Two analog counters for neural network implementation
Kurosh Madani, Patrick F. Garda, Eric Belhaire, Francis Devos · IEEE Journal of Solid-State Circuits · 1991
Simple analog circuits which are useful for the implementation of the synchronous Boltzmann machine learning algorithms are presented. A simple charge-transfer-based analog counter is described. The authors give a functional model of its behavior and analyze the differences between this model and the counter implementation. They also present simulation results and the test of a prototype. Along the same lines, they study a switched-current-based counter, which achieves better results (dynamic range, linearity) through higher complexity.>