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Unsupervised waveform classification for multi-neuron recordings: a real-time, software-based system. I. Algorithms
M Salganicoff1, M Sarna, L Sax
1Department of Physiology, University of Pennsylvania, Philadelphia 19104.
Abstract:
We describe a new, mostly software-based device for the sorting of waveforms in an extracellular multi-neuron recording situation. The sorting algorithm is largely unattended, and, after an initial 'learning' process, works in real time. Shape comparisons are based on up to 8 time points in the waveform; these points (the reduced feature set) are chosen automatically by analyzing the current incoming data stream. A feasibility version has been implemented on a LSI-11/2 system, using FORTRAN for set-up calculations and assembler for the real-time operations. Detailed comparisons with performance of other sorting devices are presented in the companion paper.