In this paper, we propose an adaptive quantization method that can easily transfer the weights, which are trained in software network with floating point operation, to the real synaptic devices… Click to show full abstract
In this paper, we propose an adaptive quantization method that can easily transfer the weights, which are trained in software network with floating point operation, to the real synaptic devices in hardware-based neural networks and maintain high performance. An n-type gated Schottky diode is investigated as a synaptic device, and the conductance behavior of this device is modeled successfully. Max value normalization and
               
Click one of the above tabs to view related content.