Title :
Blind source separation of signals with known alphabets using ε-approximation algorithms
Author :
Li, Qingyu ; Bai, Er-Wei ; Ding, Zhi
Author_Institution :
Dept. of Electr. & Comput. Eng., Iowa Univ., Iowa City, IA, USA
Abstract :
We show that blind separation of signals in given alphabets can be formulated into a quadratic optimization problem with integer constraints. Then, efficient ε-approximation algorithms are applied to directly estimate the transmitted signals. The proposed approach does not require any high order statistics. Moreover, the algorithms converge to an ε neighborhood of the global optimum with polynomial computational complexity. Simulations show that the algorithm achieves satisfactory performance using a short length of data.
Keywords :
approximation theory; blind source separation; computational complexity; optimisation; blind signal separation; blind source separation; efficient ε-approximation algorithms; integer constraints; known alphabets; polynomial computational complexity; quadratic optimization; short data length; simulations; time-varying environment; Bandwidth; Blind source separation; Constraint optimization; Convergence; Higher order statistics; Iterative algorithms; Maximum likelihood estimation; Signal processing; Signal processing algorithms; Statistical analysis;
Journal_Title :
Signal Processing, IEEE Transactions on
DOI :
10.1109/TSP.2002.806561