Proceedings of the Korean Institute of Intelligent Systems Conference (한국지능시스템학회:학술대회논문집)
- 2003.09a
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- Pages.599-602
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- 2003
Random generator-controlled backpropagation neural network to predicting plasma process data
- Kim, Sungmo (Department of Electronic Engineering, Sejong University) ;
- Kim, Sebum (Department of Electronic Engineering, Sejong University) ;
- Kim, Byungwhan (Department of Electronic Engineering, Sejong University)
- Published : 2003.09.01
Abstract
A new technique is presented to construct predictive models of plasma etch processes. This was accomplished by combining a backpropagation neural network (BPNN) and a random generator (RC). The RG played a critical role to control neuron gradients in the hidden layer, The predictive model constructed in this way is referred to as a randomized BPNN (RG-BPNN). The proposed scheme was evaluated with a set of experimental plasma etch process data. The etch process was characterized by a 2
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