Skip to Main Content
During the 1990s, Ritter introduced a new family of associative memories based on lattice algebra instead of linear algebra. These memories provide unlimited storage capacity, unlike linear-correlation-based models. The canonical lattice-based memories, however, are susceptible to noise in the initial input data. In this brief, we present novel methods of encoding and decoding lattice-based memories using two families of ordered weighted average (OWA) operators. The result is a greater robustness to distortion in the initial input data, and a greater understanding of the effect of the choice of encoding and decoding operators on the behavior of the system, with the tradeoff that the time complexity for encoding is increased.