Comparison of neural spike classification techniques

J. P. Stitt, R. P. Gaumond, J. L. Frazier, F. E. Hanson

Research output: Contribution to journalConference articlepeer-review

5 Scopus citations

Abstract

This paper presents an Artificial Neural Network (ANN) capable of sorting neural spikes contained in a single-channel multiunit recording. The ANN performs very well when compared with Template Matching and Principal Components, two of the conventional optimal spike classification methods that have been widely used for sorting action potentials.

Original languageEnglish (US)
Pages (from-to)1092-1094
Number of pages3
JournalAnnual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
Volume3
StatePublished - 1997
EventProceedings of the 1997 19th Annual International Conference of the IEEE Engineering in Medicine and Biology Society - Chicago, IL, USA
Duration: Oct 30 1997Nov 2 1997

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

Fingerprint

Dive into the research topics of 'Comparison of neural spike classification techniques'. Together they form a unique fingerprint.

Cite this