A mixed-signal spatio-temporal signal classifier for on-sensor spike sorting
In this paper, we combine recent progress in neuro-morphic computation and neuromorphic mixed-signal hardwareto present the first step towards an implementation of a neu-romorphic spike sorting algorithm, that has been proven ableto extract and decode spikes, in real time. This implementationis based on TSMC 180nm technology. Combined with a neu-ral recording system, we anticipate this approach to leverageefficient neuromorphic brain-machine interfaces for embeddedrehabilitation prosthetic control.
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Publication: Congress
1624015057480
June 18, 2021
/research/publications/a-mixed-signal-spatio-temporal-signal-classifier-for-on-sensor-spike-sorting
In this paper, we combine recent progress in neuro-morphic computation and neuromorphic mixed-signal hardwareto present the first step towards an implementation of a neu-romorphic spike sorting algorithm, that has been proven ableto extract and decode spikes, in real time. This implementationis based on TSMC 180nm technology. Combined with a neu-ral recording system, we anticipate this approach to leverageefficient neuromorphic brain-machine interfaces for embeddedrehabilitation prosthetic control. - G. Haessig, D. García-Lesta, R. Benosman, G. Lenz, P. Dudek
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