Associative memory design using discrete-time second-order neural networks with local interconnections

In this brief a design method for associative memories using a new model of discrete-time high-order neural networks which includes local interconnections among neurons is illustrated. The synthesis approach, which exploits the properties of pseudoinverse matrices, is flexible as it enables one to choose the complexity of the associative memory to be designed; that is, it can generate networks for associative memories with first-order and/or higher order interactions among neurons. The suggested technique preserves local interconnections among neurons, making feasible an implementation of such networks. Simulation results and comparisons among different neural architectures are reported to show the applicability of the proposed method.