2:45 PM - 3:15 PM
[18p-432-4] Application of resistive change devices for realization of brain-inspired neuromorphic hardware
Keywords:semiconductor, memristor
Whereas a learning process in artificial intelligence consumes a great amount of power, a human brain can learn its environments and situations with an extremely high energy efficiency. Brain inspired neuromorphic hardware, which is modelled after the information processing principle in a biological brain, is intensively studied to realize such low power online learning as human brains do. In this talk, we discuss synaptic behaviors of resistive change devices for application to neuromorphic hardware technologies.