图像矩阵matlab代码-cuda-rpca-admm:使用ADMM进行优化以实现前景背景分离的鲁棒PCA的CUDA实现

GENERATING MATRIX Use the generate_matrix.m file to generate a random matrix of a specified size and a particular rank Command- `generate_matrix(25344, 200, 1);` Here 25344 corresponds to the image size (144 x 176) and 200 corresponds to the number of frames in the video Note that the first dimension should be greater than the second one in generate_matrix() for our algorithm to work. (25344 > 200) This command will generate a 200A.dat file, which will serve as input to our RPCA algorithm RUNNING RPCA USING ADMM USING MATLAB From MATLAB, use the admm_example.m file to run ADMM for RPCA. Provide the matrix generated in the previous step as input. Command- `admm_example('200A.dat');` This command will run admm and write the output matrices into three different files named like boyd_X1.dat etc.. RUNNING RPCA USING ADMM USING CUDA For CUDA code, use the script compile_and_run.sh to compile the code and run the file. Provide the input matrix as an argument to this script. Command- `./compile_and_run.sh 200A.dat` This command will run the CUDA code for RPCA and write output to files named like X1_out.dat, etc.. Other files include MATLAB files to convert output into videos.