Storage capacity of kernel associative memories

被引：0

作者：

Caputo, B ^{[1
]}

Niemann, H ^{[1
]}

机构：

[1] Univ Erlangen Nurnberg, Dept Comp Sci, Chair Pattern Recognit, D-91058 Erlangen, Germany

来源：

ARTIFICIAL NEURAL NETWORKS - ICANN 2002 | 2002年 / 2415卷

关键词：

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This contribution discusses the thermodynamic phases and storage capacity of an extension of the Hopfield-Little model of associative memory via kernel functions. The analysis is presented for the case of polynomial and Gaussian kernels in a replica symmetry ansatz. As a general result we found for both kernels that the storage capacity increases considerably compaxed to the Hopfield-Little model.

引用

页码：51 / 56

页数：6

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