A configurable neural phase shifter (NPS) is fabricated for spike neuromorphic circuits by integrating an ionic/Si hybrid synaptic transistor with a conventional MOSFET. NPS can mimic a neural network to process temporal-code pulses by shifting their temporal phases by t ranged between 9.0 and 24.5 ms, which falls in the range observed in biological neural networks. t can also be configured by following the synaptic learning rule of spike-timing-dependent plasticity. The device can significantly simplify the structures and reduce the power consumption of neuromorphic circuits to emulate neural networks for spike signal processing, memory, and learning.
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Zhang et al. (2010) studied this question.
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