Title :
Neural Networks Preprocessing Based Adaptive Estimation of Evoked Potentials
Author_Institution :
Coll. of Electron. Eng., Jiujiang Univ., Jiujiang
Abstract :
Independent component analysis (ICA) is a new powerful tool for blind source separation. This paper proposes a new algorithm that combines two existent algorithms, the improved infomax algorithm and the fastICA algorithm. Utilizing the initial weights obtained by the improved infomax algorithm, we can not only reduce the length of data which fastICA algorithm needs, but also enhance the convergence stability of fastICA algorithm. The effectiveness of the algorithm is verified by computer simulations.
Keywords :
bioelectric potentials; blind source separation; brain; independent component analysis; medical signal processing; neural nets; neurophysiology; blind source separation; evoked potentials; fastICA algorithm; independent component analysis; infomax algorithm; neural networks; Adaptive estimation; Biological neural networks; Blind source separation; Convergence; Educational institutions; Independent component analysis; Neural networks; Power engineering and energy; Signal processing algorithms; Stability;
Conference_Titel :
Bioinformatics and Biomedical Engineering, 2008. ICBBE 2008. The 2nd International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-1747-6
Electronic_ISBN :
978-1-4244-1748-3
DOI :
10.1109/ICBBE.2008.882
