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以新型混沌系统———Liu系统为例,运用Matlab对混沌系统进行建模和动态仿真,分析了其动态仿真在混沌控制与同步中的应用,并对仿真结果作了简要的说明和讨论. (--- Liu chaotic system with a new system, for example, use of Matlab to the chaotic system modeling and dynamic simulation analysis of its dynamic simulation in the chaos control and synchronization of applications, and simulation results gave a brief description and discussion.)

文章主要介绍了利用MATCOM进行VC和MATLAB 混合编程的步骤与优点, 并将其用于SAR 图像处理与质量评估软件开发。该软件通过图形与菜单, 界面用户只需进行简 单的菜单操作就可以得到直观的处理和评估结果, 为开展SAR 图像处理、质量评估研究提供了一个有力的工具。(Article introduces the use of MATCOM for VC++ and MATLAB programming steps and advantages of mixed and used in SAR image processing and quality assessment of software development. The software graphics and menus, just a simple user interface, menu operations can be intuitive handling and evaluation of results, for carrying out SAR image processing, quality assessment study provides a powerful tool.)

利用有限差分软件Flac3d生成人工地震波，并用于岩土工程动力分析(Using finite difference software Flac3d generate artificial seismic waves, and for dynamic analysis of geotechnical engineering)

油轮航向调节的多层感知器，可定义不同条件下的油轮参数(Multilayer perceptron for tanker ship heading regulation)

说明：  使用MATLAB语言求出两电荷间电势与电场的情况(Calculated using the MATLAB language between the two electric potential and electric charge of the situation)

speech compression by dct adpcm

关于FBMC和OFDM的子载波信道对比的，里面还包含了原参考文献。(it is about the sub channel comparation between FBMC and OFDM.)

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)

This matlab m-file computes the average image power of an image and displays a filtered image.

mitmatlab工具箱，有各种机器学习的算法(mitmatlab toolbox, there are a variety of machine learning algorithm)