Modulating 3D memristor synapse by analog spiking pulses for bioinspired neuromorphic computing

Memristor based artificial synapses have demonstrated great potential for bioinspired neuromorphic computing in recent years. To emulate synaptic fimctions, such as short-term plasticity and long-term potentiation/depression, square pulses or combined complex pulse groups are applied on the device. However, in biological neuron systems, the action potentials are analog pulses with similar amplitudes. Furthermore, in biological systems, the intensity of the stimulus is coded into the frequency of action potentials to modulate the weight of synapses. Toward this programming method, we applied a series of analog spiking pulses with same peaks on Ru/TiOJTiN 3D memristor to emulate synaptic functions, such as long-term potentiation/depression and synaptic saturation. Moreover, we demonstrated the conductance change of the device under different stimulus frequencies of analog spiking pulses and described the statistical results of conductance change value, which shows that the device conductance has a larger change value under a higher spiking frequency with identical pulse number. These results show that the analog spiking pulses can well modulate the memristor-based synaptic weight and have a great potential for bioinspired computing in the future.

Memristor based artificial synapses have demonstrated great potential for bioinspired neuromorphic computing in recent years.To emulate synaptic functions, such as short-term plasticity and long-term potentiation/depression, square pulses or combined complex pulse groups are applied on the device. However, in biological neuron systems, the action potentials are analog pulses with similar amplitudes. Furthermore, in biological systems, the intensity of the stimulus is coded into the frequency of action potentials to modulate the weight of synapses. Toward this programming method, we applied a series of analog spiking pulses with same peaks on Ru/TiO_x/TiN 3D memristor to emulate synaptic functions, such as long-term potentiation/depression and synaptic saturation. Moreover, we demonstrated the conductance change of the device under different stimulus frequencies of analog spiking pulses and described the statistical results of conductance change value, which shows that the device conductance has a larger change value under a higher spiking frequency with identical pulse number. These results show that the analog spiking pulses can well modulate the memristor-based synaptic weight and have a great potential for bioinspired computing in the future.