搜索资源列表
ICABSS
- 简述了独立分量分析理论和盲源分离技术20年的发展历史,概述性非常强。-Outlining very briefly independent component analysis theory and blind source separation technique 20 years of development history.
resultICA
- 大纲很简单地独立分量分析理论和盲源分离技术20多年的发展历史,及其程序。-Independent component analysis of the history of the development of the theory and blind source separation technology more than 20 years, and its procedures.
project-1
- 对盲源分离和独立分量分析进行了详细的介绍,可读性好。-Blind source separation and independent component analysis, a detailed introduction and readable.
FastICA_testing_wav_img_samples
- matlab FastICA快速独立分量分析 通过FastICA工具箱(内含),对图像、音频进行盲源分离,去均值,白化处理,支持tif,jpg,bmp,wav等多种格式,并附有详细程序注释及sample供运行使用-matlab FastICA fast independent component analysis FastICA toolbox (included), images, audio, blind source separation to mean whitening process
ICA
- 基于独立分量分析去除肌电信号中的工频干扰及其谐波分量-Filter the power line interference and its harmonic in EMG
tidu_ICA
- 梯度ICA方法用来解决独立分量分析问题,通信方面的-the code of independent component analysis of matlab
work
- 对三路信号进行分离,基于峭度和基于负熵的独立分量分析(ICA)-The three way signal separation, based on the kurtosis and independent component analysis (ICA) based on negative entropy
ICALABIPv2_0
- 独立分量分析工具,ICAlab,可以对了解独立分量分析的具体操作。-Independent component analysis tools, ICAlab, specific actions can understand the independent component analysis.
sdica
- 硕博美国留学的中科大本科毕业的研究独立分量分析的一位牛人编写的子带ica的matlab程序。研究盲源分离的必备。-USTC graduated Shuobo study in the United States of an independent component analysis cattle were prepared subband ica matlab program. Study the blind source separation essential.
ica_D_R
- 具有参考信号的独立分量分析程序,国外的提出这个问题的人编写的。-Independent component analysis (ICA) program with a reference signal abroad website.
332
- 齿轮箱早期的故障信号往往十分微弱,信噪比低,这大大限制了已有诊断方法在早期诊断中的应用,因此如何获取真实的振动信号是提高齿轮箱早期故障诊断质量的关键,独立分量分析(ICA)为此提供了一种新的思路。文 中研究了ICA在齿轮箱故障早期诊断中的应用,首先分析了齿轮箱的混合振动信号模型,然后针对具体的轴承故障进行了实验,并使用快速ICA算法分离出轴承的振动信号-The early gearbox fault signal is often very weak, low signal-to-noise
FastICA-algorithm
- 利用独立分量分析中的FastICA算法对盲信号源进行了分离。最终通过实验结果表明,独立分量分析可以有效地实现分离。-FastICA algorithm using independent component analysis and blind source separation. Eventually through the experimental results show that the independent component analysis can be effectively
psogaijinsuanfa
- 基于粒子群算法改进算法的独立分量分析算法研究-Independent component analysis algorithm based particle swarm algorithm to improve the algorithm
robust_ICA
- 稳健独立分量分析算法,实现任意混合信号的分离。-Strong and independent component analysis algorithm to achieve any mixed-signal separation.
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.
MS-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.
fastICA
- matlabfastica 快速独立分量分析源代码-matlabfastica fast independent component analysis of the source code
ICA
- matlab中ICA独立分量分析全部代码免费下载-Independent component analysis ICA in matlab code free download full
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(:,