7z-master

说明：  一个C#开发的线性规划 单纯形算法，能够求解中小规模的线性规划问题，欢迎大家下载，自己写的哦！！(A C# development of linear programming simplex algorithm to solve the small and medium-scale linear programming problem, welcome to download their own writing Oh! !)

说明：  JQuery Picture Display Code for Horizontal Responsive Arrangement of Pictures and jQuery Picture Adaptive Arrangement

说明：  实现IEEE33节点的确定性潮流计算，采用直角坐标系的牛拉法(The deterministic power flow calculation of ieee33 node is realized by using the niula method in rectangular coordinate system)

//以上的代码加载了两个PCD文件得到共享指针， //后续配准是完成对源点云到目标点云的参考坐标系的变换矩阵的估计， //得到第二组点云变换到第一组点云坐标系下的变换矩阵 // 将输入的扫描点云数据过滤到原始尺寸的10%以提高匹配的速度， //只对源点云进行滤波，减少其数据量，而目标点云不需要滤波处理 //因为在NDT算法中在目标点云 对应的 体素网格数据结构的 统计计算不使用单个点， //而是使用包含在每个体素单元格中的点的统计数据(The following links describe a set of basic PCL tutorials. Please note that their source codes may already be provided as part of the PCL regular releases, so check there before you start copy & pasting the code. The list of tutorials below is automatically generated from reST files located in our git repository.)

debian linux 硬盘安装文件.硬盘安装硬盘安装-debian linux hard disk installation files. the hard disk to install the hard disk installation

说明：  动态窗口法实现二维路径规划，可以设置圆形动/静态障碍物(Dynamic window method is used to realize two-dimensional path planning, and circular dynamic / static obstacles can be set)

说明：  生成GPS所使用的的CA码，可以用于后续与数据码调制，并调制到载波上(Generate the CA code used by GPS)

说明：  一款超酷的3D元素周期表三维图片墙效果，使用html5和jquery技术制作(A cool 3-D periodic table wall effect, Using HTML 5 and jQuery Technology)

说明：  定导航颜色渐变是一款简洁易用的轻量级幻灯Basic jQu(Fixed Navigation Color Gradient is a compact and easy-to-use lightweight slide Basic jQu)

说明：  独立成分分析(Independent Component Analysis，ICA)是近年来提出的非常有效的数据分析工具，它主要用来从混合数据中提取出原始的独立信号。它作为信号分离的一种有效方法而受到广泛的关注。近几年出现了一种快速ICA算法(Fast ICA)，该算法是基于定点递推算法得到的，它对任何类型的数据都适用，同时它的存在对运用ICA分析高维的数据成为可能。又称固定点(Fixed-Point)算法，是由芬兰赫尔辛基大学Hyvärinen等人提出来的。是一种快速寻优迭代算法，与普通的神经网络算法不同的是这种算法采用了批处理的方式，即在每一步迭代中有大量的样本数据参与运算。但是从分布式并行处理的观点看该算法仍可称之为是一种神经网络算法。(Independent component analysis (ICA) is a very effective data analysis tool proposed in recent years. It is mainly used to extract the original independent signals from the mixed data. As an effective method of signal separation, it has been widely concerned. In recent years, a fast ICA algorithm (fast ICA) has appeared. The algorithm is based on the fixed-point recursive algorithm, which is applicable to any type of data. At the same time, its existence makes it possible to use ICA to analyze high-dimensional data. Also known as fixed-point algorithm, it was proposed by HYV & auml; rinen et al. It is a fast optimization iterative algorithm. Different from the common neural network algorithm, this algorithm adopts the way of batch processing, that is, there are a large number of sample data in each iteration. But from the point of view of distributed parallel processing, this algorithm can still be called a neural network algorithm.)