Memristor based on ?-In2Se3 for emulating biological synaptic plasticity and learning behavior

Nowadays, memristors are extremely similar to biological synapses and can achieve many basic functions of synapses, making them become a new generation research hotspots for brain-like neurocomputing. In this work, we prepare memristor based on two-dimensional ?-In2Se3 nanosheets, which exhibits excellent electrical properties, faster switching speeds, continuous tunability device conduction. Meanwhile, most bio-synapse be implemented faithfully, such as short-term memory (STM), long-term (LTM), four different types spike-timing-dependent plasticity (STDP), paired-pulse facilitation (PPF). More importantly, systematically study three effective methods LTM, in the reinforcement learning faithfully simulated according Ebbinghaus forgetting curve. Therefore, believe work will promote development computing artificial intelligence.