title: Integer sparse distributed memory: analysis and results.
abstract: Sparse distributed memory is an auto-associative memory system that stores high dimensional Boolean vectors. Here we present an extension of the original SDM, the Integer SDM that uses modular arithmetic integer vectors rather than binary vectors. This extension preserves many of the desirable properties of the original SDM: auto-associativity, content addressability, distributed storage, and robustness over noisy inputs. In addition, it improves the representation capabilities of the memory and is more robust over normalization. It can also be extended to support forgetting and reliable sequence storage. We performed several simulations that test the noise robustness property and capacity of the memory. Theoretical analyses of the memory's fidelity and capacity are also presented.
authors.affiliation: Computer Science Department & Institute for Intelligent Systems, The University of Memphis, 365 Innovation Dr., Memphis, TN 38152, USA. jsnaider@memphis.edu
authors.forename: Javier
authors.initials: J
authors.lastname: Snaider
authors.forename: Stan
authors.initials: S
authors.lastname: Franklin
authors.forename: Steve
authors.initials: S
authors.lastname: Strain
authors.forename: E Olusegun
authors.initials: EO
authors.lastname: George
mesh_terms: D003198:Computer Simulation; D008568:Memory; D008962:Models, Theoretical; D016571:Neural Networks, Computer; D009622:Noise; D013223:Statistics as Topic / Q000379:methods
keywords: Auto-associative memory; High dimensional space; Sparse distributed memory