We study numerically the memory that forgets, introduced in 1986 by Parisi by bounding the synaptic strength, with a mechanism that avoids confusion; allows remembering the pattern learned more recently; and has a physiologically very well-defined meaning. We analyze a number of features of this learning for a finite number of neurons and finite number of patterns. We discuss how the system behaves in the large but finite N limit. We analyze the basin of attraction of the patterns that have been learned, and we show that it is exponentially small in the age of the pattern.

Forgetting memories and their attractiveness / Marinari, E.. - In: NEURAL COMPUTATION. - ISSN 0899-7667. - 31:3(2019), pp. 503-516. [10.1162/neco_a_01162]

Forgetting memories and their attractiveness

Marinari E.
2019

Abstract

We study numerically the memory that forgets, introduced in 1986 by Parisi by bounding the synaptic strength, with a mechanism that avoids confusion; allows remembering the pattern learned more recently; and has a physiologically very well-defined meaning. We analyze a number of features of this learning for a finite number of neurons and finite number of patterns. We discuss how the system behaves in the large but finite N limit. We analyze the basin of attraction of the patterns that have been learned, and we show that it is exponentially small in the age of the pattern.
2019
memory; spin glass; Hopfield model
01 Pubblicazione su rivista::01f Lettera, Nota
Forgetting memories and their attractiveness / Marinari, E.. - In: NEURAL COMPUTATION. - ISSN 0899-7667. - 31:3(2019), pp. 503-516. [10.1162/neco_a_01162]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1339797
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