Hybrid-control of synapse circuits for programmable cellular neural networks

Abstract

This paper describes a hybrid weight-control strategy for VLSI realizations of programmable Cellular Neural Networks (CNNs), based on auto-tuning of analog control signals to digitally specified values. The approach merges the advantages of digital and analog programmability, achieving low areas and reduced number of control lines, simplifying the control and storage of weight values, and eliminating their dependency on global process-parameter variations