کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
743575 894363 2008 6 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Study on the odor classification in dynamical concentration robust against humidity and temperature changes
موضوعات مرتبط
مهندسی و علوم پایه شیمی شیمی آنالیزی یا شیمی تجزیه
پیش نمایش صفحه اول مقاله
Study on the odor classification in dynamical concentration robust against humidity and temperature changes
چکیده انگلیسی

In this paper, we propose a method for enhancing the robustness of odor classification against the changes of humidity and temperature when the odor concentration is changing dynamically. We used amplitudes of frequency components of sensor responses at particular frequencies, instead of response magnitudes, to compose a pattern vector for the odor classification. The frequency analysis was done by using a short-time Fourier transform (STFT) and the selection of the frequency components by using a stepwise discriminant analysis. Besides the use of the STFT, we also improved the classification performance by including the humidity and temperature values to the pattern vector. Using a learning vector quantization (LVQ) neural network and training the network with wide-range data, we successfully achieved high robustness against various environment conditions even if the odor concentration was changing dynamically and irregularly under various humidity and temperature.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Sensors and Actuators B: Chemical - Volume 134, Issue 1, 28 August 2008, Pages 252–257
نویسندگان
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