Theory of the dynamics of the Hopfield model of associative memory
- Prabodh Shukla
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We present an analysis of the parallel dynamics of the Hopfield model of the associative memory of a neural network without recourse to the replica formalism. A probabilistic method based on the signal-to-noise ratio is employed to obtain a simple recursion relation for the zero temperature as well as the finite temperature dynamics of the network. The fixed points of the recursion relation and their basins of attraction are found to be in fairly satisfactory agreement with the numerical simulations of the model. We also present some new numerical results which support our recursion relation and throw light on the nature of the ensemble of the network states which are optimized with respect to single spin flips.
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- Theory of the dynamics of the Hopfield model of associative memory
Journal of Statistical Physics
Volume 71, Issue 3-4 , pp 705-717
- Cover Date
- Print ISSN
- Online ISSN
- Kluwer Academic Publishers-Plenum Publishers
- Additional Links
- Hopfield model
- parallel dynamics
- probabilistic method
- signal-to-noise ratio
- Industry Sectors
- Prabodh Shukla (1)
- Author Affiliations
- 1. Department of Physics, North Eastern Hill University, 793003, Shillong, India