IEEE on MRI fuzzy segmentation of brain images related article ,2007

一种数据聚类算法的源码，可以在模式识别和图像处理中试用。 -a data clustering algorithm source code, in pattern recognition and image processing trial.

pso 粒子智能优化算法，C语言实现。欢迎下载。-Intelligent Optimization Algorithm pso particles, C language. Welcome to download

Boltzmann Machine Optimization 人工智能人工神经网络源码-Boltzmann Machine Optimization of artificial neural network artificial intelligence source

请认真书写上传资料的详细功能、包含内容说明(至少要20个字)。尽量不要让站长把时间都花费在为您修正说明上。压缩包解压时不能有密码-You can see from the above images that lower levels capture flow at center (small displacements), whereas higher levels capture flow at periphery (larger displacements).

EBP反向传播算法对应的源程序，三层网络，分隐层神经元，输出层神经元，输入层神经元的一个基本的程序实现-EBP back-propagation algorithm the corresponding source code, the three-tier networks, sub-hidden layer neurons, output layer neurons, input layer neurons realize a basic procedure

BP神经网络的设计前向型神经网络的实例，基于Matlab环境。-BP neural network design to the examples of neural network, based on the Matlab environment.

he algorithm is equivalent to Infomax by Bell and Sejnowski 1995 [1] using a maximum likelihood formulation. No noise is assumed and the number of observations must equal the number of sources. The BFGS method [2] is used for optimization. The number of independent components are calculated using Bayes Information Criterion [3] (BIC), with PCA for dimension reduction.

人工智能学习指导-artificial intelligence guiding

关联规则的频繁项集算法bomo的源代码，含说明文件，C编写，可在linux和windows下编译。-Related and regular frequent source codes which collects algorithm bomo, includes the supporting paper, C is written, can compile under linux and windows

The tca package is a Matlab program that implements the tree-dependent component analysis (TCA) algorithms that extends the independent component analysis (ICA), where instead of looking for a linear transform that makes the data components independent, we are looking for components that can be best fitted in a tree structured graphical model. The TCA model can be applied in any situation where the data can be assumed to have been transformed by an unknown linear transformation.