Title :
Asymmetric bidirectional associative memories
Author :
Xu, Zong-Ben ; Leung, Yee ; He, Xiang-Wei
Author_Institution :
Inst. for Comput. & Appl. Math., Xi´´an Jiaotong Univ., China
fDate :
10/1/1994 12:00:00 AM
Abstract :
Bidirectional associative memory (BAM) is a potentially promising model for heteroassociative memories. However, its applications are severely restricted to networks with logical symmetry of interconnections and pattern orthogonality or small pattern size. Although the restrictions on pattern orthogonality and pattern size can be relaxed to a certain extent, all previous efforts are at the cost of increase in connection complexity. In this paper, a new modification of the BAM is made and a new model named asymmetric bidirectional associative memory (ABAM) is proposed. This model not only can cater for the logical asymmetry of interconnections but also is capable of accommodating a larger number of non-orthogonal patterns. Furthermore, all these properties of the ABAM are achieved without increasing the connection complexity of the network. Theoretical analysis and simulation results all demonstrate that the ABAM indeed outperforms the BAM and its existing variants in all aspects of storage capacity, error-correcting capability and convergence
Keywords :
content-addressable storage; neural nets; asymmetric bidirectional associative memories; connection complexity; convergence; error-correcting capability; heteroassociative memories; logical asymmetry; pattern orthogonality; storage capacity; Analytical models; Associative memory; Convergence; Costs; Helium; Humans; Machine intelligence; Magnesium compounds; Neural networks; Neurons;
Journal_Title :
Systems, Man and Cybernetics, IEEE Transactions on