| 초록 |
In the upcoming era of “Big Data”, a vast amount of unstructured data are not efficaciously processed due to the limitation on the communication between processing and memory units in the conventional von Neumann computing system. In this work, we develop a cobalt oxide-based memristor that can provide synaptic functions of artificial neural network for the neuromorphic computing system. The device shows threshold switching (TS) characteristics, turned on over threshold voltage, and its conduction mechanism is based on space charge limited current (SCLC). The memristor device has a variety of synaptic characteristics, such as delay-saturation-relaxation dynamics, paired-pulse facilitation (PPF), short-term potentiation (STP), long-term potentiation (LTP), and degree of memorization or forgetting. Furthermore, it is also confirmed that this device is feasible to emulate integration and fire events of artificial neuron. |
