GAUSSIAN SYNAPSES FOR PROBABILISTIC NEURAL NETWORKS

摘要

Embodiments relate to a Gaussian synapse device configured so that its transfer characteristics resemble a Gaussian distribution. Embodiments of the Gaussian synapse device include an n-type field-effect transistor (FET) and p-type FET with a common contact so that the two FETs are connected in series. Some embodiments include a global back-gate contact and separate top-gate contact to obtain dual-gated FETs. Some embodiments include two different 2D materials used in the channel to generate the two FETs, while some embodiments use a single ambipolar transport material. In some embodiments, the dual-gated structure is used to dynamically control the amplitude, mean and standard deviation of the Gaussian synapse. In some embodiments, the Gaussian synapse device can be used as a probabilistic computational device (e.g., used to form a probabilistic neural network).