Soft Analyzer Modeling for Dearomatization Unit Using KPCR with Online Eigenspace Decomposition

2006 ◽  
pp. 495-504
Author(s):  
Haiqing Wang ◽  
Daoying Pi ◽  
Ning Jiang ◽  
Steven X. Ding
Keyword(s):  
Eigenspace Decomposition

Background Modeling Approach Based on Eigenspace Decomposition

2012 ◽  
Vol 157-158 ◽  
pp. 1399-1403
Author(s):  
Jian Wu Long ◽  
Xuan Jing Shen ◽  
Hai Peng Chen
Keyword(s):  
Video Sequence ◽  
Moving Objects ◽  
Principal Component ◽  
Background Model ◽  
Training Set ◽  
Training Samples ◽  
The Matrix ◽  
Eigenspace Decomposition ◽  
Svd Decomposition ◽  
Background Models

In this work principal component analysis (PCA) was adopted to construct a background model and moving objects were detected by background subtraction method. Firstly, constructed the matrix of training samples by means of converting the video sequence to vectors. Then calculated the covariance matrix C of the training set, and acquired the eigenvalues and eigenvectors of C through SVD decomposition. Next, sorted the eigenvalues and reconstructed the background model by using several image vectors which had higher cumulative contribution. Finally, comparison experiments are performed with the detection results by GMM approach. Experimental results show that the proposed method in this paper could establish background models more accurate and have better effective of object detection.

scholarly journals Lawson homology for abelian varieties

2015 ◽  
Vol 27 (2) ◽  
Author(s):  
Wenchuan Hu
Keyword(s):  
Abelian Varieties ◽  
Eigenspace Decomposition

AbstractIn this paper we study the action of the Fourier–Mukai transform on the Lawson homology of abelian varieties and a Beauville-type eigenspace decomposition of Lawson homology with rational coefficients.

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