This paper proposes a new active noise control (ANC) system based on a recursiveleast-squareslattice (RLSL) algorithm by designing secondary-path innovation (SPI) and lattice-order decision (LOD) algorithms. The SPI...
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This paper proposes a new active noise control (ANC) system based on a recursiveleast-squareslattice (RLSL) algorithm by designing secondary-path innovation (SPI) and lattice-order decision (LOD) algorithms. The SPI algorithm associated with the power spectral factorization of the secondary path is designed to apply the RLSL algorithm to the ANC system without the filtered-input structure. The SPI algorithm whitens the error microphone signals into the virtual error signals just ahead of the secondary path to construct the virtual desired signals corresponding to the outputs of the lattice filter. The LOD algorithm is designed to operate the ANC system without knowing the tap length of the optimal finite impulse response (FIR) filter. The decision algorithm using the initial and final estimation errors of the lattice filter estimates the tap length of the optimal FIR filter by increasing the lattice order one-by-one until the final estimation error reaches below a threshold value. Even in environments where the tap length of the optimal FIR filter is unknown, the proposed ANC system with low computational complexity shows almost the same performance as the ANC system based on a filtered-input recursiveleastsquaresalgorithm.
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 implement...
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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 recursiveleast-squareslattice (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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