Molecular Approach to Hopfield Neural Network

被引:15
|
作者
Laskowski, Lukasz [1 ,2 ]
Laskowska, Magdalena [2 ]
Jelonkiewicz, Jerzy [1 ]
Boullanger, Arnaud [3 ]
机构
[1] Czestochowa Tech Univ, Dept Comp Engn, PL-42200 Czestochowa, Poland
[2] Czestochowa Tech Univ, Inst Phys, PL-42200 Czestochowa, Poland
[3] Univ Montpellier 2, Chim Mol & Org Solide, Inst Charles Gerhardt, UMR CC 5253 1701, F-34095 Montpellier 5, France
关键词
Hopfield neural network; Artificial neuron; Spin-glass; Molecular magnet; MESOPOROUS SILICA; FUZZY;
D O I
10.1007/978-3-319-19324-3_7
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The present article puts forward a completely new technology development, a spin glass-like molecular implementation of the Hopfield neural structure. This novel approach uses magnetic molecules homogenously distributed in mesoporous silica matrix, which forms a base for a converting unit, an equivalent of a neuron in the Hopfield network. Converting units interact with each other via a fully controlled magnetic fields, which corresponds to weighted interconnections in the Hopfield network. This novel technology enables building fast, high-density content addressable associative memories. In particular, it is envisaged that in the future this approach can be scaled up to mimic memory with human-like characteristics. This would be a breakthrough in artificial brain implementations and usher in a new type of highly intelligent beings. Another application relates to systems designed for multi-objective optimization (multiple criteria decision making).
引用
收藏
页码:72 / 78
页数:7
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