Recognition of olfactory signals based on supervised fuzzy C-means and k-NN algorithms
- 31 July 2001
- journal article
- research article
- Published by Elsevier in Pattern Recognition Letters
- Vol. 22 (9) , 1007-1019
- https://doi.org/10.1016/s0167-8655(01)00040-x
Abstract
No abstract availableKeywords
This publication has 14 references indexed in Scilit:
- Electronic noses: prospects for applications in Australian industryPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2002
- The how and why of electronic nosesIEEE Spectrum, 1998
- Fuzzy clustering with partial supervisionIEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics), 1997
- Similarity Metric Learning for a Variable-Kernel ClassifierNeural Computation, 1995
- Learning Boolean concepts in the presence of many irrelevant featuresArtificial Intelligence, 1994
- Model-Based Gaussian and Non-Gaussian ClusteringPublished by JSTOR ,1993
- Detection of vapours and odours from a multisensor array using pattern-recognition techniques Part 2. Artificial neural networksSensors and Actuators B: Chemical, 1992
- Detection of vapours and odours from a multisensor array using pattern recognition Part 1. Principal component and cluster analysisSensors and Actuators B: Chemical, 1991
- Knowledge acquisition via incremental conceptual clusteringMachine Learning, 1987
- Algorithms of fuzzy clustering with partial supervisionPattern Recognition Letters, 1985