Gradient method of learning for stochastic kinetic model of neuron
| dc.contributor.author | Świetlicka, Aleksandra | |
| dc.contributor.author | Gugała, Karol | |
| dc.contributor.author | Karón, Igor | |
| dc.contributor.author | Kolanowski, Krzysztof | |
| dc.contributor.author | Majchrzycki, Mateusz | |
| dc.contributor.author | Rybarczyk, Andrzej | |
| dc.date.accessioned | 2014-07-14T07:23:21Z | |
| dc.date.available | 2014-07-14T07:23:21Z | |
| dc.date.issued | 2013 | |
| dc.description.abstract | In this paper we are focusing on the kinetic extension [4] of classic model of Hodgkin and Huxley [2]. We are showing the descent gradient method used in the learning process of neuron, which is described with stochastic kinetic model. In comparison with [1] we use only 3 weights instead of 9: gNa; gK and gL: We show that this model behaves equally accurate as the model of Hodgkin and Huxley with slighter system description. | en |
| dc.format | 2 s. | cs |
| dc.format.mimetype | application/pdf | |
| dc.identifier.citation | ISTET 2013: International Symposiumon Theoretical Electrical Engineering: 24th – 26th June 2013, Pilsen, Czech Republic, p. III-17-III-18. | en |
| dc.identifier.isbn | 978-80-261-0246-5 | |
| dc.identifier.uri | http://hdl.handle.net/11025/11489 | |
| dc.language.iso | en | en |
| dc.publisher | University of West Bohemia | en |
| dc.relation.ispartofseries | ISTET: International Symposium on Theoretical Electrical Engineering | en |
| dc.rights | © University of West Bohemia | en |
| dc.rights.access | openAccess | en |
| dc.subject | stochastický kinetický model neuronu | cs |
| dc.subject | gradientní metoda učení | cs |
| dc.subject | Hodgin-Huxleyho model | cs |
| dc.subject.translated | stochastic kinetic model of neuron | en |
| dc.subject.translated | gradient method of learning | en |
| dc.subject.translated | Hodgkin-Huxley model | en |
| dc.title | Gradient method of learning for stochastic kinetic model of neuron | en |
| dc.type | konferenční příspěvek | cs |
| dc.type | conferenceObject | en |
| dc.type.status | Peer-reviewed | en |
| dc.type.version | publishedVersion | en |
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