A Memory-Based STDP Rule for Stable Attractor Dynamics in Boolean Recurrent Neural Networks

0503755 - ÚI 2020 RIV US eng C - Konferenční příspěvek (zahraniční konf.)
Cabessa, Jérémie - Villa, A.
A Memory-Based STDP Rule for Stable Attractor Dynamics in Boolean Recurrent Neural Networks.
IJCNN 2019. International Joint Conference on Neural Networks Proceedings. New York: IEEE, 2019, č. článku N-20311. ISBN 978-1-7281-1985-4.
[IJCNN 2019. International Joint Conference on Neural Networks /32./. Budapest (HU), 14.07.2019-19.07.2019]
Grant CEP: GA ČR(CZ) GA19-05704S
Institucionální podpora: RVO:67985807
Klíčová slova: learning (artificial intelligence) * recurrent neural nets
Obor OECD: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Trvalý link: http://hdl.handle.net/11104/0295541