Modeling of Spiking Analog Neural Circuits with Hebbian Learning, Using Amorphous Semiconductor Thin Film Transistors with Silicon Oxide Nitride Semiconductor Split Gates

This paper uses the results of the characterization of amorphous semiconductor thin film transistors (TFTs) with a split gate and the quasi-permanent memory structure referred to as silicon oxide nitride semiconductor (SONOS) gates, to model spiking neural circuits with Hebbian learning ability. MOSFETs using organic (tris 8-hydroxyquinolinate aluminum (Alq3), copper phthalocyanine (CuPc)) and inorganic (ZnO) amorphous materials can be …