title: Reduced order multiport parallel and multidirectional neural associative memories.
abstract: This paper proposes multiport parallel and multidirectional intraconnected associative memories of outer product type with reduced interconnections. Some new reduced order memory architectures such as k-directional and k-port parallel memories are suggested. These architectures are, also, very suitable for implementation of spatio-temporal sequences and multiassociative memories. It is shown that in the proposed memory architectures, a substational reduction in interconnections is achieved if the actual length of original N-bit long vectors is subdivided into k sublengths. Using these sublengths, submemory matrices, T ( s ) or W ( s ), are computed, which are then intraconnected to form k-port parallel or k-directional memories. The subdivisions of N-bit long vectors into k sublengths save ((k-1) x 100) / k % of interconnections. It is shown, by means of an example, that more than 80% reduction in interconnections is achieved. Minimum limit in bits on k as well as maximum limit on subdivisions in k is determined. The topologies of reduced interconnectivity developed in this paper are symmetric in structure and can be used to scale up to larger systems. The underlying principal of construction, storage and retrieval processes of such associative memories has been analyzed. The effect of complexity of different levels of reduced interconnectivity on the quality of retrieval, signal to noise ratio, and storage capacity has been investigated. The model possesses analogies to biological neural structures and digital parallel port memories commonly used in parallel and multiprocessing systems.
authors.affiliation: School of Science and Technology, University of Management and Technology, Lahore, Pakistan. drabhatti@gmail.com
authors.forename: Abdul Aziz
authors.initials: AA
authors.lastname: Bhatti
mesh_terms: D006801:Humans; D008433:Mathematics; D008568:Memory; D009415:Nerve Net; D016571:Neural Networks, Computer