Digital image processing (2nd ed.)
Digital image processing (2nd ed.)
Neurocomputing: foundations of research
Stability and optimization analyses of the generalized brain-state-in-a-box neural network model
Journal of Mathematical Psychology
DCBAM: a discrete chainable bidirectional associative memory
Pattern Recognition Letters
Memory and learning of sequential patterns by nonmonotone neural networks
Neural Networks - 1996 Special issue: four major hypotheses in neuroscience
A discrete sequential bidirectional associative memory for multistep pattern recognition
Pattern Recognition Letters
Fundamentals of Artificial Neural Networks
Fundamentals of Artificial Neural Networks
Adaptive learning of fuzzy BSB and GBSB neural models
Cybernetics and Systems Analysis
Brief Associative memory design using overlapping decompositions
Automatica (Journal of IFAC)
Design of GBSB neural associative memories using semidefinite programming
IEEE Transactions on Neural Networks
Heteroassociations of spatio-temporal sequences with the bidirectional associative memory
IEEE Transactions on Neural Networks
Pattern sequence recognition using a time-varying Hopfield network
IEEE Transactions on Neural Networks
Neural associative memory storing gray-coded gray-scale images
IEEE Transactions on Neural Networks
Associative Memory Design Using Support Vector Machines
IEEE Transactions on Neural Networks
Improvements of Complex-Valued Hopfield Associative Memory by Using Generalized Projection Rules
IEEE Transactions on Neural Networks
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In this paper, a generalized Brain-State-in-a-Box (gBSB)-based hybrid neural network is proposed for storing and retrieving pattern sequences. The hybrid network consists of autoassociative and heteroassociative parts. Then, a large-scale image storage and retrieval neural system is constructed using the gBSB-based hybrid neural network and the pattern decomposition concept. The notion of the deadbeat stability is employed to describe the stability property of the vertices of the hypercube to which the trajectories of the gBSB neural system are constrained. Extensive simulations of large scale pattern and image storing and retrieval are presented to illustrate the results obtained.