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dc.contributor.authorLu, Tsung-Cheen_US
dc.contributor.authorChen, Pei-Yuen_US
dc.contributor.authorYeh, Shih-Weien_US
dc.contributor.authorVan, Lan-Daen_US
dc.date.accessioned2016-03-28T00:05:41Z-
dc.date.available2016-03-28T00:05:41Z-
dc.date.issued2014-01-01en_US
dc.identifier.isbn978-1-4799-2346-5en_US
dc.identifier.issn2163-4025en_US
dc.identifier.urihttp://hdl.handle.net/11536/129760-
dc.description.abstractIn this work, a multiple stopping criteria and high-recision empirical mode decomposition (EMD) hardware architecture implementation is proposed for Hilbert-Huang transform (HHT) in biomedical signal processing. The proposed architecture can support multiple stopping criteria including the constant criteria, the SD criteria and the ratio criteria. The 38-bit floating point precision is adopted in this work to support 10 IMF components with enough accuracy. The off-chip memory architecture is adopted to increase the processing capacity. By the pipelined cubic spline coefficient unit (PCSCU), the computation time can be reduced. The proposed EMD hardware architecture is implemented in TSMC 90 nm CMOS process with the core area of 4.47 mm(2) at the operating frequency of 40 MHz. The post-layout simulation result shows that our work with the constant criterion can speed up the performance 50.4 times compared to the software computation on a single core of ARM11 for 2K data size breathing signals.en_US
dc.language.isoen_USen_US
dc.titleMultiple Stopping Criteria and High-Precision EMD Architecture Implementation for Hilbert-Huang Transformen_US
dc.typeProceedings Paperen_US
dc.identifier.journal2014 IEEE BIOMEDICAL CIRCUITS AND SYSTEMS CONFERENCE (BIOCAS)en_US
dc.citation.spage200en_US
dc.citation.epage203en_US
dc.contributor.department資訊工程學系zh_TW
dc.contributor.departmentDepartment of Computer Scienceen_US
dc.identifier.wosnumberWOS:000366049300068en_US
dc.citation.woscount0en_US
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