The Sparse Blume - Emery - Griffiths Model of Associative Memories

被引：0

作者：

Heusel, J. ^{[1
]}

Loewe, M. ^{[1
]}

机构：

[1] Univ Munster, Fachbereich Math & Informat, Einsteinstr 62, D-48149 Munster, Germany

来源：

MARKOV PROCESSES AND RELATED FIELDS | 2018年 / 24卷 / 05期

关键词：

Associative memory; storage capacity; sparse data; artificial intelligence; machine learning; exponential inequalities; negative association; STORAGE CAPACITY; NEURAL-NETWORKS; HOPFIELD MODEL; INFORMATION; RETRIEVAL; BOUNDS;

D O I：

暂无

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

We analyze the Blume -Emery- Griffiths (BEG) associative memory with sparse patterns and at zero temperature. We give bounds on its storage capacity provided that we want the stored patterns to be fixed points of the retrieval dynamics. We compare our results to that of other models of sparse neural networks and show that the BEG model has a superior performance compared to them.

引用

页码：779 / 810

页数：32

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