Glassy behavior in neural network models of associative memory
Data(s) |
15/11/2002
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Resumo |
Neural network models of associative memory exhibit a large number of spurious attractors of the network dynamics which are not correlated with any memory state. These spurious attractors, analogous to "glassy" local minima of the energy or free energy of a system of particles, degrade the performance of the network by trapping trajectories starting from states that are not close to one of the memory states. Different methods for reducing the adverse effects of spurious attractors are examined with emphasis on the role of synaptic asymmetry. (C) 2002 Elsevier Science B.V. All rights reserved. |
Formato |
application/pdf |
Identificador |
http://eprints.iisc.ernet.in/39222/1/Glassy_behavior_in_neural.pdf Dasgupta, Chandan (2002) Glassy behavior in neural network models of associative memory. In: Physica A: Statistical Mechanics and its Applications, 315 (1-2). pp. 137-149. |
Publicador |
Elsevier Science |
Relação |
http://dx.doi.org/10.1016/S0378-4371(02)01246-3 http://eprints.iisc.ernet.in/39222/ |
Palavras-Chave | #Physics |
Tipo |
Journal Article PeerReviewed |