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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Gardnert, J.W. Bartlett, P.N. |
| Copyright Year | 1995 |
| Description | Author affiliation: University of Warwick (Gardnert, J.W.) |
| Abstract | The performance of any electronic nose is ultimately determined by the properties of its constituent parts (e.g. the sensors, signal processing, and pattern recognition engine). Electronic noses currently exploit different sensor materials technologies (e.g. semiconducting oxide, conducting polymer, phthalocyanines and lipid coatings) as well as different pattern recognition paradigms (e.g. canonical analysis, back-propagation and learning vector quantification). This has led to the need to compare objectively the performance of an increasing number of both research and commercial electronic noses. This paper addresses this problem and suggest the need for odour standards to define both the range and resolving power of an electronic nose. We present a generic model from which we can define such parameters. The model can also be employed as diagnostic tool which can predict not only the relative performance of different electronic noses but also the effect of, for example, changing the number or type of odour sensor, temperature fluctuations or ageing. We believe that the definition of standard odour samples and standard performance parameters would be of great benefit in this field. |
| Starting Page | 671 |
| Ending Page | 674 |
| File Size | 413082 |
| Page Count | 4 |
| File Format | |
| ISBN | 9163034735 |
| DOI | 10.1109/SENSOR.1995.717320 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 1995-06-25 |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Electronic noses Sensor arrays Noise level Signal resolution Array signal processing Chemical sensors Engines Thermal sensors Circuit noise Extraterrestrial measurements |
| Content Type | Text |
| Resource Type | Article |
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