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Signal Processing Techniques Based on Adaptive Radial Basis Function Networks for Chemical Sensor Arrays
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 Title & Authors
Signal Processing Techniques Based on Adaptive Radial Basis Function Networks for Chemical Sensor Arrays
Byun, Hyung-Gi;
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 Abstract
The use of a chemical sensor array can help discriminate between chemicals when comparing one sample with another. The ability to classify pattern characteristics from relatively small pieces of information has led to growing interest in methods of sensor recognition. A variety of pattern recognition algorithms, including the adaptive radial basis function network (RBFN), may be applicable to gas and/ or odor classification. In this paper, we provide a broad review of approaches for various types of gas and/or odor identification techniques based on RBFN and drift compensation techniques caused by sensor poisoning and aging.
 Keywords
Chemical sensor array;Pattern recognition;Gas and/or odor classification;Radial basis function networks;Drift compensation;
 Language
English
 Cited by
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