搜索资源列表
ICA
- 独立成分分析(Independent Component Analysis，ICA)是近年来提出的非常有效的数据分析工具，它主要用来从混合数据中提取出原始的独立信号。它作为信号分离的一种有效方法而受到广泛的关注。-Independent component analysis (ICA) is proposed in recent years very effective tool for data analysis. It is mainly used to extract the origin
ICA
- ICA源程序,用PCA预处理，用于盲分离，已经给出源文件，可以直接使用-ICA source, pretreated with PCA for source separation, has been given the source files can be used directly
ICA
- ICA optimization algorithm
ICA-BBS
- 这是一个特别适合初学者进行学习,训练的关于ICA盲源分离的例子。简单易懂。-This is a particularly suitable for beginners to learn, training on the ICA blind source separation example. Easy to understand.
ICA
- ICA的具体算法流程及对TE过程进行故障检测的应用-ICA and fault detection on TE
ICA-algorithm
- ICA algorithm for optimization
ICA
- 此程序适用于初学者的多通道正定盲源分离的快速ICA算法，适合初学者学习使用-This program is suitable for beginners of multi-channel positive definite fast ICA algorithm of blind source separation, suitable for beginners learning to use
ICA
- ICA算法可以提取个混合信号中各独立分量-The ICA algorithm can extract independent components in a mixed signal
FastICA_2.5
- matlab's fast ica algorithm
Chared ICA Code
- 帝国主义竞争算法基本的流程都有，解决具体的问题可在代码上修改。(Imperialist Competition Algorithm)
ICAmatlab程序
- 用于盲源信号分离,可以将源信号通过混合矩阵进行混合，通过求解分离矩阵，实现源信号的分离。(Using ICA algorithm to solve blind source separation problems,this procedure can separate the source commendably.)
Chared ICA Code
- 受帝国主义殖民竞争机制的启发，Atashpaz-Gargari和Lucas于2007年提出了一种新的智能优化算法—帝国竞争算法 (ICA)。与GA, PSO, ABC等受生物行为启发的群智能算法不同，ICA受社会行为启发，通过摸拟殖民地同化机制和帝国竞争机制而形成的一种优化方法。ICA也是一种基于群体的优化方法，其解空间由称为国家的个体组成。ICA将国家分为几个子群，称为帝国。在每个帝国内，ICA通过同化机制使非最优的国家(殖民地)向最优国家(帝国主义国家)靠近，该过程类似于PSO。帝国竞争机制
ica4
- code 5 ica mlp intelligent
独立成分分析ICA
- 完整的独立成分分析的示例程序，有四幅图像，生动详细(Complete independent component analysis of the sample program, there are four images, vivid detail)
implementICA
- 基本的ICA算法，可用于机器学习，最基础且有用的算法(The basic ICA algorithm can be used for machine learning, the most basic and useful algorithms)
ICA工具箱+-+FastICA_25
- matlab FASTICA工具箱,实现信号的盲源分离(FASTICA toolbox can achieve BBS for signal)
实验6_NMF-ICA
- 实现非负矩阵分解算法和独立成分分析，得到遥感遥感图像解混结果(The non negative matrix factorization algorithm and independent component analysis are implemented to get the unmixing results of remote sensing images)
代码
- ICA子程序，用于理解思想，通过均值、白化、正交等处理，再使用梯度求权重(ICA subroutine, used to understand ideas, through the mean, whitening, orthogonal processing, and then use the gradient and weight)
ICA
- 用于盲源分离理论，信号处理方面，fastica算法理论基础(Theory of blind source separation)
7941943ICA
- 独立分量分析代码，ICA的目的就是寻找解混矩阵W(A的逆矩阵)，然后对X进行线性变换，得到输出向量U(Independent Component Correlation Algorithm)