桁架杆分析

雷达杂波抑制算法 (Radar clutter suppression algorithm)

噪声谱估计方法，包括“minimum tracking”，“MCRA algorithm”，“IMCRA algorithm”，“Continuous minimal tracking”。(This folder contains noise-estimation algorithms,include: minimum tracking , MCRA algorithm , IMCRA algorithm , Continuous minimal tracking .)

说明：  louvain经典复杂网络社团结构检测程序(louvain classic complex network community structure detection program)

小波去噪，分程3种，第一对信号进行强制消噪处理并图示结果；第二用默认阈值对信号进行消噪处理并图示结果；第三用给定的软阈值进行消噪处理。以及运行图。(Denoising , sub-way three kinds , the first pair of signal processing and noise cancellation forced the results shown second by default thresholds for signal processing and illustrates the results of de-noising third with a given soft threshold de-noising deal with . And a diagram.)

将实数信号分解为循环偶分量和循环奇分量以及循环卷积等程序（matlab源程序）(The real number signal decomposition cycle even component and circulation odd component, and circular convolution program (matlab source code))

车辆车速控制系统的simulink程序，本人制作，仅供参考。(Car speed control system simulink program, made reference only.)

说明：  这是MATLAB智能算法30个案例分析（第2版）的code部分，内容详实，有兴趣学习基于matlab只能优化算法的可以参考，里面主要有遗传算法、粒子群算法、模拟退化算法等的演示。(This is the code part of the 30 case analysis (second edition) of MATLAB intelligent algorithms. The content is detailed. If you are interested in learning based on matlab, you can only optimize the algorithm. You can refer to it. There are demonstrations of genetic algorithm, particle swarm algorithm, simulation degradation algorithm, etc.)

A simple code for selective mapping

共轭梯度法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。(Conjugate gradient method is between the steepest descent method and Newton method between a method that only use the first derivative information, but the steepest descent method to overcome the disadvantage of slow convergence, but also avoids the need to store and calculate Newton Hesse matrix and the shortcomings of the inverse, conjugate gradient method is not only linear equations to solve large-scale one of the most useful, large-scale nonlinear optimization solution is also the most efficient algorithms.)

This program shows how to overlay a statistical map on top of an anatomical map.