Solvation, transduction and independent component analysis for pattern recognition in SAW electronic nose

2006 ◽  
Vol 113 (1) ◽  
pp. 1-21 ◽  
Author(s):  
R.D.S. Yadava ◽  
Ruchi Chaudhary
Keyword(s):  
Pattern Recognition ◽  
Independent Component Analysis ◽  
Electronic Nose ◽  
Component Analysis ◽  
Independent Component

Palm Vein Recognition Based on Independent Component Analysis

2013 ◽  
Vol 333-335 ◽  
pp. 1106-1109
Author(s):  
Wei Wu
Keyword(s):  
Pattern Recognition ◽  
Independent Component Analysis ◽  
Euclidean Distance ◽  
Recognition Performance ◽  
Component Analysis ◽  
Independent Component ◽  
Experimental Results ◽  
Vein Pattern ◽  
Vein Recognition ◽  
Palm Vein

Palm vein pattern recognition is one of the newest biometric techniques researched today. This paper proposes project the palm vein image matrix based on independent component analysis directly, then calculates the Euclidean distance of the projection matrix, seeks the nearest distance for classification. The experiment has been done in a self-build palm vein database. Experimental results show that the algorithm of independent component analysis is suitable for palm vein recognition and the recognition performance is practical.

PATTERN RECOGNITION OF THE TERM STRUCTURE USING INDEPENDENT COMPONENT ANALYSIS

2006 ◽  
Vol 20 (02) ◽  
pp. 173-188 ◽  
Author(s):  
EDMOND HAOCUN WU ◽  
PHILIP L. H. YU
Keyword(s):  
Time Series ◽  
Pattern Recognition ◽  
Independent Component Analysis ◽  
Term Structure ◽  
Financial Time Series ◽  
Empirical Studies ◽  
Multivariate Time Series ◽  
Principal Component ◽  
Component Analysis ◽  
Independent Component

Term structure is a useful curve describing some financial asset as a function of time to maturity or expiration. In this paper, we propose to use Independent Component Analysis (ICA) to model the term structure of multiple yield curves. The idea is that we first employ ICA to decompose the multivariate time series, then we suggest two ICA methods for dimension reduction and pattern recognition of the term structure. We also compare the results by using an alternative method, Principal Component Analysis (PCA). The empirical studies suggest that the proposed ICA approaches outperform PCA methods in modeling the term structure. This model can be used in financial time series analysis as well as related financial applications.

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