A novel machine learning-based approach for the detection and analysis of spontaneous synaptic currents:
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| Hauptverfasser: | , , |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Erlangen ; Nürnberg
Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU)
2022
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| Schlagworte: | |
| Online-Zugang: | Volltext Volltext Volltext |
| Beschreibung: | 1 Online-Ressource |
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| 245 | 1 | 0 | |a A novel machine learning-based approach for the detection and analysis of spontaneous synaptic currents |c Thomas Pircher, Bianca Pircher, Andreas Feigenspan |
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| spelling | Pircher, Thomas Verfasser aut A novel machine learning-based approach for the detection and analysis of spontaneous synaptic currents Thomas Pircher, Bianca Pircher, Andreas Feigenspan Erlangen ; Nürnberg Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU) 2022 1 Online-Ressource txt rdacontent c rdamedia cr rdacarrier Archivierung/Langzeitarchivierung gewährleistet DE-101 pdager Machine learning algorithms Algorithms Neurons Computer software Software tools Signal filtering Preprocessing Signal decoders Pircher, Bianca Verfasser aut Feigenspan, Andreas Verfasser aut Sonderdruck aus PLoS ONE Vol. 17 (2022) 10.1371/journal.pone.0273501 https://nbn-resolving.org/urn:nbn:de:bvb:29-opus4-214108 Resolving-System kostenfrei Volltext https://d-nb.info/1279277467/34 Langzeitarchivierung Nationalbibliothek kostenfrei Volltext application/pdf https://open.fau.de/handle/openfau/21410 Verlag kostenfrei Volltext 1\p aepkn 0,82321 20230128 DE-101 https://d-nb.info/provenance/plan#aepkn 2\p emasg 0,32465 20230128 DE-101 https://d-nb.info/provenance/plan#emasg 3\p npi 20230127 DE-101 https://d-nb.info/provenance/plan#npi |
| spellingShingle | Pircher, Thomas Pircher, Bianca Feigenspan, Andreas A novel machine learning-based approach for the detection and analysis of spontaneous synaptic currents |
| title | A novel machine learning-based approach for the detection and analysis of spontaneous synaptic currents |
| title_auth | A novel machine learning-based approach for the detection and analysis of spontaneous synaptic currents |
| title_exact_search | A novel machine learning-based approach for the detection and analysis of spontaneous synaptic currents |
| title_exact_search_txtP | A novel machine learning-based approach for the detection and analysis of spontaneous synaptic currents |
| title_full | A novel machine learning-based approach for the detection and analysis of spontaneous synaptic currents Thomas Pircher, Bianca Pircher, Andreas Feigenspan |
| title_fullStr | A novel machine learning-based approach for the detection and analysis of spontaneous synaptic currents Thomas Pircher, Bianca Pircher, Andreas Feigenspan |
| title_full_unstemmed | A novel machine learning-based approach for the detection and analysis of spontaneous synaptic currents Thomas Pircher, Bianca Pircher, Andreas Feigenspan |
| title_short | A novel machine learning-based approach for the detection and analysis of spontaneous synaptic currents |
| title_sort | a novel machine learning based approach for the detection and analysis of spontaneous synaptic currents |
| url | https://nbn-resolving.org/urn:nbn:de:bvb:29-opus4-214108 https://d-nb.info/1279277467/34 https://open.fau.de/handle/openfau/21410 |
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