DSSS_MSK_

实现了1D,2D,3D空间自由度下的运动参数的扩展Kalman滤波算法，文章2008 IROS Visual SLAM for 3D Large-Scale Seabed Acquisition Employing Underwater Vehicles的具体实现。(a novel technique to align partial 3D reconstructions of the seabed acquired by a stereo camera mounted on an autonomous underwater vehicle. Vehicle localization and seabed mapping is performed simultaneously by means of an Extended Kalman Filter. Passive landmarks are detected on the images and characterized considering 2D and 3D features. Landmarks are re-observed while the robot is navigating and data association becomes easier but robust. Once the survey is completed, vehicle trajectory is smoothed by a Rauch-Tung-Striebel filter obtaining an even better alignment of the 3D views and yet a large-scale acquisition of the seabed.)

2014年全国研究生数学建模竞赛D题第三、四问：果蔬分配问题-规划问题。( 2014年全国研究生数学建模竞赛D题第三、四问：果蔬分配问题-规划问题。 The research of mathematical modeling contest D title in 2014 third, four Q: fruits and vegetables allocation problem- Programming problem.)

AES coding end de-coding by matlab

EzStego的全部源码，适用于Windows/Linux等等环境(EzStego all the source code for Windows/Linux environment, etc.)

The chebfun project is a collection of algorithms, and a software system in object-oriented Matlab, which extends familiar powerful methods of numerical computation involving numbers to continuous or piecewise-continuous functions. It also implements continuous analogues of linear algebra notions like the QR decomposition and the SVD. The mathematical basis of the system combines tools of Chebyshev expansions, fast Fourier transform, barycentric interpolation, Clenshaw-Curtis quadrature, and recursive zerofinding.

说明：  am的Matlab源程序，可以用于系统仿真！！！(am)

matlab example shows you can work that easily.

关于matlab的浙大课件包含word和ppt(ppt and word about matlab from zhejiang university)

example of using emd

遗传算法是模拟达尔文的遗传选择和自然淘汰的生物进化过程的计算模型。它的思想源于生物遗传学和适者生存的自然规律，是具有“生存＋检测”的迭代过程的搜索算法。遗传算法以一种群体中的所有个体为对象，并利用随机化技术指导对一个被编码的参数空间进行高效搜索。(Genetic algorithm is simulated Darwinian natural selection of genetic selection and evolution process model. It' s thought from biological genetics and survival of the fittest laws of nature, is a " survival+ detection" iterative process of search algorithm. Genetic algorithms in a group all the individuals targeted, and technical guidance on the use of a randomized coded efficiently search parameter space.)