An entropic associative memory

Abstract Natural memories are associative, declarative and distributed, and memory retrieval is a constructive operation. In addition, cues of objects that are not contained in the memory are rejected directly. Symbolic computing memories resemble natural memories in their declarative character, and...

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Autores principales:	Luis A. Pineda, Gibrán Fuentes, Rafael Morales
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/23c7c74af93a45528faef4a2a9da2700
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spelling	oai:doaj.org-article:23c7c74af93a45528faef4a2a9da27002021-12-02T11:45:01ZAn entropic associative memory10.1038/s41598-021-86270-72045-2322https://doaj.org/article/23c7c74af93a45528faef4a2a9da27002021-03-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-86270-7https://doaj.org/toc/2045-2322Abstract Natural memories are associative, declarative and distributed, and memory retrieval is a constructive operation. In addition, cues of objects that are not contained in the memory are rejected directly. Symbolic computing memories resemble natural memories in their declarative character, and information can be stored and recovered explicitly; however, they are reproductive rather than constructive, and lack the associative and distributed properties. Sub-symbolic memories developed within the connectionist or artificial neural networks paradigm are associative and distributed, but lack the declarative property, the capability of rejecting objects that are not included in the memory, and memory retrieval is also reproductive. In this paper we present a memory model that sustains the five properties of natural memories. We use Relational-Indeterminate Computing to model associative memory registers that hold distributed representations of individual objects. This mode of computing has an intrinsic computing entropy which measures the indeterminacy of representations. This parameter determines the operational characteristics of the memory. Associative registers are embedded in an architecture that maps concrete images expressed in modality specific buffers into abstract representations and vice versa. The framework has been used to model a visual memory holding the representations of hand-written digits. The system has been tested with a set of memory recognition and retrieval experiments with complete and severely occluded images. The results show that there is a range of entropy values, not too low and not too high, in which associative memory registers have a satisfactory performance. The experiments were implemented in a simulation using a standard computer with a GPU, but a parallel architecture may be built where the memory operations would take a very reduced number of computing steps.Luis A. PinedaGibrán FuentesRafael MoralesNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-15 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Luis A. Pineda Gibrán Fuentes Rafael Morales An entropic associative memory
description	Abstract Natural memories are associative, declarative and distributed, and memory retrieval is a constructive operation. In addition, cues of objects that are not contained in the memory are rejected directly. Symbolic computing memories resemble natural memories in their declarative character, and information can be stored and recovered explicitly; however, they are reproductive rather than constructive, and lack the associative and distributed properties. Sub-symbolic memories developed within the connectionist or artificial neural networks paradigm are associative and distributed, but lack the declarative property, the capability of rejecting objects that are not included in the memory, and memory retrieval is also reproductive. In this paper we present a memory model that sustains the five properties of natural memories. We use Relational-Indeterminate Computing to model associative memory registers that hold distributed representations of individual objects. This mode of computing has an intrinsic computing entropy which measures the indeterminacy of representations. This parameter determines the operational characteristics of the memory. Associative registers are embedded in an architecture that maps concrete images expressed in modality specific buffers into abstract representations and vice versa. The framework has been used to model a visual memory holding the representations of hand-written digits. The system has been tested with a set of memory recognition and retrieval experiments with complete and severely occluded images. The results show that there is a range of entropy values, not too low and not too high, in which associative memory registers have a satisfactory performance. The experiments were implemented in a simulation using a standard computer with a GPU, but a parallel architecture may be built where the memory operations would take a very reduced number of computing steps.
format	article
author	Luis A. Pineda Gibrán Fuentes Rafael Morales
author_facet	Luis A. Pineda Gibrán Fuentes Rafael Morales
author_sort	Luis A. Pineda
title	An entropic associative memory
title_short	An entropic associative memory
title_full	An entropic associative memory
title_fullStr	An entropic associative memory
title_full_unstemmed	An entropic associative memory
title_sort	entropic associative memory
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/23c7c74af93a45528faef4a2a9da2700
work_keys_str_mv	AT luisapineda anentropicassociativememory AT gibranfuentes anentropicassociativememory AT rafaelmorales anentropicassociativememory AT luisapineda entropicassociativememory AT gibranfuentes entropicassociativememory AT rafaelmorales entropicassociativememory
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An entropic associative memory

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