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Nonlinear inverse dynamic models of gas sensing systems based on chemical sensor arrays for quantitative measurements

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Gas sensing systems based on low-cost chemical sensor arrays are gaining interest for the analysis of multicomponent gas mixtures. These sensors show different problems, e.g., nonlinearities and slow time-response, which can be partially solved by digital signal processing. Our approach is based on building a nonlinear inverse dynamic system. Results for different identification techniques, including artificial neural networks and Wiener series, are compared in terms of measurement accuracy.

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IEEE Transactions on Instrumentation and Measurement, 1998, vol. 47, núm. 3, p. 644-651.

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Articles publicats en revistes (Enginyeria Electrònica i Biomèdica)

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Nonlinear inverse dynamic models of gas sensing systems based on chemical sensor arrays for quantitative measurements