| Форма представления | Статьи в зарубежных журналах и сборниках |
| Год публикации | 2017 |
| Язык | английский |
|
Дистефано Сальваторе , автор
Зыков Евгений Юрьевич, автор
Магид Евгений Аркадьевич, автор
Таланов Максим Олегович, автор
|
|
Герасимов Юрий Александрович, автор
|
| Библиографическое описание на языке оригинала |
Talanov M., Zykov E., Erokhin V., Magid E., Distefano S., Gerasimov Yu., Vallverdu J. Modeling inhibitory and excitatory synapse learning in the memristive neuron model // ICINCO 2017 - Proceedings of the 14th International Conference on Informatics in Control, Automation and Robotics. - 2017. - Vol. 2. - p. 514-521. |
| Аннотация |
In this paper we present the results of simulation of exitatory Hebbian and inhibitory «sombrero'' learning of a hardware architecture based on organic memristive elements and operational amplifiers implementing an artificial neuron we recently proposed. This is a first step towards the deployment on robots of a bio-plausible simulation, currently developed in the neuro-biologically inspired cognitive architecture (NeuCogAr) implementing basic emotional states or affects in a computational system, in the context of our «Robot dream'' project.
The long term goal is to re-implement dopamine, serotonin and noradrenaline pathways of NeuCogAr in a memristive hardware. |
| Ключевые слова |
Cognitive architecture, memristive elements, circuits, artificial neuron, affects, biologically inspired robotic system |
| Название журнала |
ICINCO 2017 - Proceedings of the 14th International Conference on Informatics in Control, Automation and Robotics
|
| URL |
https://www.scitepress.org/PublicationsDetail.aspx?ID=aQs6etIJ2NQ=&t=1 |
| Пожалуйста, используйте этот идентификатор, чтобы цитировать или ссылаться на эту карточку |
https://repository.kpfu.ru/?p_id=166180 |
| Файлы ресурса | |
|
|
Полная запись метаданных  |
| Поле DC |
Значение |
Язык |
| dc.contributor.author |
Дистефано Сальваторе |
ru_RU |
| dc.contributor.author |
Зыков Евгений Юрьевич |
ru_RU |
| dc.contributor.author |
Магид Евгений Аркадьевич |
ru_RU |
| dc.contributor.author |
Таланов Максим Олегович |
ru_RU |
| dc.contributor.author |
Герасимов Юрий Александрович |
ru_RU |
| dc.date.accessioned |
2017-01-01T00:00:00Z |
ru_RU |
| dc.date.available |
2017-01-01T00:00:00Z |
ru_RU |
| dc.date.issued |
2017 |
ru_RU |
| dc.identifier.citation |
Talanov M., Zykov E., Erokhin V., Magid E., Distefano S., Gerasimov Yu., Vallverdu J. Modeling inhibitory and excitatory synapse learning in the memristive neuron model // ICINCO 2017 - Proceedings of the 14th International Conference on Informatics in Control, Automation and Robotics. - 2017. - Vol. 2. - p. 514-521. |
ru_RU |
| dc.identifier.uri |
https://repository.kpfu.ru/?p_id=166180 |
ru_RU |
| dc.description.abstract |
ICINCO 2017 - Proceedings of the 14th International Conference on Informatics in Control, Automation and Robotics |
ru_RU |
| dc.description.abstract |
In this paper we present the results of simulation of exitatory Hebbian and inhibitory «sombrero'' learning of a hardware architecture based on organic memristive elements and operational amplifiers implementing an artificial neuron we recently proposed. This is a first step towards the deployment on robots of a bio-plausible simulation, currently developed in the neuro-biologically inspired cognitive architecture (NeuCogAr) implementing basic emotional states or affects in a computational system, in the context of our «Robot dream'' project.
The long term goal is to re-implement dopamine, serotonin and noradrenaline pathways of NeuCogAr in a memristive hardware. |
ru_RU |
| dc.language.iso |
ru |
ru_RU |
| dc.subject |
Cognitive architecture |
ru_RU |
| dc.subject |
memristive elements |
ru_RU |
| dc.subject |
circuits |
ru_RU |
| dc.subject |
artificial neuron |
ru_RU |
| dc.subject |
affects |
ru_RU |
| dc.subject |
biologically inspired robotic system |
ru_RU |
| dc.title |
Modeling inhibitory and excitatory synapse learning in the memristive neuron model |
ru_RU |
| dc.type |
Статьи в зарубежных журналах и сборниках |
ru_RU |
|
EN 
中文 
ES 
Карта сайта
