Title :
Blind Source Extraction with Adaptive Learning Rate Based on a Linear Predictor
Author_Institution :
Sch. of Comput. Sci. & Eng., Univ. of Electron. Sci. & Technol. of China, Chengdu, China
Abstract :
An on-line BSE algorithm with an adaptive learning rate is proposed. By indirectly studying one of the existing on-line BSE algorithms based on line predictability, the bound for the optimal learning rate which guarantees the convergence of the algorithm is derived. Based on the analysis results, an on-line algorithm with an adaptive learning rate is presented. Since the learning rates of the existing on-line algorithms based on line predictability are chosen empirically in practice, the adaptive one proposed in this paper is more useful. The simulations verify the obtained results.
Keywords :
blind source separation; convergence; learning (artificial intelligence); adaptive learning rate; blind source extraction; linear predictor; online BSE algorithm; Algorithm design and analysis; Convergence; Data mining; Eigenvalues and eigenfunctions; Performance analysis; Prediction algorithms; Signal processing algorithms;
Conference_Titel :
E-Product E-Service and E-Entertainment (ICEEE), 2010 International Conference on
Conference_Location :
Henan
Print_ISBN :
978-1-4244-7159-1
DOI :
10.1109/ICEEE.2010.5661231