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.
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页码：51 / 56
页数：6
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