The hardware design of supervised learning (SL) in spiking neural network (SNN) prefers 3-terminal memristive synapses, where the third terminal is used to impose supervise signals. In this work we address this demand by fabricating graphene transistor gated through organic ferroelectrics of polyvinylidene fluoride. Through gate tuning not only is the nonvolatile and continuous change of graphene channel conductance demonstrated, but also the transition between electron-dominated and hole-dominated transport. By exploiting the adjustable bipolar characteristic, the graphene-ferroelectric transistor can be electrically reconfigured as potentiative or depressive synapse and in this way complementary synapses are realized. The complementary synapse and neuron circuit is then constructed to execute remote supervise method (ReSuMe) of SNN, and quick convergence to successful learning is found through network-level simulation when applying to a SL task of classifying 3 × 3-pixel images. The presented design of graphene-ferroelectric transistor-based complementary synapses and quantitative simulation may indicate a potential approach to hardware implementation of SL in SNN.
Mechanical resonance is a common problem in drive systems with elastic coupling. On-line adaptive notch filter is widely used to make system stable and the key of this method is to identify natural torsional frequency from speed feedback signal. However, because of common adoption of digital control and expansion of system bandwidth, oscillation frequency of the system is more likely to deviate from natural torsional frequency to a higher one. When oscillation frequency is shifted, the enabled notch filter with erroneous notch frequency causes an oscillation with a lower frequency and even makes resonance severer. In order to explain this phenomenon, the classical two-mass model based classification of resonances is checked at first. Then, by taking digital control, current loop delay and saturation nonlinearity into consideration, an improved digital mechanical resonance model is proposed and a criterion for oscillation frequency deviation is finally obtained. Furthermore, a more widely applicable and robust notch filter tuning strategy with no oscillation rebound is presented. In the end, the validity of aforementioned analysis and strategy is verified by experimental results.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.