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Quantifying olfactory perception: mapping olfactory perception space by using multidimensional scaling and self-organizing maps

Mamlouk, Amir Madany and Chee-Ruiter, Christine and Hofmann, Ulrich G. and Bower, James M. (2003) Quantifying olfactory perception: mapping olfactory perception space by using multidimensional scaling and self-organizing maps. Neurocomputing, 52-54 . pp. 591-597. ISSN 0925-2312. doi:10.1016/s0925-2312(02)00805-6. https://resolver.caltech.edu/CaltechAUTHORS:20191223-134154849

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Abstract

In this paper we describe an effort to project an olfactory perception database onto the nearest high dimensional Euclidean space using multidimensional scaling. This yields an independent Euclidean interpretation of odor perception, whether this space is metric or not. Self-organizing maps were then applied to produce two-dimensional maps of the Euclidean approximation of olfactory perception space. These maps provide new knowledge about complexity and potentially the functionality of the sense of smell from the point of view of human odor perception. This report is based on a recent thesis by Madany Mamlouk, Quantifying olfactory perception, at the University of Lübeck, Germany.


Item Type:Article
Related URLs:
URLURL TypeDescription
https://doi.org/10.1016/s0925-2312(02)00805-6DOIArticle
Additional Information:© 2002 Elsevier Science B.V. Available online 20 May 2003.
Subject Keywords:Olfactory perception; Multidimensional scaling; Self-organizing maps
DOI:10.1016/s0925-2312(02)00805-6
Record Number:CaltechAUTHORS:20191223-134154849
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20191223-134154849
Official Citation:Amir Madany Mamlouk, Christine Chee-Ruiter, Ulrich G. Hofmann, James M. Bower, Quantifying olfactory perception: mapping olfactory perception space by using multidimensional scaling and self-organizing maps, Neurocomputing, Volumes 52–54, 2003, Pages 591-597, ISSN 0925-2312, https://doi.org/10.1016/S0925-2312(02)00805-6. (http://www.sciencedirect.com/science/article/pii/S0925231202008056)
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:100414
Collection:CaltechAUTHORS
Deposited By: Tony Diaz
Deposited On:23 Dec 2019 21:51
Last Modified:16 Nov 2021 17:53

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