@inproceedings{b6224978063e4b899a880c3f44e706f9,
title = "An efficient VLSI implementation of SVD processor of on-line recursive ICA for real-time EEG system",
abstract = "This paper presents an efficient VLSI implementation of a singular value decomposition (SVD) processor of on-line recursive independent component analysis (ORICA) for use in a real-time electroencephalography (EEG) system. ICA is a well-known method for blind source separation (BBS), which helps to obtain clear EEG signals without artifacts. In general, computations of ORICA are complicated and the critical computational latency is associated with the SVD process. Accordingly, the performance of the SVD processor should be prioritized. Going beyond previous research [1], this work presents a novel design of coordinate rotation digital computer (CORDIC) engine which is optimized and speeded up to avoid structural hazards. Finally, the processor is fabricated using TSMC 40nm CMOS technology in a 16-channel EEG system. The computation time of the SVD processor is reduced by 24.7% and the average correlation coefficient between original source signals and extracted ORICA signals is 0.95452.",
author = "Wai-Chi Fang and Chang, {Jui Chung} and Huang, {Kuan Ju} and Feng, {Chih Wei} and Chou, {Chia Ching}",
note = "Publisher Copyright: {\textcopyright} 2014 IEEE.; 10th IEEE Biomedical Circuits and Systems Conference, BioCAS 2014 ; Conference date: 22-10-2014 Through 24-10-2014",
year = "2014",
month = dec,
day = "9",
doi = "10.1109/BioCAS.2014.6981648",
language = "English",
series = "IEEE 2014 Biomedical Circuits and Systems Conference, BioCAS 2014 - Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "73--76",
booktitle = "IEEE 2014 Biomedical Circuits and Systems Conference, BioCAS 2014 - Proceedings",
address = "United States",
}