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Spiking activity of individual neurons can be separated from the acquired multi-unit activity with spike sorting methods. Processing the recorded high-dimensional neural data can take a large amount of time when performed on general-purpose computers. In this paper, an FPGA-based real-time spike sorting system is presented which takes into account the spatial correlation between the electrical signals recorded with closely-packed recording sites to cluster multi-channel neural data. The system uses a spatial window-based version of the O
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