.8000 38.9390 38.7058 ％ 0.9000 39.5218 39.3437 (MATLAB implementation of SPIHT (without A rithmatic coding stage). Performance evalua% tion : this toolbox VS. SPIHT%% Test image : lena512.raw%% bpp SPIHT (dB) This code (dB)% 0. 1000 29.8107 32.7202 0.2000 29.3202% 32.2514% 0.3000 0.4000 34.5479 34.0331% 35.8422 35.485 7% 0.5000 0.6000 36.8623 36.5939% 37.6650 37.3 759% 38.0491% 0.7000 0.8000 38.2581 38.9390 38 .7058 0.9000 39.5218 39.3437%)

This file can be used in matlab to implement easy fft. it is very effective and good method to implement easy fft.