BP

MATLAB二维图像处理程序，是个例子，可以学习一下(MATLAB two-dimensional FFT image treatment procedures, are an example, you can study what)

该压缩包包含了“信号与系统分析及MATLAB实现”一书的所有程序； (The archive contains a " signal and system analysis and MATLAB to achieve" a book of all programs )

说明：  二维无网格EFG计算程序，由MLS方法生成新函数(Two-dimensional meshless EFG computer program to generate a new function by the MLS method)

基于遗传算法的组卷设计，此为书籍版本。。。。(Design based on genetic algorithm test paper, this is the book version. . . .)

应用matlab进行数独解密的算法和教程，英文版，来自matlab创始人(The Userguide to use matlab to solve sudoku)

matlab源代码，是非负矩阵分解工具箱，包含乘法更新，最小二乘约束，投影梯度法等方法(Usage: [W,H] = nmf(X,K,alg,maxiter,speak) W: output matrix H: output matrix X: input matrix K: number of components alg: algorithm to use maxiter: maximum number of iterations speak: print to screen Algorithms: mm: Multiplicative updates method using euclidean distance measure. cjlin: Projected gradient method prob: Probabilistic non-negative matrix factorization. als: Alternating least squares. alsobs: Alternating least squares with optimal brain surgeon. Demonstrations: PET: NMF on a PET dataset Text: NMF used on a three different datasets Email, medical, and CNN. Algorithms mm: Multiplicative update method using euclidean distance measure. Described in Lee and Seung, 2001, Algorithms for Non-negative Matrix Factorization, Advances in Neural Information Processing Systems 13, 556-562. This algorithm is the most commonly used algorithm to solve NMF. cjlin: Alternative non-negative least squares using projected gradients. Author: Chih-Je)

在matlab平台上编写的基于SIMP和OC法的拓扑优化程序(topology optimization based on SIPM and OC)

说明：  自适应滤波matlab程序自适应滤波matlab程序(Adaptive filtering adaptive filtering matlab matlab process procedures)

全变差图像处理Matlab程序，for the paper: "Algorithms and Software for Total Variation Image Reconstruction via First-Order Methods, Numerical Algorithms"(Software for Total Variation Image Reconstruction (for Matlab Version 7.5 or later) "mxTV" is a software package for image reconstruction based on the Total Variation model, and including denoising, inpainting, and deblurring. The work was carried out as part of the project CSI: Computational Science in Imaging, funded by the Danish Research Council for Technology and Production Sciences, and headed by Prof. Per Christian Hansen, DTU Informatics. The collaborators are DTU Informatics, Dept. of Electronic Systems at Aalborg University, and MOSEK ApS. The underlying algorithms are based on recently published first-order methods developed by Nesterov, tailored specifically to the image restoration problems. These methods have O(1/ε) complexity, where ε is the accuracy of the solution. The core computational routines are written in C, with a mex interface to Matlab. The algorithms and the software are described in the paper: J. Dahl, P. C. Hansen, S. H. Jensen, and T. L. Jensen, Alg)

说明：  这是一个基于蚁群智能算法的组播QOS路由问题程序代码。(This is a multicast QoS problem based on AC.)