Dongkwon Lee
LG Chem
20 Papers
169 Citations
Dongkwon Lee is an academic researcher from LG Chem. The author has contributed to research in topics: Kernel method & Spinning cone. The author has an hindex of 9, co-authored 20 publications. Previous affiliations of Dongkwon Lee include Pohang University of Science and Technology & Yeungnam University.
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Papers
Fault identification for process monitoring using kernel principal component analysis
TL;DR: Two new statistics which represent the contribution of each variable to the monitoring statistics, Hotelling's T 2 and squared prediction error of kernel PCA, respectively are defined.
314
New gene selection method for classification of cancer subtypes considering within‐class variation
TL;DR: A new criterion for measuring the relevance of individual genes by using mean and standard deviation of distances from each sample to the class centroid in order to treat the well‐known problem of gene selection, large within‐class variation.
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Robust PID tuning for Smith predictor in the presence of model uncertainty
TL;DR: In this paper, the equivalent gain plus time delay (EGPTD) is introduced to incorporate robust stability in PID tuning of the Smith predictor, which can cope with simultaneous uncertainties in all parameters of the model in an efficient manner.
69
Gene selection and classification from microarray data using kernel machine.
TL;DR: This work proposes a methodology that can effectively select an informative subset of genes and classify the subtypes (or patients) of disease using the selected genes.
62
Nonlinear regression using RBFN with linear submodels
TL;DR: This paper presents an extended version of the traditional RBFN that has a linear function of inputs as a connecting weight, which is functionally equivalent to the first-order Sugeno fuzzy model and gives considerably better performance and shows faster learning in comparison to previous methods.
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