3. Conclusion
We have reported a novel memtransistor of which the channel conductance can be modulated by the ions doping and dedoping under the electric field driving. By adjusting the amplitude of the gate stimuli, both short-term and long-term memory can be realized. Short-term memory effect, such as PPF, SRDP and single pulse stimuli parameters were investigated. Retention, multi-states, LTP and LTD were also acquired to exploit the long-term ion dynamics. By using the short-term accumulation effect, we implemented pattern reconstruction from a set of noisy images. Owing to the energy barrier for ions moving and the inevitable voltage drop on the passivation layer, nonlinear short-term responses can be utilized for hardware softplus neurons and filtering units. By reconfiguring the temporal scales of ion-modulated memtransistor, we proposed an artificial neuromorphic vision system in which filtering units, synapses and activation neurons were constructed with the memtransistors. Moreover, we performed system-level simulations of hardware neural networks with the ion-modulated memtransistors. All the experimental and simulation results suggest the proposed ion-modulated memtransistor can reduce the delay and energy cost in classifying the noisy images, and thus provides an energy efficent way to construct neuromorphic artificial vision systems.