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Delaunay triangulation is one of the most well known algorithms for space tesselation. Dynamic Delaunay triangulation, in which you can update the input points using a predefined matrice for saving points, is presented in this document.

matlab代码，三维点云数据处理，对含灰度的三维点云进行傅立叶变换(matlab code, three-dimensional point cloud data processing, the three-dimensional point cloud with gray Fourier transform)

本文提出了一种适用于低轨卫异扩频通信系统的多普勒频移快捕方法.该方法基于数字匹配滤波器及自动频率控制环路_利用数字匹配滤波器的囚码快捕特性及其输出主相关峰值对频偏的敏感性，缩短多普勒频移的 捕获时间.论文首先推导了多普勒频移的平均捕获时间表达式，然后根据数值分析结果得到了准最佳捕获判决策略，最后通过比较验证了该快捕方法相对于传统串行捕获方法在性能上的提高. (This paper presents a low-orbit health for different spread spectrum communication system fast catching the Doppler shift method, which based on digital matched filter and automatic frequency control loop _ prisoners using digital matched filter code features rapid acquisition and the output of the main correlation peak frequency deviation of the sensitivity of the Doppler frequency shift to shorten acquisition time. paper first derive the mean Doppler shift acquisition time expression, then the numerical results obtained quasi-optimal capture decision strategies, and finally verified by comparing with the rapid acquisition method to capture the traditional method of serial improvement in performance.)

聚类算法不同有效性指标的性能比较，改进代码用于不同的应用问题(Clustering algorithm performance comparison of different effectiveness index, improve code used for different applications)

Partial Least Squares regression bilinear factor model 的输出源码(Partial Least Squares regression bilinea r factor model output FOSS)

整体最小二乘最小奇异值法的matlab实现，供大家一块学习(The total least squares minimum singular value method of Matlab implementation, for everyone to learn a piece)

MODELLING OF MOBILE ROBOT DYNAMICS

说明：  多目标遗传算法是NSGA-II[1]（改进的非支配排序算法）,该遗传算法相比于其它的多目标遗传算法有如下优点：传统的非支配排序算法的复杂度为 ，而NSGA-II的复杂度为 ，其中M为目标函数的个数，N为种群中的个体数。引进精英策略，保证某些优良的种群个体在进化过程中不会被丢弃，从而提高了优化结果的精度。采用拥挤度和拥挤度比较算子，不但克服了NSGA中需要人为指定共享参数的缺陷，而且将其作为种群中个体间的比较标准，使得准Pareto域中的个体能均匀地扩展到整个Pareto域，保证了种群的多样性。（消除了共享参数）。(Multi-objective genetic algorithm is nsga-ii [1] (improved non-dominant sorting algorithm), which has the following advantages compared with other multi-objective genetic algorithms: the complexity of the traditional non-dominant sorting algorithm is, while the complexity of nsga-ii is, where M is the number of objective functions and N is the number of individuals in the population.The introduction of elite strategy to ensure that some good individuals in the evolutionary process will not be discarded, thus improving the accuracy of the optimization results.The comparison operator of crowding degree and crowding degree not only overcomes the defect that NSGA needs to specify the Shared parameter artificially, but also takes it as the comparison standard between individuals in the population, so that individuals in the quasi-pareto domain can uniformly expand to the whole Pareto domain, ensuring the diversity of the population.(eliminating Shared parameters).)

基于matlab的神经网络训练方法，其中采用不同的隐层，自己编写的，实现多类数据的分类(It ia a code to learn network.)

基于C语言的PID功能实现，用c语言编写的PID算法(PID function based on the C language implementation)