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Predictive modeling and analysis of HfO2 thin film process based on Bayesian information criterion using PCA-based neural networks

Surface and interface analysis, 2013-09, Vol.45 (9), p.1334-1339

2013

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Formation of p-type ZnO film on InP substrate by phosphor doping

Applied surface science, 2003-04, Vol.210 (3), p.177-182

2003

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Characterization and process effects of HfO2 thin films grown by metal-organic molecular beam epitaxy

Materials science & engineering. B, Solid-state materials for advanced technology, 2005-11, Vol.123 (1), p.20-30

2005

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A Modeling Toolbox and Its Applications to Statistical Process Modeling

Journal of software, 2013-11, Vol.8 (11), p.2706-2706

2013

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Characteristics and processing effects of ZrO2 thin films grown by metal-organic molecular beam epitaxy

Applied surface science, 2004-04, Vol.227 (1-4), p.387-398

2004

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Piecewise Regression Model for Solenoid Embedded Inductors Based on the Quasi-newton Method

Transactions on Electrical and Electronic Materials, 2005, 6(6), , pp.256-261

2005

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Investigation of cell gap on the polymer substrates using statistical modelling for flexible liquid crystal display applications

International journal of nanomanufacturing, 2008, Vol.2 (4), p.361

2008

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PCA-Based Neural Network Modeling Using the Photoluminescence Data for Growth Rate of ZnO Thin Films Fabricated by Pulsed Laser Deposition

Advances in Neural Networks - ISNN 2006, p.1099-1104

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Piecewise Regression Model for Solenoid Embedded Inductors Based on the Quasi-newton Method

Transactions on electrical and electronic materials, 2005-12, Vol.6 (6), p.256-261

2005

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Predictive modeling and analysis of HfO 2 thin film process based on Bayesian information criterion using PCA‐based neural networks

Surface and interface analysis, 2013-09, Vol.45 (9), p.1334-1339

2013

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Predictive modeling and analysis of HfO sub(2) thin film process based on Bayesian information criterion using PCA-based neural networks

Surface and interface analysis, 2013-09, Vol.45 (9), p.1334-1339

2013

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Comparison of Latin Hypercube Sampling andSimple Random Sampling Applied to Neural NetworkModeling of HfO2 Thin Film Fabrication

Transactions on Electrical and Electronic Materials, 2006, 7(4), , pp.210-214

2006

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Regular Paper : Process Effect on the RMS Roughness of HfO2 Thin Films Grown by MOMBE

Transactions on electrical and electronic materials, 2007-04, Vol.8 (2), p.58

2007

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Statistical modeling of the electrical characteristics for HfO 2 thin films grown by MOMBE for high- k dielectric applications

Journal of materials processing technology, 2008, Vol.203 (1), p.454-460

2008

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Process Effect on the RMS Roughness of CuInSe 2 Thin Films Grown by MOMBE

Transactions on electrical and electronic materials, 2007, Vol.8 (2), p.58-66

2007

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Regular Paper : Comparison of Latin Hypercube Sampling and Simple Random Sampling Applied to Neural Network Modeling of HfO2 Thin Film Fabrication

Transactions on electrical and electronic materials, 2006-08, Vol.7 (4), p.210

2006

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Neural network based modeling of HfO 2 thin film characteristics using Latin Hypercube Sampling

Expert systems with applications, 2007, Vol.32 (2), p.358-363

2007

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Time delay neural network modeling for particle size in SAG mills

Powder technology, 2010, Vol.205 (1-3), p.250-262

2010

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PCA-based network modeling using standardized X-ray diffraction data for the electrical characteristics of the HfO2 thin films grown by MOMBE

2007 International Semiconductor Device Research Symposium, 2007, p.1-2

2007

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Comparison of Latin Hypercube Sampling and Simple Random Sampling Applied to Neural Network Modeling of HfO 2 Thin Film Fabrication

Transactions on electrical and electronic materials, 2006, Vol.7 (4), p.210-214

2006

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Characterization and process effects of HfO2 thin films grown by metal-organic molecular beam epitaxy

Materials science & engineering. B, Solid-state materials for advanced technology, 2005-11, Vol.123 (1), p.20-30

2005

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Neural network based modeling for the growth rate of ZnO thin films on the pulsed laser deposition

International Meeting for Future of Electron Devices, 2004, 2004, p.79-80

2004

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Characterization and process effects of HfO 2 thin films grown by metal-organic molecular beam epitaxy

Materials science & engineering. B, Solid-state materials for advanced technology, 2005, Vol.123 (1), p.20-30

2005

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Process Effect on the RMS Roughness of CuInSe 2 Thin Films Grown by MOMBE

Transactions on electrical and electronic materials, 2007-04, Vol.8 (2), p.58-66

2007

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Comparison of Latin Hypercube Sampling and Simple Random Sampling Applied to Neural Network Modeling of HfO 2 Thin Film Fabrication

Transactions on electrical and electronic materials, 2006-08, Vol.7 (4), p.210-214

2006

Volltextzugriff (PDF)

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Predictive modeling and analysis of HfO2 thin film process based on Bayesian information criterion using PCA-based neural networks

Formation of p-type ZnO film on InP substrate by phosphor doping

Characterization and process effects of HfO2 thin films grown by metal-organic molecular beam epitaxy

A Modeling Toolbox and Its Applications to Statistical Process Modeling

Characteristics and processing effects of ZrO2 thin films grown by metal-organic molecular beam epitaxy

Piecewise Regression Model for Solenoid Embedded Inductors Based on the Quasi-newton Method

Investigation of cell gap on the polymer substrates using statistical modelling for flexible liquid crystal display applications

PCA-Based Neural Network Modeling Using the Photoluminescence Data for Growth Rate of ZnO Thin Films Fabricated by Pulsed Laser Deposition

Piecewise Regression Model for Solenoid Embedded Inductors Based on the Quasi-newton Method

Predictive modeling and analysis of HfO 2 thin film process based on Bayesian information criterion using PCA‐based neural networks

Predictive modeling and analysis of HfO sub(2) thin film process based on Bayesian information criterion using PCA-based neural networks

Comparison of Latin Hypercube Sampling andSimple Random Sampling Applied to Neural NetworkModeling of HfO2 Thin Film Fabrication

Regular Paper : Process Effect on the RMS Roughness of HfO2 Thin Films Grown by MOMBE

Statistical modeling of the electrical characteristics for HfO 2 thin films grown by MOMBE for high- k dielectric applications

Process Effect on the RMS Roughness of CuInSe 2 Thin Films Grown by MOMBE

Regular Paper : Comparison of Latin Hypercube Sampling and Simple Random Sampling Applied to Neural Network Modeling of HfO2 Thin Film Fabrication

Neural network based modeling of HfO 2 thin film characteristics using Latin Hypercube Sampling

Time delay neural network modeling for particle size in SAG mills

PCA-based network modeling using standardized X-ray diffraction data for the electrical characteristics of the HfO2 thin films grown by MOMBE

Comparison of Latin Hypercube Sampling and Simple Random Sampling Applied to Neural Network Modeling of HfO 2 Thin Film Fabrication

Characterization and process effects of HfO2 thin films grown by metal-organic molecular beam epitaxy

Neural network based modeling for the growth rate of ZnO thin films on the pulsed laser deposition

Characterization and process effects of HfO 2 thin films grown by metal-organic molecular beam epitaxy

Process Effect on the RMS Roughness of CuInSe 2 Thin Films Grown by MOMBE

Comparison of Latin Hypercube Sampling and Simple Random Sampling Applied to Neural Network Modeling of HfO 2 Thin Film Fabrication

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