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FPGA implementation of adaptive segmentation for non-stationary biomedical signals

Circuits, Devices & Systems, IET(2010)

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摘要
A novel field programmable gate array (FPGA) implementation of adaptive segmentation for non-stationary biomedical signals is presented. The design uses Simulink-to-FPGA methodology and has been successfully implemented onto Xilinx Virtex II Pro device. The implementation is based on the recursive least-squares lattice (RLSL) algorithm using double-precision floating-point arithmetic and is programmable for users providing data length, system order and threshold selection functions. The implemented RLSL design provides very good performance in obtaining accurate conversion factor values with a mean correlation above 99% and detecting segment boundaries with high accuracy for both synthesised and real-world biomedical signals.
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关键词
field programmable gate arrays,least squares approximations,medical signal processing,Simulink-to-FPGA methodology,adaptive segmentation,double-precision floating-point arithmetic,field programmable gate array,nonstationary biomedical signals,recursive least-squares lattice algorithm,segment boundary detection
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