2008
NeurIPS
NeurIPS 2008
Spike Feature Extraction Using Informative Samples
Abstract
This paper presents a spike feature extraction algorithm that targets real-time spike sorting and facilitates miniaturized microchip implementation. The proposed algorithm has been evaluated on synthesized waveforms and experimentally recorded sequences. When compared with many spike sorting approaches our algorithm demonstrates improved speed, accuracy and allows unsupervised execution. A preliminary hardware implementation has been realized using an integrated microchip interfaced with a personal computer.
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Interdisciplinary Bridge
- Artificial Intelligence and Healthcare & Medicine and Interdisciplinary and Mathematics & Optimization
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Trend Setter
- Signal Processing
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Hot Topic Early Bird
- real-time processing
Authors
Topics
Machine Learning > Core Methods > Classification
Machine Learning > Learning Types > Self-Supervised Learning
Healthcare & Medicine > Research > Biosignal Processing
Machine Learning > Core Methods > Feature Learning
Mathematics & Optimization > Mathematics > Signal Processing
Interdisciplinary > Science > Neuroscience
Machine Learning > Core Methods > Feature Extraction