Accelerating Nyström Kernel Independent Component Analysis with Many Integrated Core Architecture

2016 ◽  
pp. 168-176
Author(s):  
Lei Shan ◽  
He Wang ◽  
Weixia Xu ◽  
Canqun Yang ◽  
Minxuan Zhang
Keyword(s):  
Independent Component Analysis ◽  
Component Analysis ◽  
Independent Component ◽  
Kernel Independent Component Analysis ◽  
Many Integrated Core

scholarly journals Reduction of Multidimensional Image Characteristics Based on Improved KICA

2014 ◽  
Vol 2014 ◽  
pp. 1-6
Author(s):  
Jia Dongyao ◽  
Ai Yanke ◽  
Zou Shengxiong
Keyword(s):  
Independent Component Analysis ◽  
Evaluation Method ◽  
Principal Component ◽  
Characteristic Parameter ◽  
Component Analysis ◽  
Independent Component ◽  
Average Correlation ◽  
Analysis Algorithm ◽  
Correlation Degree ◽  
Kernel Independent Component Analysis

The domestic and overseas studies of redundant multifeatures and noise in dimension reduction are insufficient, and the efficiency and accuracy are low. Dimensionality reduction and optimization of characteristic parameter model based on improved kernel independent component analysis are proposed in this paper; the independent primitives are obtained by KICA (kernel independent component analysis) algorithm to construct an independent group subspace, while using 2DPCA (2D principal component analysis) algorithm to complete the second order related to data and further reduce the dimension in the above method. Meanwhile, the optimization effect evaluation method based on Amari error and average correlation degree is presented in this paper. Comparative simulation experiments show that the Amari error is less than 6%, the average correlation degree is stable at 97% or more, and the parameter optimization method can effectively reduce the dimension of multidimensional characteristic parameters.

Sign in / Sign up

Export Citation Format

Share Document