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J. Modeling Refraction Characteristics of Silicon Nitride Film Deposited in a SiH/sub 4/-NH/sub 3/-N/sub 2/ Plasma Using Neural Network. IEEE Trans. Plasma Sci. 2003, 31, pp 317–323. 32. Wang, X. ; Mahajan, R. L. Artificial Neural Network ModelBased Run-to-Run Process Controller. IEEE Trans. Components, Packaging, Manufactur. Technol. C 1996, 19, pp 19– 26. 33. Han, S. ; May, G. ; Rohatgi, A. Modeling the Growth of PECVD Silicon Nitride Films for Solar Cell Applications Using Neural Networks. IEEE Trans.

An Object-Oriented Neural Network Simulator for Semiconductor Manufacturing Applications. Proc. 8th World Multi-Conference on Systemics, Cybernetics and Informatics, 2004. ; Ruping, S. Process Improvements by Applying Neural Networks. Semiconductor International, 2002. Neumath. htm. ; Culicover, P. Neural Connections, Mental Computation. MIT Press: Cambridge, MA, 1989. White, D. ; Butler, S. ; Barna, G. G. Spatial Characterization of Wafer State Using Principal Component Analysis of Optical Emission Spectra in Plasma Etch.

2001, 9, pp 271–284. 30. -S. Use of Neural Network to Characterize a Low Pressure Temperature Effect on Refractive Property of Silicon Nitride Film Deposited by PECVD. IEEE Trans. Plasma Sci. 2004, 32, pp 84–89. 31. ; Kim, T. ; Kim, B. ; Shim, I. J. Modeling Refraction Characteristics of Silicon Nitride Film Deposited in a SiH/sub 4/-NH/sub 3/-N/sub 2/ Plasma Using Neural Network. IEEE Trans. Plasma Sci. 2003, 31, pp 317–323. 32. Wang, X. ; Mahajan, R. L. Artificial Neural Network ModelBased Run-to-Run Process Controller.

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54.Semiconductor Manufacturing by John G. Webster (Editor)


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