Implementing Spike-Timing-Dependent Plasticity and Unsupervised Learning in a Mainstream NOR Flash Memory Array

In this work, we present the first implementation of spike-timing-dependent plasticity (STDP) and unsupervised learning in a mainstream NOR Flash memory array based on floating-gate cells. A simple yet effective word-line and bit-line pulse scheme is proposed to make a common-ground double-polysilicon NOR array in 40 nm embedded technology work as an artificial synaptic array in a spiking neural network learning according to the STDP rule, with no change required either to the array or to the cell design. With this scheme, long-term potentiation and long-term depression of the synaptic weights are achieved, respectively, by hot-hole injection and channel hot-electron injection at the drain side of the cells. Unsupervised learning is experimentally demonstrated in the array, paving the way for the development of large-scale and high-density neuromorphic systems based on mainstream nonvolatile memory technologies.