MEAN FIELD MONTE CARLO STUDIES OF ASSOCIATIVE MEMORY - Understanding the Dynamics of a Many-pattern Model

Ish Dhand, Manoranjan P. Singh

2011

Abstract

Dynamics of a Hebbian model of associative memory is studied using Mean field Monte-Carlo method. Under the assumption of infinite system, we have derived single-spin equations, using the generating functional method from statistical mechanics, for the purpose of simulations. This approach circumvents the strong finite-size effects of the usual calculations on this system. We have tried to understand the retrieval of a stored pattern in presence of another condensed pattern undergoing reinforcement, positive or negative. We find that the retrieval is faster and the retrieval quality is better for the case of positive reinforcement.

References

  1. Eissfeller, H. and Opper, M. (1992). New method for studying the dynamics of disordered spin systems without finite-size effects. Physical Review Letters, 68(13):2094.
  2. Eissfeller, H. and Opper, M. (1994). Mean-field monte carlo approach to the Sherrington-Kirkpatrick model with asymmetric couplings. Physical Review E, 50(2):709.
  3. Hanggi, P. (1978). Correlation functions and masterequations of generalized (non-Markovian) langevin equations. Zeitschrift fr Physik B Condensed Matter and Quanta, 31(4):407-416.
  4. Hebb, D. O. (2002). The organization of behavior: a neuropsychological theory. L. Erlbaum Associates.
  5. Henkel, R. D. and Opper, M. (1991). Parallel dynamics of the neural network with the pseudoinverse coupling matrix. Journal of Physics A: Mathematical and General, 24(9):2201-2218.
  6. Hopfield, J. J. (1982). Neural networks and physical systems with emergent collective computational abilities. Proceedings of the National Academy of Sciences, 79(8):2554 -2558.
  7. Kohring, G. and Schreckenberg, M. (1991). Numerical studies of the spin-flip dynamics in the SK-model. Journal de Physique I, 1(8):5.
  8. Sherrington, D. and Kirkpatrick, S. (1975). Solvable model of a Spin-Glass. Physical Review Letters, 35(26):1792.
  9. Singh, M. P. and Dasgupta, C. (2003). Mean-field monte carlo approach to the dynamics of a one pattern model of associative memory. cond-mat/0303061.
  10. Toulouse, G., Dehaene, S., and Changeux, J. P. (1986). Spin glass model of learning by selection. Proceedings of the National Academy of Sciences, 83(6):1695 -1698.
Download


Paper Citation


in Harvard Style

Dhand I. and P. Singh M. (2011). MEAN FIELD MONTE CARLO STUDIES OF ASSOCIATIVE MEMORY - Understanding the Dynamics of a Many-pattern Model . In Proceedings of the International Conference on Neural Computation Theory and Applications - Volume 1: NCTA, (IJCCI 2011) ISBN 978-989-8425-84-3, pages 395-400. DOI: 10.5220/0003683803950400


in Bibtex Style

@conference{ncta11,
author={Ish Dhand and Manoranjan P. Singh},
title={MEAN FIELD MONTE CARLO STUDIES OF ASSOCIATIVE MEMORY - Understanding the Dynamics of a Many-pattern Model},
booktitle={Proceedings of the International Conference on Neural Computation Theory and Applications - Volume 1: NCTA, (IJCCI 2011)},
year={2011},
pages={395-400},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003683803950400},
isbn={978-989-8425-84-3},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Neural Computation Theory and Applications - Volume 1: NCTA, (IJCCI 2011)
TI - MEAN FIELD MONTE CARLO STUDIES OF ASSOCIATIVE MEMORY - Understanding the Dynamics of a Many-pattern Model
SN - 978-989-8425-84-3
AU - Dhand I.
AU - P. Singh M.
PY - 2011
SP - 395
EP - 400
DO - 10.5220/0003683803950400