Proposal, Analysis And Demonstration Of Analog/Digital-Mixed Neural Networks Based On Memristive Device Arrays

Artificial neural network (NN) circuits are proposed and analyzed from the viewpoints of flexibility and robustness based on memristive devices. The typical 3-layered fully-connected NN is a primitive unit of Deep Learning (DL) and plays a key role in determining DL performance. We propose three types of NN structure at a circuit level. fully-digital, analog/digital mixed, fully-analog. focusing on digital or analog calculations such as a multiplier accumulator, and examine their figures of merit. One key property of the analog/digital-mixed structure is demonstrated on reconfigurable analog ICs. Important aspects regarding neuromorphic computing are highlighted in our experiments on spike-timing-dependent plasticity on memristive devices and non-linear characteristics.