资源列表
partial-least-square-and-modeling
- 能够实现偏最小二乘建模和特征建模，这是软测量技术上面的只是，对建模有一点点帮助-partial least square and modeling
Feature-selection-
- 基于基因遗传算法的特征选择程序 高喊制图功能,直接给出匹配耦合-Feature selection based on GA in Matlab
frequent-subgraph
- 用于图集上子图搜索的代码，gSpan和FFSM的源码，都是在linux下运行，其中gSpan包括直接可以用shell运行的二进制文件和一个C&matlab版本，FFSM是C&matlab版本-Atlas subgraph search for the code, gSpan and FFSM source, are run under linux, which can be used directly gSpan including binaries and shell to run a C &
2-jiedaolibai
- 使用神经网络实现2阶倒立摆的控制。包含simulink连接图、神经网络程序、最终结果。-Second order inverted pendulum control using neural network. Contains the simulink connection diagram, neural network program, the final result.
AOMUSv0.72.tar
- 自助推理可满足性研究算法。用于求解极小不可满足子式的随即搜索算法。-Self-study reasoning algorithm can meet. For solving minimal unsatisfiable sub-formula then search algorithm.
on-convolutional-nueral-network
- 基于卷积神经网络的模式分类器,论文中讲述了卷积神经网络的技术，是个好论文。-pattern classfier based on convolutional nerual networks
word-recognition-and-nerual-networks
- 基于卷积神经网络的字符识别技术，较好的算法！！神经网络、-Convolution-based neural network character recognition technology, better algorithm! ! Neural network,
CNM-algorithm
- 社区分析算法CNM，可以用来进行社区网络分析- Community analysis algorithm CNM, network analysis can be used for community
libsvm-3.1-[FarutoUltimate3.1Mcode]
- 台湾大学林智仁的libsvm工具箱的增强版，集成了参数选择算法，十分好用。-Lin Zhiren Taiwan University, an enhanced version of libsvm toolbox integrates parameter selection algorithm, is very easy to use.
SQPSO
- 基于物种形成的PSO算法（SQPSO），里面含有量子粒子的思想。主要参考Blackwell的论文。采用的动态环境是MPB函数---移动峰基准函数10个峰-PSO algorithm based on the formation of species (SQPSO), which contains the idea of quantum particles. Blackwell main reference papers. Using a dynamic environ
duofeilei-fisher
- 用语言编写的多分类fisher程序，已成功实验过，可以用，用到的数据时改一下参数哦就可以用-With multi-language classified fisher program has been successful experiment that can be used, when data is used to change parameters, oh what can be used
SimpleTracker
- 颗粒跟踪’建立一个或多个颗粒随时间变化而形成的轨迹。跟踪算法记录下颗粒在每帧数据中的位置。本算法的亮点是间断处理。间断是指一个颗粒在一帧中出现而在下一帧中消失。如果不做处理，当该颗粒在后续帧中重现时，将产生新的虚假跟踪。-Particle tracking to create one or a plurality of particles with time and the formation of the track. Particle tracking algorithm recorded