Extended Sparse Distributed Memory and Sequence Storage

Abstract

Sparse distributed memory (SDM) is an auto-associative memory system that stores high-dimensional Boolean vectors. SDM uses the same vector for the data (word) and the location where it is stored (address). Here, we present an extension of the original SDM that uses word vectors of larger size than address vectors. This extension preserves many of the desirable properties of the original SDM: auto-associability, content addressability, distributed storage and robustness over noisy inputs. In addition, it adds new functionality, enabling an efficient auto-associative storage of sequences of vectors, as well as of other data structures such as trees. Simulations testing this new memory are described.