Full metadata record
DC FieldValueLanguage
dc.contributor.authorShih, Wei-Yehen_US
dc.contributor.authorHuang, Kuan-Juen_US
dc.contributor.authorChen, Chiu-Kuoen_US
dc.contributor.authorFang, Wai-Chien_US
dc.contributor.authorCauwenberghs, Gerten_US
dc.contributor.authorJung, Tzyy-Pingen_US
dc.date.accessioned2014-12-08T15:30:04Z-
dc.date.available2014-12-08T15:30:04Z-
dc.date.issued2012en_US
dc.identifier.isbn978-1-4673-2293-5en_US
dc.identifier.issn2163-4025en_US
dc.identifier.urihttp://hdl.handle.net/11536/21544-
dc.description.abstractThis paper presents an effective chip implementation of a real-time eight-channel electroencephalogram signal processor based on on-line recursive independent component analysis (ORICA) algorithm. The system architecture is composed of a memory unit, a whitening unit, an ORICA training unit, and an ORICA computation unit. The proposed architecture is implemented using TSMC 90 nm CMOS technology. It occupies a core area of 800x800 mu m(2) and consumes 4.18 mW at a core supply voltage of 1.0 V and 50 MHz clock operating frequency. Simulated super and sub-Gaussian signals are used to verify the system. The separated signals match those obtained using off-line Matlab-based analysis.en_US
dc.language.isoen_USen_US
dc.titleAn Effective Chip Implementation of A Real-time Eight-channel EEG Signal Processor Based on On-line Recursive ICA Algorithmen_US
dc.typeProceedings Paperen_US
dc.identifier.journal2012 IEEE BIOMEDICAL CIRCUITS AND SYSTEMS CONFERENCE (BIOCAS): INTELLIGENT BIOMEDICAL ELECTRONICS AND SYSTEM FOR BETTER LIFE AND BETTER ENVIRONMENTen_US
dc.citation.spage192en_US
dc.citation.epage195en_US
dc.contributor.department電子工程學系及電子研究所zh_TW
dc.contributor.departmentDepartment of Electronics Engineering and Institute of Electronicsen_US
dc.identifier.wosnumberWOS:000316563200063-
Appears in Collections:Conferences Paper