Sparsely interconnected neural networks for associative memories applying discrete Walsh transform

The conventional synthesis procedure of discrete time sparsely interconnect ed neural networks (DTSINNs) for associative memories may generate the cell s with only self-feedback due to the sparsely interconnected structure. Alt hough this problem is solved by increasing the number of interconnections, hardware implementation becomes very difficult. In this letter, we propose the DTSINN system which stores the 2-dimensional discrete Walsh transforms (DWTs) of memory patterns. As each element of DWT involves the information of whole sample data, our system can associate the desired memory patterns, which the conventional DTSINN fails to do.