资源列表
KrigingInter
- 克里格插值法在MATLAB上的实现及应用-Kriging Implementation and Application of the MATLAB
PSO
- 神经网络构建，粒子群算法优化BP神经网络迭代寻优-Neural network building , iterative particle swarm algorithm to optimize the BP neural network optimization
compare
- 能够有效比较FAN和TDOA和泰勒级数展开法三种不同算法在三维定位的优劣性！-Can effectively compare FAN and TDOA and Taylor series expansion method in three different algorithms in three-dimensional positioning and inferiority!
hopfield
- 这是一个基于人工神经网络的城市路径选择hopfield算法，对于研究神经网络算法的读者有一定的参考作用，运行大概需要十分钟左右。-This is a city of route choice hopfield algorithm based on artificial neural network, neural network algorithm to research the reader has a certain reference function, operation takes a
joinline
- 链接直线和圆弧 是利用lisp语言进行二次开发的重要编程语言-Connecting lines and arcs is an important programming language for secondary development using lisp
5702ab54c2db
- 人工免疫网络实现分类聚类函数寻优，算法不错，希望对大家有用-This is the Fisher linear discriminant classifier, the general classification of the image of a good effect of artificial immune network to achieve classification clustering function optimization, the algorithm is good,
Robot-Soccer-
- 机器人足球比赛的matlab程序，很有意思，属于人工智能领域-robot soccer
kelongxuanze
- 本程序为免疫算法在克隆选择中的应用，其中注释非常详细。包含主函数 初始化函数 解码函数 克隆函数 变异函数。-This procedure for the application of immune algorithm in the clonal selection, the comments are very detailed. Contains the main function to initialize the decoding function cloning function var
PPT
- 深度学习，神经网络算法入门，含PPT，matlab教程-Depth learning, neural network algorithm entry containing PPT, matlab tutorials, and more
Artificial-Neural-Networks
- 深度学习，人工神经网络的模型，逐层学习算法，可以构建多层的-deep learning, artificial neural network model, learning algorithm, can construct a multi-layer
pos_mlp
- Multi Layer Perceptron for binary classification using Python. Also showing hoe to do K-Folding in python.
PCA-and-whitening
- 基于PCA和白化的数据预处理操作，PCA具有两个功能：维数约减和数据可视化；白化的目的是去掉数据之间的相关性。深度学习的一个主要工作就是数据的预处理-Based on PCA and data pre-whitening operation, PCA has two functions: dimensionality reduction and data visualization whitening purpose is to remove the correlation between t