Capacity analysis for a two-level decoupled Hamming network for associative memory under a noisy environment.
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.
Chen
Liang
L
Computer Science Department, University of Northern British Columbia, BC, Canada V2N 4Z9. lchen@ieee.org
Tokuda
Naoyuki
N
Nagai
Akira
A
D001245:Association Learning; D003198:Computer Simulation; D004777:Environment; D006801:Humans; D008568:Memory; D016571:Neural Networks, Computer; D009622:Noise