DC Field | Value | Language |
---|---|---|
dc.contributor.author | Paik, Se-Bum | ko |
dc.contributor.author | Park, Youngjin | ko |
dc.date.accessioned | 2021-10-08T06:30:15Z | - |
dc.date.available | 2021-10-08T06:30:15Z | - |
dc.identifier.uri | http://hdl.handle.net/10203/288098 | - |
dc.description.abstract | Provided is a spiking neural network system for dynamical control of flexible, stable, and hybrid memory storage. An information storage method may include converting input information to a temporal pattern in a form of a spike; and storing the information that is converted to the temporal pattern in a spiking neural network. The storing may comprise storing information by applying, to the spiking neural network, a spike-timing-dependent plasticity (STDP) learning rate that is an unsupervised learning rule. | - |
dc.title | Spiking neural network system for dynamic control of flexible, stable and hybrid memory storage | - |
dc.title.alternative | 신경망 시스템을 이용한 정보의 장기, 단기, 및 하이브리드 기억을 위한 방법 | - |
dc.type | Patent | - |
dc.type.rims | PAT | - |
dc.contributor.localauthor | Paik, Se-Bum | - |
dc.contributor.nonIdAuthor | Park, Youngjin | - |
dc.contributor.assignee | KAIST | - |
dc.identifier.iprsType | 특허 | - |
dc.identifier.patentApplicationNumber | 15720772 | - |
dc.identifier.patentRegistrationNumber | 11068774 | - |
dc.date.application | 2017-09-29 | - |
dc.date.registration | 2021-07-20 | - |
dc.publisher.country | US | - |
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