scholarly journals Monitoring Nonlinear and Non-Gaussian Processes Using Gaussian Mixture Model-Based Weighted Kernel Independent Component Analysis

2017 ◽  
Vol 28 (1) ◽  
pp. 122-135 ◽  
Author(s):  
Lianfang Cai ◽  
Xuemin Tian ◽  
Sheng Chen
Keyword(s):  
Independent Component Analysis ◽  
Gaussian Mixture Model ◽  
Mixture Model ◽  
Gaussian Processes ◽  
Component Analysis ◽  
Gaussian Mixture ◽  
Independent Component ◽  
Kernel Independent Component Analysis ◽  
Weighted Kernel ◽  
Non Gaussian

An Alternative Perspective on Adaptive Independent Component Analysis Algorithms

1998 ◽  
Vol 10 (8) ◽  
pp. 2103-2114 ◽  
Author(s):  
Mark Girolami
Keyword(s):  
Independent Component Analysis ◽  
Closed Form ◽  
Gaussian Mixture Model ◽  
Score Function ◽  
Component Analysis ◽  
Gaussian Mixture ◽  
Independent Component ◽  
Analysis Algorithm ◽  
Alternative Perspective ◽  
Independent Component Analysis Algorithm

This article develops an extended independent component analysis algorithm for mixtures of arbitrary subgaussian and supergaussian sources. The gaussian mixture model of Pearson is employed in deriving a closed-form generic score function for strictly subgaussian sources. This is combined with the score function for a unimodal supergaussian density to provide a computationally simple yet powerful algorithm for performing independent component analysis on arbitrary mixtures of nongaussian sources.

Sign in / Sign up

Export Citation Format

Share Document