A synthesis procedure for Hopfield's continuous-time associative memory

A new technique is presented for designing associative memories to be implemented by Hopfield neural networks. This technique guarantees that each desired memory is stored and is attractive. The procedure also guarantees that the resulting network can be implemented, a requirement often overlooked by other methods. This synthetic procedure does not require a symmetric interconnection matrix; instead, stability is guaranteed by use of the results presented by A.N. Michel et al. (1989). Two examples are presented that demonstrate the synthesis procedure's storage ability and flexibility.<>