Binary cellular neural/nonlinear network with programmable floating-gate neurons

This paper presents an implementation of a cellular neural/nonlinear network (CNN) with capacitively coupled neurons that are based on the floating-gate MOSFET (FG-MOS) technology. The circuit is intended for processing black and white (B/W) images. A neuron state is determined by charge distribution in the input of a FG-MOS inverter. The capacitive couplings to the neighbors are one-bit programmable, while the bias template can be programmed with two bits. Also, a fixed state map (transient mask) is included in the cell. The operation of an 8×8 network is illustrated by simulations of selected templates.