GPS

Garder 大作，通信领域同步大拿Garder的经典著作！精通锁相环！(Garder masterpiece, the communication field synchronization big take Garder classics! Proficient in phase-locked loop!)

基于遗传算法的pid整定的maatlab的源代码 可直接使用。 (Based on genetic algorithm pid the tuning maatlab the source code can be used directly.)

matlab在大气科学中的应用~这是介绍如何在大气科学研究中使用matlab的入门教程(matlab in atmospheric science applications- this is how to use matlab in atmospheric sciences Tutorial)

说明：  matlab仿真例程，是支持向量机工具箱（matlab），可用于模式分类，模式识别 Nu_SVC二类分类算法(matlab simulation routines, support vector machine toolbox (matlab), can be used for pattern classification, pattern recognition Nu_SVC second-class Classification Algorithm)

利用c语言生成符合正态分布的随机数，并在matlab程序中画出曲线图，并与理论值比较(Use c language to generate normally distributed random numbers and draw graphs in matlab program)

matlab程序，一种快速ICA算法，用于混合信号盲分离，可应用于通信系统信号处理(matlab program, a fast ICA algorithm for blind separation of mixed signals, signal processing can be used in communication systems)

matlab计算股市的代码,可以帮助你分析股市，胜券在握！(matlab code for stocks)

程序为地震勘探资料处理方法中的数值模型模拟正演，方法为射线追踪(The program forward numerical model for seismic exploration data processing method in the simulation, for ray tracing method)

An article with code on how to create the Alpha effect (fading in and out effect). Starts with the application of alpha on images, and ends with the creation of alpha animation. This is NOT about the Per Pixel Alpha Blend used in Windows. (An article with code on how to create the Alpha effect (fading in and out effect). Starts with the application of alpha on images, and ends with the creation of alpha animation. This is NOT about the Per Pixel Alpha Blend used in Windows. )

梯度下降法是最早最简单，也是最为常用的最优化方法。梯度下降法实现简单，当目标函数是凸函数时，梯度下降法的解是全局解。一般情况下，其解不保证是全局最优解，梯度下降法的速度也未必是最快的。梯度下降法的优化思想是用当前位置负梯度方向作为搜索方向，因为该方向为当前位置的最快下降方向，所以也被称为是”最速下降法“。最速下降法越接近目标值，步长越小，前进越慢。(The gradient descent method is the earliest and most simple and most commonly used optimization method. The gradient descent method is simple to realize. When the objective function is a convex function, the solution of the gradient descent method is a global solution. In general, the solution is not guaranteed to be the global optimal solution, and the gradient descent method is not necessarily the fastest. The optimization idea of gradient descent method is to use the current position negative gradient direction as the search direction, because the direction is the fastest descending direction of the current position, so it is also called the steepest descent method. The faster the slowest descent approach is closer to the target, the smaller the step, the slower the progress.)