Capacity analysis for a two-level decoupled Hamming network for associative memory under a noisy environment

Authors:
Liang Chen;Naoyuki Tokuda;Akira Nagai
Affiliations:
Computer Science Department, University of Northern British Columbia, BC, Canada V2N 4Z9;SunFlare Research and Development Center, Shinjuku Hirose Bldg, Yotsuya 4-7, Shinjuku-ku, Tokyo 160-0004, Japan;Advanced Media Network Center, Utsunomiya University, Utsunomiya, Tochigi 321-8585, Japan
Venue:
Neural Networks
Year:
2007

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Abstract

Our detailed analysis has established that in addition to the advantages of computationally efficiency and easy hardware implementation, the two-level decoupled Hamming network possesses a substantially higher capacity over the single-level Hamming associative memory since the effect caused by Ikeda et al.'s uniform random noise [Ikeda, N., Watta, P., Artiklar, M., & Hassoun, M. (2001). A two-level Hamming network for high performance associative memory. Neural Networks, 14(9), 1189-1200] is much smaller than that caused by the practically more prevalent concentrated noise. We therefore conclude that the two-level decoupled Hamming network with middle-sized windows should be an elegant associative memory model in all the senses of efficiency, hardware implementation and capacity.