TY - GEN
T1 - Multiple stopping criteria and high-precision EMD architecture implementation for Hilbert-Huang transform
AU - Lu, Tsung Che
AU - Chen, Pei Yu
AU - Yeh, Shih Wei
AU - Van, Lan-Da
N1 - Publisher Copyright:
© 2014 IEEE.
PY - 2014/12/9
Y1 - 2014/12/9
N2 - In this work, a multiple stopping criteria and high-precision 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 mm2 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.
AB - In this work, a multiple stopping criteria and high-precision 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 mm2 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.
UR - http://www.scopus.com/inward/record.url?scp=84920538106&partnerID=8YFLogxK
U2 - 10.1109/BioCAS.2014.6981697
DO - 10.1109/BioCAS.2014.6981697
M3 - Conference contribution
AN - SCOPUS:84920538106
T3 - IEEE 2014 Biomedical Circuits and Systems Conference, BioCAS 2014 - Proceedings
SP - 200
EP - 203
BT - IEEE 2014 Biomedical Circuits and Systems Conference, BioCAS 2014 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 10th IEEE Biomedical Circuits and Systems Conference, BioCAS 2014
Y2 - 22 October 2014 through 24 October 2014
ER -