Abstract
Odor classification has been forcused due to one of five senses of human being. If we could establish the odor classification technology, we would expect various new technology since human being requires five sences to acheive higher quality information processing and sophistcated decision making. For example, we could expect the odor classification and odor synthesis, which enable us to achieve odor communication technology. Furthermore, the odor classification would be applicable to keep the society safe by detecting the dangerous odors and to make our life more satisfactory by using additional odor information. In this paper we develop an electronic nose using a neural network. The neural network is a multi-layered neural network based on the gradient method. After classifying the various odors, we consider the classification in case that mixed odors are measured. To improve the classification accuracy we adopt a genetic algorithm to find a reduction factor to separate two mixed odors.
Highlights
The 2004 Nobel Prize in Medicine and Physiology was awarded to Richard Axel and Linda B
By using neural networks we have developed for odor classification of various sources for fire such as household burning materials in [21]
In this paper we focuses on mixed odors classification
Summary
The 2004 Nobel Prize in Medicine and Physiology was awarded to Richard Axel and Linda B. Odor is one of five senses for human and it makes our life pleasant or unpleasant based on odor environment. We will discuss a new E-nose system to separate two kinds of odors from mixed odors by using a layered neural network. Milke [20] is the first person who used two kinds of metal-oxide semiconductor gas sensor (MOGS) to classify several sources for fire. His results were only 85% of correct classification based on a conventional statistical pattern recognition. We use the trained neural network to classify the mixed odors into original odor using the method of [22]
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