An architecture of small-scaled neuro-hardware using probabilistically-calculated pulse neurons

This article proposed an architecture of a neuro-hardware that can be realized on by far a small-scaled circuit compared to the conventional approach. In order to reduce the scale of the circuits, the architecture employs a new method of computing the membrane potential and the sigmoidal function by encapsulating the probability properties into relative delay between two pulses of the different signal lines. Proposed architecture enables to integrate more than one hundred of neurons on a latest FPGA chip, which means thirteen-fold miniaturization compared to conventional architecture.