搜索资源列表
AMulti-sourceImagFusionAlgorithmUsingICA
- 一种基于ICA的多源图像融合算法为了尽可能 达到这一要求，在分析盲源分离理论的基础上，提出了一种基于独立分量分析(ICA)的图像融合算法。-ICA-based multi-source image fusion algorithm in order to meet this requirement as far as possible, in the analysis of blind source separation based on the theory put forward bas
icaimageprocessing
- 独立分量分析ICA，用于图像处理，程序不错，可以参考-Independent Component Analysis ICA, for image processing, the procedure well, can refer to
fastICA_imag
- 基于快速独立分量分析盲复原算法的混合图像分离-Independent component analysis based on fast recovery algorithm for blind separation of mixed images
Separating-Reflections-from-Image
- 基于快速核独立分量分析的图像反光分离研究 -Fast Kernel independent component analysis based on the image separation of reflection
Independent-component-analysis--
- 基于独立分量分析的图像特征提取及泊松噪声去除，用于初学者，很实用，欢迎下载-Independent component analysis based on image feature extraction and removal of Poisson noise, for beginners, it is useful, please download
Feature-level-fusion-recognition
- 介绍了复值独立分量分析(Complex ICA)的基本原理和算法，提出了基于复值独立分量分析的目标识别方法并将其应用于多传感器融合的目标识别中-The basic principle and algorithm of the complex valued Independent Component Analysis (ICA)are introduced，and a new target recognition algorithm based on the complex valued IC
ica-and-pca
- 基于matlab环境下的一个独立分量分析的小程序，包括对三个语音信号混合后的ica分析-Analysis program based on an independent component in the Matlab environment, including analysis of three speech signals mixed after ica
Improved-ICA-character-recognition
- 该算法一种结合改进的基于独立分量分析（ICA）提取算法和基于多层感知器和单向二叉决策树的多类支持向量机分类方法。-The algorithm is a combination of improved based on independent component analysis (ICA) algorithm and multi-class support vector machine classification method based on binary decision tree of
MF-ica
- 一种独立分量分析方法，有应用示例程序，可以用于处理语音信号。-A method of independent compony analysis is used to process sound signals.
FAST-ICA
- 1、对观测数据进行中心化，； 2、使它的均值为0，对数据进行白化—>Z； 3、选择需要估计的分量的个数m，设置迭代次数p<-1 4、选择一个初始权矢量（随机的W，使其维数为Z的行向量个数）； 5、利用迭代W(i,p)=mean(z(i,:).*(tanh((temp) *z)))-(mean(1-(tanh((temp)) *z).^2)).*temp(i,1)来学习W （这个公式是用来逼近负熵的） 6、用对称正交法处理下W 7、归一化W(:,p)=W(:,
FAST-ICA11
- 1、对观测数据进行中心化，； 2、使它的均值为0，对数据进行白化—>Z； 3、选择需要估计的分量的个数m，设置迭代次数p<-1 4、选择一个初始权矢量（随机的W，使其维数为Z的行向量个数）； 5、利用迭代W(i,p)=mean(z(i,:).*(tanh((temp) *z)))-(mean(1-(tanh((temp)) *z).^2)).*temp(i,1)来学习W （这个公式是用来逼近负熵的） 6、用对称正交法处理下W 7、归一化W(:,p)=W(:,
ica
- 用于独立分量分析的c++原代码自己开发的-Independent Component Analysis for c++ Original code developed their own
ICA(1)
- ICA独立分量图像特征提取,内含源程序和图片，程序完整、易懂，有很好的参考价值。-The ICA independent component image feature extraction，Contains the source program and pictures, complete, and easy to understand and have a very good reference value.
CIA2
- 一种独立分量分析的算法，内有详细介绍每一步程序的作用和意义-Independent component analysis algorithm, with detailed descr iption of each step of the process of the role and significance
FASTICA
- 快速独立分量分析用于图像处理源代码,工具包-FsatICA for image processing
ICA_paper
- 盲信号分离的论文，有理论，有具体实例。ICA，独立分量分析，用于混合图片的分离-Blind signal separation of the paper, there is a theory, there are specific examples. ICA, independent component analysis, used for the separation of mixed images
FICA_DEMO
- 快速ICA的matlab m文件，是演示代码，可以直接运行。独立分量分析。使用了基于负熵极大值的牛顿迭代法来判断分离结果的非高斯性-Fast matlab m ICA files, is a demo code, you can directly run. Independent component analysis. The non Gauss used Newton iterative method based on negative entropy to determine the max
image-enhancement
- 基于RGB模型的独立分量直方图均衡化 增强彩色图像 -color image enhancement
KEJAL4
- 独立分量分析中的cubica34a代码 matlab格式 希望有用,(Independent component analysis in matlab cubica34a code format Hope to useful,)
useful__usefql
- 独立分量分析的开关算法代码 ,内有pdf格式说明文挡 希望有用,(Switch algorithm of independent component analysis code, with exposition in PDF format Hope to useful,)