Pattern analysis for machine olfaction: a review Export

@article{citeulike:3480628, abstract = {Pattern analysis constitutes a critical building block in the development of gas sensor array instruments capable of detecting, identifying, and measuring volatile compounds, a technology that has been proposed as an artificial substitute for the human olfactory system. The successful design of a pattern analysis system for machine olfaction requires a careful consideration of the various issues involved in processing multivariate data: signal-preprocessing, feature extraction, feature selection, classification, regression, clustering, and validation. A considerable number of methods from statistical pattern recognition, neural networks, chemometrics, machine learning, and biological cybernetics have been used to process electronic nose data. The objective of this review paper is to provide a summary and guidelines for using the most widely used pattern analysis techniques, as well as to identify research directions that are at the frontier of sensor-based machine olfaction.}, author = {Gutierrez-Osuna, R.}, booktitle = {Sensors Journal, IEEE}, citeulike-article-id = {3480628}, citeulike-linkout-0 = {http://dx.doi.org/10.1109/JSEN.2002.800688}, citeulike-linkout-1 = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1021060}, doi = {10.1109/JSEN.2002.800688}, journal = {Sensors Journal, IEEE}, keywords = {gas, neural\_network}, number = {3}, pages = {189--202}, posted-at = {2008-12-09 01:46:14}, priority = {2}, title = {Pattern analysis for machine olfaction: a review}, url = {http://dx.doi.org/10.1109/JSEN.2002.800688}, volume = {2}, year = {2002} }

TY - JOUR ID - citeulike:3480628 L3 - citeulike-article-id:3480628 N2 - Pattern analysis constitutes a critical building block in the development of gas sensor array instruments capable of detecting, identifying, and measuring volatile compounds, a technology that has been proposed as an artificial substitute for the human olfactory system. The successful design of a pattern analysis system for machine olfaction requires a careful consideration of the various issues involved in processing multivariate data: signal-preprocessing, feature extraction, feature selection, classification, regression, clustering, and validation. A considerable number of methods from statistical pattern recognition, neural networks, chemometrics, machine learning, and biological cybernetics have been used to process electronic nose data. The objective of this review paper is to provide a summary and guidelines for using the most widely used pattern analysis techniques, as well as to identify research directions that are at the frontier of sensor-based machine olfaction. IS - 3 JF - Sensors Journal, IEEE EP - 202 TI - Pattern analysis for machine olfaction: a review VL - 2 T2 - Sensors Journal, IEEE SP - 189 KW - gas KW - neural_network AU - Gutierrez-Osuna, R PY - 2002/// UR - http://dx.doi.org/10.1109/JSEN.2002.800688 ER -