A compact neuromorphic nanodevice with inherent learning and memory properties emulating those of biological synapses is the key to developing artificial neural networks rivaling their biological counterparts. Experimental results showed that memorization with a wide time scale from volatile to permanent can be achieved in a WO 3− x -based nanoionics device and can be precisely and cumulatively controlled by adjusting the device’s resistance state and input pulse parameters such as the amplitude, interval, and number. This control is analogous to biological synaptic plasticity including short-term plasticity, long-term potentiation, transition from short-term memory to long-term memory, forgetting processes for short- and long-term memory, learning speed, and learning history. A compact WO 3− x -based nanoionics device with a simple stacked layer structure should thus be a promising candidate for use as an inorganic synapse in artificial neural netwo...
Rui Yang, Kazuya Terabe, Yiping Yao, Tohru Tsuruoka, Tsuyoshi Hasegawa, James K Gimzewski and Masakazu Aono
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Rui Yang, Kazuya Terabe, Yiping Yao, Tohru Tsuruoka, Tsuyoshi Hasegawa, James K Gimzewski and Masakazu Aono
Click for full article
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