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Abstract:

A neural network model of associative memory is presented which unifies the two historically more relevant enhancements to the basic Little-Hopfield discrete model: the graded response units approach and the stochastic, Glauber-inspired model with a random field representing thermal fluctuations. This is done by casting the retrieval process of the model with graded response neurons, into the framework of a diffusive process governed by the Fokker-Plank equation, which leads to a Langevin system describing the process at a microscopic level, while the time evolution of the probability density function is governed by a multivariate Fokker Planck equation operating over the space of all possible activation patterns. The present unified approach has two notable features: (i) greater biological plausibility and (ii) ability to escape local minima of energy (associated with spurious memories), which makes it a potential tool for those complex optimization problems for which the previous models failed.

Registro:

Documento: Artículo
Título:Biologically plausible associative memory: Continuous unit response + stochastic dynamics
Autor:Segura Meccia, E.C.; Perazzo, R.P.J.
Filiación:Sch. of Computing, Info. Syst. Math., South Bank University, 103 Borough Road, London SE1 0AA, United Kingdom
Departamento de Fisica, Universidad de Buenos Aires, Ciudad Universitaria, (1428) Buenos Aires, Argentina
Palabras clave:Associative memory; Fokker-Planck equation; Graded response; Hopfield model; Stochastic dynamics; Asymptotic stability; Computer simulation; Neural networks; Numerical methods; Probability density function; Probability distributions; Random processes; Biologically plausible associative memory; Continuous unit response; Fokker-Planck equation; Graded response; Hopfield model; Stochastic dynamics; Associative storage
Año:2002
Volumen:16
Número:3
Página de inicio:243
Página de fin:257
DOI: http://dx.doi.org/10.1023/A:1021742025239
Título revista:Neural Processing Letters
Título revista abreviado:Neural Process Letters
ISSN:13704621
CODEN:NPLEF
Registro:https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_13704621_v16_n3_p243_SeguraMeccia

Referencias:

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  • Segura, E.C., Perazzo, R.P.J., Associative memories in infinite dimensional spaces (2000) Neural Processing Letters, 12, pp. 129-144

Citas:

---------- APA ----------
Segura Meccia, E.C. & Perazzo, R.P.J. (2002) . Biologically plausible associative memory: Continuous unit response + stochastic dynamics. Neural Processing Letters, 16(3), 243-257.
http://dx.doi.org/10.1023/A:1021742025239
---------- CHICAGO ----------
Segura Meccia, E.C., Perazzo, R.P.J. "Biologically plausible associative memory: Continuous unit response + stochastic dynamics" . Neural Processing Letters 16, no. 3 (2002) : 243-257.
http://dx.doi.org/10.1023/A:1021742025239
---------- MLA ----------
Segura Meccia, E.C., Perazzo, R.P.J. "Biologically plausible associative memory: Continuous unit response + stochastic dynamics" . Neural Processing Letters, vol. 16, no. 3, 2002, pp. 243-257.
http://dx.doi.org/10.1023/A:1021742025239
---------- VANCOUVER ----------
Segura Meccia, E.C., Perazzo, R.P.J. Biologically plausible associative memory: Continuous unit response + stochastic dynamics. Neural Process Letters. 2002;16(3):243-257.
http://dx.doi.org/10.1023/A:1021742025239