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.