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- 若信号间的能量和频率比例过大,经验模式分解不能分解出正确的单一模式分量。针对这 种状况提出一种经验模式分解与独立分量相结合的信号分析方法。该方法能分离出 IMF 分量的固有特性, 消除EMD分解过后各IMF之间信息混淆问题,恢复各个单分量所丢失的信息特性,改善了经验模式分解能力不足所带来局限性,保障经验模式分解的有效性。-If the signal energy and frequency ratio is too large, the empirical mode decomposit
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.
Untitled
- 语音信号实时采集,并用独立分量将混合信号分离-Real-time voice signal acquisition, and independent component of 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(:,
ICA3
- 通过独立分量分析,来实现盲源信号的分离。程序简单易懂,适合初学者-Done by independent component analysis and blind source separation of signals. Program is easy to understand, suitable for beginners
FAST-ICAmatlab
- ICA用于雷达信号分选,基于独立分量分析的matlab程序设计。-ICA for radar signal sorting, based on independent component analysis matlab program design.
nonnegativeICAexample
- 非负独立分量盲源信号的分离方法是一种很简单的盲源分离方法-Non-negative independent component blind source separation method is a very simple blind source separation methods
-component-analysis
- 用独立分量分析方法实现地震转换波与多次反射波分离-Using independent component analysis method to achieve multiple seismic converted wave and the reflected wave separation
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
fastICA_data1
- 信号处理的Fast ICA实现进行快速独立分量分析-Fast ICA signal processing to achieve fast independent component analysis
Independent-component-analysis
- 演示代码为“独立分量分析:教程介绍”版权:2005年,企业石、心理学系、谢菲尔德大学,谢菲尔德,英格兰。-Demonstration code for "Independent component analysis: A Tutorial Introduction"
NewICA_2014
- 独立分量分析算法(ICA)可以用于信号分解,数据处理等-Independent component analysis (ICA) can be used to decompose the signal, data processing
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.