An investigation on local minima of a Hopfield network for optimization circuits

The Hopfield architecture can be utilized in the VLSI implementation of several important optimization functions. A description is given of the properties of local minima in the energy function of Hopfield networks. A novel design technique to eliminate such local minima has been developed. The neural-based analog-to-digital converter is used as an example to demonstrate this design technique. Experimental results agree well with theoretical calculations on the output characteristics of the analog-to-digital converter.<>