Title :
A de-mixing algorithm based on the second order sample moment for independent component analysis
Author_Institution :
Dept. of Inf. & Calculation Sci., Central Univ. for Nat., Beijing
Abstract :
For the data which are mixed with an orthogonal system in the independent component analysis, that is the mixing matrix of the observation data is an orthogonal matrix, there is no an algorithm in this case at present except ones to the data with a general nonsingular mixing matrix. This paper presents an algorithm for this kind of the low order correlation data. The algorithm can be ensured in theory that the feasible solution of the problem with an orthogonal mixing matrix is the global optimal solution. Simulation experiments illustrate the efficiency of the algorithm.
Keywords :
independent component analysis; matrix algebra; signal sampling; de-mixing algorithm; general nonsingular mixing matrix; independent component analysis; low order correlation data; orthogonal mixing matrix; orthogonal system; second order sample moment; Computational efficiency; Data mining; Independent component analysis; Information theory; Maximum likelihood estimation; Optimization methods; Principal component analysis;
Conference_Titel :
Signal Processing, 2008. ICSP 2008. 9th International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-2178-7
Electronic_ISBN :
978-1-4244-2179-4
DOI :
10.1109/ICOSP.2008.4697067