AscIIart

base de données multimodale base de données multimodale base de données multimodale base de données multimodale

是一个人脸识别系统，过程非常详细，对学习非常有帮助(Is a face recognition system, the process is very detailed and very helpful in learning)

都市供求信息网分为前后台的设计，前台主要实现信息的显示、搜索与发布功能。其中信息的显示包括列表显示与详细内容显示，而列表显示，又分为首页面的信息列表显示、查看某类别下所有信息的列表显示和搜索结果列表显示；搜索功能主要包括定位搜索和模糊搜索；后台主要实现的功能为信息显示、信息审核、信息删除、付费设置与退出登录，其中的信息显示功能也分为列表显示与详细内容显示。(Urban supply and demand information network is divided into front and back design, front main achievement of the displayed information, search and publishing. Which displays information including a list of displays and display details, but the list is displayed, the information is divided into the home side s display list, a list of all the categories of information under the display and view a list of search results display Search functions include positioning search and fuzzy search the main function of the background information display, information auditing, information deleted, pay setting and exit the registry, which is also divided into the information display function displays detailed contents list display.)

用德鲁德模型计算超导材料石墨烯的介电常数和电导率(Calculated using superconducting material graphene permittivity and conductivity Drude model)

机器人机构的速度与加速度可以用通过程序来计算得出，方式更为简便(Robot body velocity and acceleration can be calculated by the program, more convenient way)

基于matlab的加性高斯白噪声 源代码 直接用软件打开即可(Matlab-based additive white Gaussian noise)

VMWare是一个“虚拟PC”软件.它使你可以在一台机器上同时运行二个(VMWare is a virtual PC software, which allows you to run two at the same time on a single machine)

说明：  共轭梯度法（Conjugate Gradient）是介于最速下降法与牛顿法之间的一个方法，它仅需利用一阶导数信息，但克服了最速下降法收敛慢的缺点，又避免了牛顿法需要存储和计算Hesse矩阵并求逆的缺点，共轭梯度法不仅是解决大型线性方程组最有用的方法之一，也是解大型非线性最优化最有效的算法之一。 在各种优化算法中，共轭梯度法是非常重要的一种。其优点是所需存储量小，具有步收敛性，稳定性高，而且不需要任何外来参数。(The Conjugate Gradient method is a method between the steepest descent method and the Newton method. It only needs to use the first derivative information, but overcomes the shortcomings of the steepest descent method and avoids the need for the Newton method to store And the calculation of Hesse matrix and the inverse of the shortcomings, conjugate gradient method is not only to solve large-scale linear equations one of the most useful methods, but also solution for large-scale nonlinear optimization of one of the most effective algorithm. In a variety of optimization algorithms, conjugate gradient method is a very important one. The advantage is that the required storage capacity is small, with step convergence, high stability, and does not require any external parameters.)

人工算法求解函数优化问题——智能计算大作业(Artificial Algorithm for Function Optimization- Great job on Intelligent Computing)

calcl md choose vector