BACKPROPAGATION (NEURAL) NETWORKS FOR FAST PRE-EVALUATION OF SPECTROSCOPIC ELLIPSOMETRIC MEASUREMENTS

被引:9
作者
FRIED, M
MASA, P
机构
[1] UNIV TWENTE,FAC ELECT ENGN IC TECHNOL,7500 AE ENSCHEDE,NETHERLANDS
[2] UNIV TWENTE,DEPT ELECTR,7500 AE ENSCHEDE,NETHERLANDS
关键词
D O I
10.1063/1.356281
中图分类号
O59 [应用物理学];
学科分类号
摘要
We show that a certain type of artificial neural systems or neural networks, more specifically the backpropagation network (BPN), can be an efficient tool in fast, approximate pre-evaluation of spectroscopic ellipsometric (SE) measurements. The BPN is a multilayer, feedforward network which can perform nontrivial mapping functions. We demonstrate the method on separation by implantation of oxygen (SIMOX) structure and ion implantation caused damage depth profile evaluation. The results are compared with others from independent measurements.
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页码:2194 / 2201
页数:8
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