A programmable g/sub m/-C CNN implementation
D. Lim, G.S. Moschytz · 2002
An implementation of a programmable cellular neural network is reported. It overcomes some of the limiting characteristics and restrictions inherent in CMOS VLSI technologies, and allows an arbitrarily large continuous-time analog CNN to be built up by modularly connecting CNN chips with a modest number of cells. The template values are implemented as sets of unit and half-unit OTAs and are digitally step-wise programmable. The design incorporates an offset compensation and initialization circuit. All external input, output and control signals are electrical and digital. The design was carried out in a 0.8 /spl mu/ CMOS technology. Each cell occupies 0.78 mm/sup 2/, including all support circuitry. Matching accuracy was measured and operation was verified on numerous uncoupled and propagation-type templates.