Associative memories for chemical sensing

被引：0
|
作者：
Reznik, AM
Shirshov, YM
Snopak, BA
Noicki, DW
Dekhtyarenko, AK
Kruglenko, IV
机构：
来源：
ICONIP'02: PROCEEDINGS OF THE 9TH INTERNATIONAL CONFERENCE ON NEURAL INFORMATION PROCESSING: COMPUTATIONAL INTELLIGENCE FOR THE E-AGE | 2002年
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：
We consider application of neural associative memories to chemical image recognition. Chemical image recognition is identification of substance using chemical sensors' data. The primary advantage of associative memories as compared with feed-forward neural networks is highspeed learning. We have made experiments on odour recognition using hetero-associative and modular auto-associative memories. We have also tested backpropagation NNs with one hidden layer. Associative memories displayed recognition quality not worse than backgropagation. networks.
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页码：2630 / 2634
页数：5
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