SEP

车牌识别程序 从图片中自动获取车牌号码 完成定位和识别(License plate recognition program from pictures automatically locate and obtain the license plate numbers to complete identification)

Robust receding horizon predictive control for systems with uncertain dynamics and input saturation

The guided filter can be used as an edge-preserving smoothing operator like the popular bilateral filter, but has better behaviors near edges. The guided filter is also a more generic concept beyond smoothing: it can transfer the structures of the guidance image to the filtering output, enabling new filtering applications like dehazing and guided feathering. Moreover, the guided filter naturally has a fast and non-approximate linear time algorithm, regardless of the kernel size and the intensity range. Currently it is one of the fastest edge-preserving filters.

拉普拉斯特征映射,最大差异展开，时频域特征(Laplacian Eigenmap Maximum difference expansion Fast Maximum difference expansion ISOMAP)

This function performs one-dimensional (Cartesian) finite-difference time-domain simulations. It assumes the spatial grid extends from k = 1 to k = Nz and that the simulation runs for nSteps time steps.(1D-FDTD-program(matlab) This function performs one-dimensional (Cartesian) finite-difference time-domain simulations. It assumes the spatial grid extends from k = 1 to k = Nz and that the simulation runs for nSteps time steps.)

客体复原代数重构算法的matlab实现。(Algebraic reconstruction algorithm object recovery matlab implementation.)

采用MATLAB编写的牛顿法插值程序，在《数值计算》测试算例中调试通过。(An interpolation program using Newton method in MATLAB, the validity of which has been verified in the standard numerical test.)

GM_PHD_Filter Version 1.09, 13th December 2013 Matlab code by Bryan Clarke b.clarke@acfr.usyd.edu.au with: - some Kalman filter update code by Tim Bailey, taken from his website http://www-personal.acfr.usyd.edu.au/tbailey/software/ - error_ellipse by AJ Johnson, taken from Matlab Central http://www.mathworks.com.au/matlabcentral/fileexchange/4705-errorellipse Algorithm by Ba-Ngu Vo & Wing-Kin Ma in: B.-N. Vo, W.-K. Ma, "The Gaussian Mixture Probability Hypothesis Density Filter", IEEE Transactions on Signal Processing, Vol 54, No. 11, November 2006, pp4091-4104 This is an implementation of a gaussian mixture probability hypothesis density filter (GM-PHD) for a simulated tracking problem. The problem specification is given in the above paper - in summary, two targets move through the environment, there is a lot of clutter on the measurement, and about halfway through a third target spawns off one of the two targets.(GM_PHD_Filter Version 1.09, 13th December 2013 Matlab code by Bryan Clarke b.clarke@acfr.usyd.edu.au with: - some Kalman filter update code by Tim Bailey, taken from his website http://www-personal.acfr.usyd.edu.au/tbailey/software/ - error_ellipse by AJ Johnson, taken from Matlab Central http://www.mathworks.com.au/matlabcentral/fileexchange/4705-errorellipse Algorithm by Ba-Ngu Vo & Wing-Kin Ma in: B.-N. Vo, W.-K. Ma, "The Gaussian Mixture Probability Hypothesis Density Filter", IEEE Transactions on Signal Processing, Vol 54, No. 11, November 2006, pp4091-4104 This is an implementation of a gaussian mixture probability hypothesis density filter (GM-PHD) for a simulated tracking problem. The problem specification is given in the above paper- in summary, two targets move through the environment, there is a lot of clutter on the measurement, and about halfway through a third target spawns off one of the two targets.)

自适应程序matlab代码，有详细说明，很不错，适合初学者！(Adaptive procedure matlab code, a detailed description, it is good for beginners!)

LDPC编码算法, Create R = 1/2 low density parity check matrix M : Number of row N : Number of column method : Method for distributing non-zero element {0} Evencol : For each column, place 1s uniformly at random {1} Evenboth: For each column and row, place 1s uniformly at random noCyle : Length-4 cycle {0} Ignore (do nothing) {1} Eliminate onePerCol: Number of ones per column H : Low density parity check matrix(LDPC_code source Create R = 1/2 low density parity check matrix M : Number of row N : Number of column method : Method for distributing non-zero element {0} Evencol : For each column, place 1s uniformly at random {1} Evenboth: For each column and row, place 1s uniformly at random noCyle : Length-4 cycle {0} Ignore (do nothing) {1} Eliminate onePerCol: Number of ones per column H : Low density parity check matrix)