搜索资源列表
ica4
- code 5 ica mlp intelligent
ica haar
- Chinese language pdf ica haar
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)
pca_ica
- 可以实现主成分分析（PCA）和独立成分分析（ICA）。(This package contains functions that implement Principal Component Analysis (PCA) and Independent Component Analysis (ICA).)
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)
icaFacesCode
- ica face recognition
ICA快速算法原理和程序
- FastICA算法是基于非高斯性最大化原则得到的一批处理算法。峭度和负熵都可以作为非高斯性的度量。(Advantages: applicable to any non-gaussian signal, blind separation algorithm with fast convergence speed and easy to use, without the need to choose the learning step, is the most widely used algorit
MIMO_ICA
- 基于独立成分分析（ICA）的盲源分离，对MIMO进行信号检测。在信道条件未知的情况下将两路信号分离(Blind source separation based on independent component analysis (ICA) is used to detect MIMO signals. Two channel signals are separated in the case of unknown channel conditions)
60481806ICA
- ICA的概述以及代码，输入为观察的信号，输出为解混后的信号，以及信号波形的图解，推荐下载，挺好的(Fast ica algorithm(Matlab version))
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)
基于负熵的FastICA
- 独立成分分析的Fast-ICA算法.可用于图像处理、信号分析、模式识别、人工智能(independent component analysis method based on negentropy.It can be used in image processing, signal analysis, pattern recognition and artificial intelligence)
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)
新建文件夹
- ICA(独立成分分解),可实现采集信号中源信号的分离，便于提取特征量，实现模式识别。同时由于可以将源信号分离开来，可实现信号的降噪，去掉基波、三次谐波、五次谐波等(ICA (independent component decomposition) can realize the separation of the source signals in the acquisition signal, and facilitate the extraction of the feature quant
MIToolbox
- 独立分量分析是一种统计和计算技术，用于揭示随机变量、测量数据或信号中的隐藏成分。(In ICA, multi-dimensional data is decomposed into components that are maximally independent in an appropriate sense (kurtosis and negentropy, in this package).the ICA components have maximal statistical indepe
FASST_version_v1
- ica fasst algorthim signal processing audio separation blind source
FastICA_2.5.tar
- 计算高维矩阵ICA,可用于高光谱图像降维，特征降维等应用(compute the ICA of the high order mitrix)
GroupICATv4.0b
- 实现fmri的ICA和IC selection的操作，找出与所需模板template对应的成分(Implement the operation of fMRI's ICA and IC selection, and find out the components corresponding to the required template template)