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Binary associative memories with complemented operations
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Title: Binary associative memories with complemented operations

Creator:

Gamino-Carranza, Arturo

Date:

2023

Resource Type:

artykuł

Contributor:

Kitowski, Zygmunt - ed. ; Piskur, Paweł - ed. ; Hożyń , Stanisław - ed.

Subtitle:

.

Group publication title:

AMCS, volume 33 (2023)

Abstract:

Associative memories based on lattice algebra are of great interest in pattern recognition applications due to their excellent storage and recall properties. In this paper, a class of binary associative memory derived from lattice memories is presented, which is based on the definition of new complemented binary operations and threshold unary operations. The new learning method generates memories M and W; the former is robust to additive noise and the latter is robust to subtractive noise. In the recall step, the memories converge in a single step and use the same operation as the learning method. The storage capacity is unlimited, and in autoassociative mode there is perfect recall for the training set. Simulation results suggest that the proposed memories have better performance compared to other models.

Publisher:

Zielona Góra: Uniwersytet Zielonogórski

Resource Identifier:

oai:zbc.uz.zgora.pl:86586

DOI:

10.34768/amcs-2023-0019

Pages:

249-265

Source:

AMCS, volume 33, number 2 (2023) ; click here to follow the link

Language:

eng

License CC BY 4.0:

click here to follow the link

Rights:

Biblioteka Uniwersytetu Zielonogórskiego

Subject and keywords:

associative memory neutral networks morphological associative memory perfect recall

Object collections:

Last modified:

Jul 25, 2025

In our library since:

Jul 25, 2025

Number of object content hits:

11

All available object's versions:

https://zbc.uz.zgora.pl/repozytorium/publication/101587

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Edition name Date
Binary associative memories with complemented operations Jul 25, 2025

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