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- W4210703918 abstract "This paper presents a Correlational Combination (CC) algorithm and its hardware implementation to be used in future multi-channel real-time spike sorting systems. Preprocessing of neural spikes are required to eliminate duplication for neural spikes recorded from a neural probe with densely spaced recording channels. In this work, we proposed using Pearson's correlation to identify duplicated neural spikes and to combine them selectively to improve SNR for a representative spike prior to performing spike sorting. Other approaches (Single Selection and Average All) were also compared with simulated multi-channel neural spikes and CC has the highest SNR for both software and hardware implementations. A hardware implementation of the CC algorithm was realized with a Xilinx Zynq-UltraScale+ field programmable gate array (FPGA). A SNR improvement of 93% was achieved when compared to the other approaches. A processing latency of <tex>$1.58 mu s$</tex> for the CC hardware module was achieved when a 250MHz system clock was used to drive the FPGA." @default.
- W4210703918 created "2022-02-08" @default.
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- W4210703918 date "2021-11-22" @default.
- W4210703918 modified "2023-09-28" @default.
- W4210703918 title "A real-time correlational combination algorithm to improve SNR for multi-channel neural recordings" @default.
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- W4210703918 doi "https://doi.org/10.1109/apccas51387.2021.9687737" @default.
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