A Boolean Hebb rule for binary associative memory design

IEEE Transactions on Neural Networks

Volumn 15, Issue 1, 2004, Pages 195-202

  Müezzinoǧlu, Mehmet Kerem ^a   Güzeliş, Cüneyt ^b  

^a UNIVERSITY OF LOUISVILLE   (United States)

^b DOKUZ EYLUL UNIVERSITY   (Turkey)

Author keywords

Hebb rule; Maximal independent set; Neurodynamics and attractor networks

Indexed keywords

BOOLEAN FUNCTIONS; BOUNDARY CONDITIONS; GRAPH THEORY; KNOWLEDGE BASED SYSTEMS; MATRIX ALGEBRA; PARAMETER ESTIMATION; SET THEORY; THEOREM PROVING; VECTORS;

BINARY ASSOCIATIVE MEMORY; BOOLEAN HEBB RULE; DYNAMIC HOPFIELD NETWORK; MAXIMAL INDEPENDENT SET; NEURODYNAMICS AND ATTRACTOR NETWORKS;

NEURAL NETWORKS;

ARTICLE; ARTIFICIAL NEURAL NETWORK; MEMORY;

MEMORY; NEURAL NETWORKS (COMPUTER);

EID: 6044227989     PISSN: 10459227     EISSN: None     Source Type: Journal    
DOI: 10.1109/TNN.2003.820669     Document Type: Article

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