Simple 'Neural' optimization networks: An A/D converter, signal decision circuit and a linear programming circuit.

We describe how several optimization problems can be rapidly solved by highly-interconnected networks of simple analog processors. Analog-to-digital, (A/D), conversion was considered as a simple optimization problem, and an A/D converter of novel architecture was designed. A/D conversion is a simple example of a more general class of signal-decision problems which we show could also be solved by appropriately-constructed networks. Circuits to solve these problems were designed using general principles which result from an understanding of the basic collective computational properties of a specific class of analog-processor networks. We also show that a network which solves linear programming problems can be understood from the same concepts.