Functional kernel-based modeling of wavelet compressed optical emission spectral Data: Prediction of plasma etch process

IEEE Sensors Journal

Volumn 10, Issue 3, 2010, Pages 746-754

  Ko, Young Don ^a   Jeong, Young Seon ^b   Jeong, Myong Kee ^c   Garcia Diaz, Alberto ^d   Kim, Byungwhan ^e  

^a LAURENTIAN UNIVERSITY   (Canada)

^b DEPARTMENT OF INDUSTRIAL AND SYSTEMS ENGINEERING   (United States)

^c the State University of New Jersey   (United States)

^d University of Tennessee Knoxville   (United States)

^e Sejong University   (South Korea)

Author keywords

Bayesian information criterion (BIC); Kernel; Multiple linear regression (MLR); Neural network (NN); Optical emission spectroscopy (OES); Partial least squares (PLSs); Plasma process modeling; Principal component analysis (PCA); Wavelet thresholding

Indexed keywords

BAYESIAN INFORMATION CRITERION; MULTIPLE LINEAR REGRESSION (MLR); MULTIPLE LINEAR REGRESSIONS; PARTIAL LEAST SQUARES; PLASMA PROCESS; WAVELET THRESHOLDING; RIDGE REGRESSION;

BAYESIAN NETWORKS; EMISSION SPECTROSCOPY; FAULT DETECTION; KNOWLEDGE BASED SYSTEMS; LIGHT EMISSION; LINEAR REGRESSION; NEURAL NETWORKS; OPTICAL EMISSION SPECTROSCOPY; PHOTORESISTS; PLASMAS; SPECTRUM ANALYSIS;

PRINCIPAL COMPONENT ANALYSIS;

EID: 77649178075     PISSN: 1530437X     EISSN: None     Source Type: Journal    
DOI: 10.1109/JSEN.2009.2038569     Document Type: Article

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