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Spike Sorting

Spike sorting is a class of techniques used in the analysis of electrophysiological data. Spike sorting algorithms use the shape(s) of waveforms collected with one or more electrodes in the brain to distinguish the activity of one or more neurons from background electrical noise.

Papers

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Showing 11–20 of 51 papers

TitleStatusHype
L-Sort: An Efficient Hardware for Real-time Multi-channel Spike Sorting with Localization—0
Neuromorphic Online Clustering and Classification—0
NeuSort: An Automatic Adaptive Spike Sorting Approach with Neuromorphic Models—0
Adaptive SpikeDeep-Classifier: Self-organizing and self-supervised machine learning algorithm for online spike sorting—0
Edge computing on TPU for brain implant signal analysisCode0
Zydeco-Style Spike Sorting Low Power VLSI Architecture for IoT BCI Implants—0
An Adaptive Contrastive Learning Model for Spike Sorting—0
Toward A Formalized Approach for Spike Sorting Algorithms and Hardware EvaluationCode0
Efficient Approximation of Action Potentials with High-Order Shape Preservation in Unsupervised Spike Sorting—0
Three-dimensional spike localization and improved motion correction for Neuropixels recordings—0
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