Yq. Wu et Sn. Batalama, Improved one-shot learning for feedforward associative memories with application to composite pattern association, IEEE SYST B, 31(1), 2001, pp. 119-125
Citations number
23
Categorie Soggetti
AI Robotics and Automatic Control
Journal title
IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS
The local identical index (LII) associative memory (ARI) proposed by the au
thors ina previous paper is a one-shot feedforward structure designed to ex
hibit no spurious attractors. In this paper we relax the latter design cons
traint in exchange for enlarged basins of attraction and we develop a famil
y of modified LII AM networks that exhibit improved performance, particular
ly in memorizing highly correlated patterns. The new algorithm meets the re
quirement of no spurious attractors only in a local sense. Finally, we show
that the modified LII family of networks can accommodate composite pattern
s of any size by storing (memorizing) only the basic (prime) prototype patt
erns, The latter property translates to low learning complexity and a simpl
e network structure with significant memory savings. Simulation studies and
comparisons illustrate and support the theoretical developments.