Title :
Synthesis of Brain-State-in-a-Box (BSB) based associative memories
Author :
Lillo, Walter E. ; Miller, David C. ; Hui, Stefen ; Zak, Stanislaw H.
Author_Institution :
Aerosp. Corp., Los Angeles, CA, USA
fDate :
9/1/1994 12:00:00 AM
Abstract :
Presents a novel synthesis procedure to realize an associative memory using the Generalized-Brain-State-in-a-Box (GBSB) neural model. The implementation yields an interconnection structure that guarantees that the desired memory patterns are stored as asymptotically stable equilibrium points and that possesses very few spurious states. Furthermore, the interconnection structure is in general non-symmetric. Simulation examples are given to illustrate the effectiveness of the proposed synthesis method. The results obtained for the GBSB model are successfully applied to other neural network models
Keywords :
content-addressable storage; neural nets; Generalized-Brain-State-in-a-Box neural model; associative memories; asymptotically stable equilibrium points; interconnection structure; memory patterns; Aerospace engineering; Artificial neural networks; Associative memory; Biological neural networks; Control systems; Hamming distance; Intelligent networks; Network synthesis; Neural networks; Prototypes;
Journal_Title :
Neural Networks, IEEE Transactions on
