Constraint Modules: An Introduction

Abstract

We describe a methodology for solving convex constraint problems using analog circuits. We demonstrate how this methodology can be used to design circuits that solve function-fitting problems through iterated gradient descent. In particular, we show how to build a small circuit that can model a nonlinearity by observation, and predistort to compensate for this nonlinearity. The system fits into a broader effort to investigate non-traditional approaches to circuit design. First, it breaks the traditional input-output abstraction barrier; all ports are bidirectional. Second, it uses primarily local properties of the circuit to show stability. Such stability arguments can be scaled to much more complex systems than traditional stability criteria.