On a Model of Associative Memory with Huge Storage Capacity-Reference-Cited by-同舟云学术

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On a Model of Associative Memory with Huge Storage Capacity

Published:2017-05-19 Issue:2 Volume:168 Page:288-299
ISSN:0022-4715
Container-title:Journal of Statistical Physics
language:en
Short-container-title:J Stat Phys

Author:

Demircigil Mete,Heusel Judith,Löwe Matthias,Upgang Sven,Vermet Franck

Publisher

Springer Science and Business Media LLC

Subject

Mathematical Physics,Statistical and Nonlinear Physics

Link

http://link.springer.com/article/10.1007/s10955-017-1806-y/fulltext.html

Reference15 articles.

1. Amit, D.J., Gutfreund, H., Sompolinsky, H.: Spin-glass models of neural networks. Phys. Rev. A. 32(2), 1007–1018 (1985a). doi: 10.1103/PhysRevA.32.1007

2. Amit, D.J., Gutfreund, H., Sompolinsky, H.: Storing infinite numbers of patterns in a spin-glass model of neural networks. Phys. Rev. Lett. 55, 1530–1533 (1985b). doi: 10.1103/PhysRevLett.55.1530

3. Bovier, A.: Sharp upper bounds on perfect retrieval in the Hopfield model. J. Appl. Probab. 36(3), 941–950 (1999)

4. Bovier, A., Niederhauser, B.: The spin-glass phase-transition in the Hopfield model with $$p$$ p -spin interactions. Adv. Theor. Math. Phys. 5(6), 1001–1046 (2001). doi: 10.4310/ATMP.2001.v5.n6.a2

5. Dembo, A., Zeitouni, O.: Large deviations techniques and applications. Stochastic Modelling and Applied Probability, vol. 38, p. 396. Springer, Berlin (2010) Corrected reprint of the second (1998) edition. ISBN 978-3-642-03310-0. doi: 10.1007/978-3-642-03311-7

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