We present a neural algorithm for the rapid online learning and identification of odourant
samples under noise, based on the architecture of the mammalian olfactory bulb and …

Metal oxide (MOX) gas sensors arrays are a predominant technological choice to perform
fundamental tasks of chemical detection. Yet, their use has been mainly limited to relatively …

We investigate optimal experiment selection to train a classifier on gas sensor arrays to get
the maximal possible performance in a limited number of experiments. In gas sensing, while …

In the last few years, the interest in the development of new pervasive or mobile
implementations of air quality multisensor devices has significantly grown. New application …

Accurate and selective detection of target gas/volatile organic compounds (VOCs) is of
utmost importance. The chemiresistive gas sensors have been a desirable candidate due to …

Abstract Development of new signal processing approaches is essential for improvement of
the reliability of metal oxide gas sensor performance in real atmospheric conditions …

Although sensor technologies have allowed us to outperform the human senses of sight,
hearing, and touch, the development of artificial noses is significantly behind their biological …

This paper proposes a framework for binary classification of the time series with cyclic
characteristics. The framework presents an iterative algorithm for learning the cyclic …

The gas sensor array has long been a major tool for measuring gas due to its high
sensitivity, quick response, and low power consumption. This goal, however, faces a difficult …

A porous silicon thin film photonic crystal (rugate) sample with both a radial gradient in the
rugate reflectance band wavelength and two spatially separated pore-wall surface …