Abstract
Analysis of an Insect's Olfactory Receptor Neuron Response by NMF Method for Odor Approximation
Highlights
Some odorants can evoke similar impressions, i.e., the same or a similar sensory impression can be obtained by blending a small number of odor constituents
We revealed that the accuracy was improved by the nonnegative matrix factorization (NMF) method,(4,5) based on the distance measure such as the Itakura-Sato (IS) divergence.[5]Because of the reproduction of small mass spectrum peaks despite important contributions, we have already reported that the IS divergence improved the accuracy in approximation of blended essential oils by mixing odor components based on mass spectrometry (MS) data space.[6]
A small set of odor component is suitable for approximating various odors by using olfactory display because of its hardware cost
Summary
Some odorants can evoke similar impressions, i.e., the same or a similar sensory impression can be obtained by blending a small number of odor constituents. An odor representation using all its constituents might be superfluous From another point of view, their olfactory thresholds are sometimes different from the limits of detection of analytical equipment or artificial sensors such as mass spectrometry. It is necessary to compare sensory space with the artificial sensors’ one and to take an appropriate distance measure to fit it so that odor approximation can be established. We revealed that the accuracy was improved by the nonnegative matrix factorization (NMF) method,(4,5) based on the distance measure such as the Itakura-Sato (IS) divergence.[5]Because of the reproduction of small mass spectrum peaks despite important contributions, we have already reported that the IS divergence improved the accuracy in approximation of blended essential oils by mixing odor components based on MS data space.[6]. We analyzed the biological sensing space on the basis of response data reported by Hallem and Carlson[7] using the NMF method
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