Ex situ plasma diagnosis by recognition of X-ray photoelectron spectroscopy data using a neural network

Materials and Manufacturing Processes

Volumn 23, Issue 5, 2008, Pages 528-532

  Kim, Byungwhan ^a   Kim, Gi Tae ^a   Lee, Hwa Jun ^a  

^a Sejong University   (South Korea)

Author keywords

Backpropgation neural network; Chemical states; Diagnosis; Ex situ; Fault; Identification; Model; Modular neural network; Monitoring; Plasma equipment; Prediction; Principal component analysis; Semiconductor; Thin film surface; Training factor

Indexed keywords

ADMINISTRATIVE DATA PROCESSING; ELECTRIC FAULT CURRENTS; ELECTRON SPECTROSCOPY; FINANCIAL DATA PROCESSING; IMAGE CLASSIFICATION; MOLECULAR ORBITALS; MOLECULAR SPECTROSCOPY; NEURAL NETWORKS; PHOTOELECTRICITY; PHOTOELECTRON SPECTROSCOPY; PHOTOELECTRONS; PHOTOIONIZATION; PHOTONS; PLASMA DIAGNOSTICS; PLASMAS; PRINCIPAL COMPONENT ANALYSIS; SINGLE CRYSTAL SURFACES; SPECTRUM ANALYSIS;

(I ,J) CONDITIONS; APPLIED (CO); BACK PROPAGATION NEURAL NETWORK (BPANN); DATA VARIANCE; EX SITU; FAULT DIAGNOSIS (FD); MODEL ACCURACY; MODEL PERFORMANCE; MODULAR NETWORKS; NEURON NUMBERS; PREDICTION ERRORS; PRINCIPAL COMPONENT ANALYSIS (PCA); PROCESS PARAMETERS; X RAY PHOTOELECTRON SPECTROSCOPY (XPS);

X RAY PHOTOELECTRON SPECTROSCOPY;

EID: 46149116376     PISSN: 10426914     EISSN: 15322475     Source Type: Journal    
DOI: 10.1080/10426910802104310     Document Type: Article

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