Title :
Improvement for Nonnegative PCA Algorithm for Independent Component Analysis
Author :
Li, Yunxia ; Zheng, Hong
Author_Institution :
Sch. of Autom. Eng., UESTC, Chengdu
Abstract :
This paper consider the independent component analysis problem, in the case where the hidden sources are nonnegative and well-grounded. It makes improvement for nonnegative PCA algorithm by adding a term to the cost function to assure the orthonormality of the separating matrix. Simulation results illustrate its effectiveness
Keywords :
independent component analysis; matrix algebra; principal component analysis; demixing matrix; independent component analysis; nonnegative PCA algorithm; orthonormality; Automation; Costs; Independent component analysis; Minimization methods; Performance analysis; Principal component analysis; Probability; Vectors;
Conference_Titel :
Neural Networks and Brain, 2005. ICNN&B '05. International Conference on
Conference_Location :
Beijing
Print_ISBN :
0-7803-9422-4
DOI :
10.1109/ICNNB.2005.1615016
