Projekt

特别经典的MATLAB学习资料，希望能够为莘莘学子提供帮助(Special classic learning materials in MATLAB, hoping to provide help for students)

说明：  基于粒子群优化算法的模糊c聚类源码，matlab类型(Fuzzy c-cluster source code based on particle swarm optimization algorithm, matlab type)

FM demodulation matlab file

Turbo Equalize matlab simulation

动态规划网络，包括执行网络和评价网络，采用BP网络实现。(ADP network, including execution network and evaluation network, is implemented by BP network.)

New Envelope Algorithm for Hilbert-Huang Transform.rar 基于希尔伯特-黄变换中的一种新包络线算法 介绍的内容比较实用(New Envelope Algorithm for Hilbert-Huang Transform.rar based on the Hilbert- Huang Transform in a new envelope algorithms are more practical introduction)

about IEEE CAN DO THE POSSIBLE STUDIES ON KALMAN

说明：  Face Detection and Tracking Using the KLT Algorithm This example shows how to automatically detect and track a face using

说明：  人工智能分割图像方法，运用深度学习实现，程序可直接使用(The method of image segmentation based on artificial intelligence and realized by deep learning)

粒子群优化算法(PSO)是一种进化计算技术(evolutionary computation)，有Eberhart博士和kennedy博士发明。源于对鸟群捕食的行为研究 PSO同遗传算法类似，是一种基于叠代的优化工具。系统初始化为一组随机解，通过叠代搜寻最优值。但是并没有遗传算法用的交叉(crossover)以及变异(mutation)。而是粒子在解空间追随最优的粒子进行搜索。详细的步骤以后的章节介绍 同遗传算法比较，PSO的优势在于简单容易实现并且没有许多参数需要调整。目前已广泛应用于函数优化，神经网络训练，模糊系统控制以及其他遗传算法的应用领域(Particle Swarm Optimization (PSO) is an evolutionary computation technique (evolutionary computation), has Dr. Eberhart and Dr. kennedy invention. Deriving from the behavior of birds of prey PSO with genetic algorithm is similar to an iterative optimization-based tools. System initialization for a group of random solutions, through the iterative search for optimal values. But there is no cross-genetic algorithm used (crossover) and mutation (mutation). But the particles in the solution space of the particles to follow the optimal search. In detail the steps after the introduction sections compared with the genetic algorithm, PSO has the advantage of being simple and easy and did not realize many of the parameters need to be adjusted. Has been widely applied to function optimization, neural network training, fuzzy system control, as well as other genetic algorithm applications)