Implementation of STDP Learning for Non-volatile Memory-based Spiking Neural Network using Comparator Metastability

Abstract

This paper presents a circuit for spike-timing dependent plasticity (STDP) learning of a non-volatile memory (NVM) based spiking neural network (SNN). Unlike conventional hardware for implementation of STDP learning, the proposed circuit does not require additional memory, amplifiers, or an STDP spike generator. Instead, the circuit utilizes the comparison time information of the dynamic comparator to implement a non-linear transfer curve of STDP learning. The circuit includes a dynamic comparator, NVM device, and some digital circuitry to write the conductance of NVM according to the STDP learning rule. Finally, the conductance response model and designed circuit for the STDP learning are used to compare the simulation results of STDP with mathematical STDP. Applications of the proposed circuit are in the design of NVM-based SNN hardware or other bio-inspired hardware systems. © 2019 IEEE.