资源列表
SPA
- SPA投影 用于 光谱分析 选取特征波长-SPA projection used for spectral analysis selected characteristic wavelengths
l_f
- 领航跟随法的实现，可以用于多机器人的编队控制。-The implementation of Leader-follower method, can be used in multiple robots formation control.
gatbx-tool
- 遗传算法常用的工具箱 安装步骤： 解压，复制到matlab安装路径下的toolbox文件中 file-set path-add with subfolders-gatbx-save-close file-preferences-general-update toolbox path cache-ok - gatbx .....\BS2RV.M .....\CONTENTS.M .....\CRTBASE.M .....\CRTBP.M
CEC2005
- PSO测试函数代码，CEC 005代码。包括shifted rotated generated函数-PSO test function code, CEC 005 code
IVA
- 独立向量分析（IVA）是对独立成分分析（ICA）算法的一种扩展，将ICA中的单变量成分扩展为多维变量成分，可有效避免卷积盲源分离过程中的排序模糊性问题。-Independent vector analysis (IVA), a multivariate extension of independent component analysis, tackles the convolutedly mixed blind source separation (BSS) problem in a wa
PIO
- 根据鸽群的迁徙特性，开发的新的算法，通过对比，发现比PSO具有更快的收敛速度。-According to the flock of migratory characteristics, the development of new algorithms, by contrast, found that more than PSO has a faster convergence.
CDBN-master
- 实现了卷积受限玻尔兹曼机（深度学习的一个重要算法），包括C++和matlab版本-Restricted Boltzmann realized convolution machine (depth study of an important algorithm), including C++ and matlab version
twin-support-vector-machine
- 孪生支持向量机（Twin support vector machine,TWSVM、TSVM)是SVM的一种变形算法。该TWSVM用于二分类，适合初学者有。-Twin support vector machine（TWSVM、TSVM)is a modified algorithm of SVM. This code is for beginner.
pid
- 温度PID控制功能块FB58使用入门 西门子自适应 以及C语言源代码-PID temperature control function block FB58 Getting Started Siemens adaptive and C language source code
clustering
- 基于快速搜索数据密度峰值的聚类算法是一种基于聚类中心具有较近邻点有更高密度且其与更高密度点间有着较大的相对距离的一类算法。-Clustering by fast search and find of density peaks is based on the idea that cluster centers are characterized by a higher density than their neighbors and by a relatively large distance
Multi-objective-Dragonfly-algorithm
- 多目标蜻蜓算法，包括11个m文件，经测试可运行得到结果-Multi-objective Dragonfly algorithm, which includes 11 m file and can be properly run to obtain results.
DeepLearnToolbox_CNN_lzbV3.0
- CNN - 主程序 参考文献: [1] Notes on Convolutional Neural Networks. Jake Bouvrie. 2006 [2] Gradient-Based Learning Applied to Document Recognition. Yann LeCun. 1998 [3] https://github.com/rasmusbergpalm/DeepLearnToolbox 作者：陆振波 电子