- matlab-tutorial here the matlab code is used for simulation of fading channels and convolutional codes
- operating-system 该文档主要是关于操作系统期末考试的选择题
- Autotuning_of_PID_Controllers_A_Relay_Feedback_Ap The proportional–integral–derivative controller consists of three simple actions
- standardmedian 很有趣的中值去噪小程序
- anisodiff1D 利用PM的非线性各向异性扩散方程对图像进行处理
- sietun 基于K均值的PSO聚类算法
资源列表
tworobotrackingsine
- 一个双机器人的路径追踪控制器，用于实现2个机器人追踪期望路径的目的。-One pair of robot path tracking controller for the robot to achieve two desired path for tracking purposes.
trackingsine
- 一个路径追踪控制器，用于实现机器人追踪期望路径的目的。-A path tracking controller for the robot to track a desired path to achieve the purpose.
l_f
- 一个路径追踪控制器，用于实现2个主从机器人的相互追踪。-A path tracking controller for each other to achieve two main tracks the robot.
kernel_matrix
- 超限学习机应用部分的内容，用于生成核函数的矩阵变量欧米伽。-Machine learning content overrun part of the matrix variable is used to generate kernels Omega.
CPSO
- 混沌粒子群算法，求代价函数问题，可以避免粒子群算法陷入局部最优，求取全局最优。代码含代价函数，可作为例子理解。-Chaos particle swarm optimization, seeking cost function problems, avoid getting into local optimum particle swarm algorithm, obtaining the global optimum. Code containing cost function can be u
FeatureExtraction
- 用超限学习机实现情感识别中的部分，用于情感等特征的提取。-Learning machine with overrun achieve emotional identification section, for extracting emotional characteristics.
control1
- 路径追踪控制器，实现目标对象贴近期望轨迹并追踪期望轨迹的控制。-Path tracking controller, to achieve the target object close to the desired trajectory and desired trajectory tracking control.
FaceAlignment-master
- 基于显式形状回归算法（explicit shape regression algorithm）
cluster
- 本程序介绍了聚类分析的各种算法，包括层次、动态、模糊和遗传算法，对数值进行模式识别。-This procedure describes the various clustering algorithms, including the level of dynamic, fuzzy and genetic algorithms, pattern recognition value.
new_BPnn
- 标准BP神经网络算法程序 m文件 编程程序-Standard BP neural network algorithm program
yiqunmatlab
- 蚁群算法 很好用的人工智能算法-yiqunsuanfa is a popular arti algthroims
PSO
- matlab程序：基于粒子群算法实现函数的优化-Matlab program: Based on particle swarm optimization algorithm to achieve the optimization of the function